Service businesses must keep finding new ways to add value to existing clients while removing barriers that slow growth. Overcoming the challenges of outdated HR planning and human resource management (HRM), contract management, and CRM systems are table stakes for staying competitive.
FinancialForce’s Summer 22 release aims to turn those weaknesses into strengths with one of the most comprehensive releases they’ve had lately. “Organizations continue to be buffeted by market disruptions, from spiraling inflation to new COVID variants and unanticipated supply chain issues,” said Scott Brown, President and Chief Executive Officer of FinancialForce. “Our new Services-as-a-Business approach delivers the automation, intelligence, and innovation that services organizations need to become more agile so they can expertly turn disruption into opportunity.”
Improving Opportunity-to-Renewal Is Key
FinancialForce’s Summer 2022 release reflects how services businesses need to gain greater visibility and control across to their opportunity-to-renewal process while growing more resilient to spiraling costs, uncertain supply chains, and chronic labor shortages. They need to take on these challenges and keep growing. FinancialForce believes its Business-as-a-Service unified platform can strengthen services’ traditionally weak areas (integrated HR, CRM, & contract management) without giving up on how fast they can react to new opportunities.
CEOs and COOs running several leading professional services firms spoken with recently say that tight labor markets, rising prices, and blind spots in the opportunity-to-renewal cycles are hurting revenue. As a result, they’re seeing a drain in Annual Recurring Revenue (ARR) and Customer Lifetime Value at risk. They also see that the blind spots in Contract Management, Configure, Price & Quote (CPQ), Resource Management, and Financial Planning & Analysis (FPA) across opportunity-to-renewal grow wider the more diverse their client bases become. What’s needed is a 360-degree view of the opportunity-to-renewal process that encompasses every aspect of service operations, from sales to delivery to customer success management, financial management, and planning.
FinancialForce’s Summer 22 release introduces Business-as-a-Service to bridge the gaps in the opportunity-to-renewal process, improving customer experiences, and driving faster growth by enabling greater real-time collaboration and visibility organization-wide.
Skills Matching & Scheduling Speed Is A Services Killer App
In the Summer 22 Release, FinancialForce strikes at the heart of what challenges services businesses face the most regarding getting staffing right. Skills matching is new in the release, providing Resource Managers with the insights they need to identify skills related to open roles as either Essential or Desirable. The goal is to bring greater accuracy and speed into the assignment process to control for costs, usage rates, and margin impacts while assigning associates to one project versus another.
Optimizing project schedules and seeing potential scheduling conflicts in real-time helps improve scheduling efficiency by identifying potential project conflicts early and alleviating them by balancing available hours.
A New Streamlined UX Pays Off For Services CPQ
The Summer 22 release marks the first time FinancialForce ERP Cloud and Professional Services (PS) Cloud run entirely on the Salesforce Lightning Experience (LEX). During the FinancialForce analyst briefing, Heidi Minzner, Vice President, Product Management (ERP Cloud) at FinancialForce, demonstrated how users could create, manage and update line-level data on requisitions and purchase orders in a single view. Additionally, LEX is evident across the entire platform.
Of the many improvements announced in the Summer 22 release, updates to Services CPQ are noteworthy. The updated Services CPQ interface built on LEX has streamlined estimates creation and provides options for defining date-driven rates. Reflecting how services businesses need more role management capabilities, the Summer 22 release can enable role requests from templates and also supports pass-through of needed skills.
Services’ CPQ improvements are based partly on the platform’s flexibility LEX provides.
William Spice, Senior Director of Product Management says that Services CPQ and Customer Success Cloud are born in LEX, providing FinancialForce with the flexibility of using the latest Salesforce visual UI to deliver greater simplicity of workflows. “Services CPQ shows us extending the footprint across the whole services lifecycle, allowing our customers to build up a range of different estimates for professional services work, widen the selling and opportunity phase, and then seamlessly be able to transition these into a delivery model,” William said.
“Customer Success Cloud is really focused on making it simple and automatic to create playbooks, which are means for anyone across the organization to help ensure that we’re treating our customers with all the respect and impact they would expect from us. And finally, performance to scale sees us continuing to invest and make sure that our applications scale faster than any of our customers can, and focusing on enterprise-level integrations like linking out of the box with JIRA and Concur, for example,” William concluded.
Improving Opportunity-to-Renewal With More Intelligence
Services CPQ’s improvements reflect revenue managers’ need for greater visibility into their sales pipelines and more insights into the propensity to close by client. FinancialForce takes that a step further by providing insights into which factors are most and least affecting opportunity-to-renewal performance.
Current FinancialForce customers have access to dashboards that deliver utilization performance and staffing efficiency and can be configured to provide revenue forecasting. Also announced is a project burn-up dashboard that visualizes work completed and enables teams to be more cost-efficient during project delivery.
Improving Services Revenue With Real-time Visibility And Control
Business-as-a-Service is predicated on the design goal of enabling any business to migrate into providing services profitably. As a result, product-centric companies’ transition to services is commonplace. Nearly every major equipment manufacturer is now selling the value delivered by their machinery as a service.
The many improvements FinancialForce has made in their platform’s Financial Planning & Analysis (FP&A) areas reflect how this area is core to getting service revenue right. Of the many announcements made in this area of their platform, highlights include providing FP&A teams with the option of performing headcount planning at the resource level to better understand how compensation adjustments will impact future budgets. In addition, flexible budget templates for improving headcount planning alignment with company goals and objectives are now included.
Also announced is a new Planning Workspace where FP&A teams can collaborate and analyze budget information and potential scenarios. The value of having the entire platform on LEX is evident in how FP&A managers can immediately use financial data to accelerate planning cycles which also drives more accurate forecasting within the Planning Workspace. Also introduced is a new machine-learning-based component to the ERP product suite. Its Intelligent bank reconciliation solution provides accounting teams the agility to match a single bank statement transaction to multiple accounting transactions. It’s also supporting a more extensive end-to-end intelligent transaction matching that streamlines reconciliation procedures. That’s welcome news for accounting teams that need the time for more intensive tasks and would like to be free from the repetitive nature of reconciliation work.
Conclusion
FinancialForce’s decision to change its cadence from four to three releases a year shows its product strategy is delving further into where the gaps are in the opportunity-to-renewal process. Concentrating on three significant releases gives their DevOps and engineering teams the time they need to develop new features while revamping the entire platform to the Salesforce Lightning Experience (LEX). Leading with usability on Services CPQ and Customer Success Cloud makes sense as services businesses need to excel in each area to grow and retain customers. Additionally, a new UX will help accelerate the ramp-up times of new users. FinancialForce enters a new era with the Summer 22 Release, closing gaps in platform strategy while helping customers do the same.
Economic uncertainty sends shock waves throughout businesses, with service organizations seeing its brunt. The recent drastic drop-off in Netflix subscribers is a case in point. Services CFOs say there is an urgent need to track how well their overarching planning strategies linking finance and operations perform. However, getting the data to analyze has been challenging for even the largest services businesses.
As a result, CFOs need Financial Planning & Analysis (FP&A) integrated with operational planning applications to make it easier to track plan performance across all P&Ls and financials. FinancialForce’s decision to launch a fully-featured FP&A on their ERP Cloud platform shows they read the services market clearly and listen to their customers’ CFOs on what matters most.
CFOs Want To Know The Financial Impact Of Every Planning Decision
Even during economic stability, finance teams struggle to get operations planning teams the data they need to predict the financial outcomes of decisions. Line-of-business leaders look to finance to provide accurate, detailed information on the financial implications of every planning decision. By having FP&A use the same data accounting, reporting and planning have, CFOs, COOs, and their teams get greater visibility and control over every aspect of budgeting and forecasting.
One of FP&A’s greatest shortcomings in the past was relying only on siloed financial data alone with little visibility into operational planning. Financial teams need access to all available data across finance and operations to do their jobs well and create accurate forecasts. Getting FP&A right with any ERP platform needs to start with the goal of delivering integrated business planning. Sales management and their teams also need visibility into FP&A reporting and analysis to manage revenue. FinancialForce’s decades of experience on the Salesforce platform combined with the integration expertise Salesforces’ MuleSoft acquisition brought to the company four years ago will increase the probability of their FP&A solution gaining adoption.
Services companies’ CFOs are grappling with new economic uncertainties every week. As a result, they’re most interested in getting greater visibility and control over the planning process, including version control, more automated multi-planning options, and more real-time enterprise-wide collaboration, all on a single platform. FinancialForce’s DevOps and product management teams deserve credit for identifying these challenges and including them in their FP&A application delivered in the Spring 2022 release.
FinancialForce’s long-awaited FP&A solution enables analysts to create multiple what-if scenarios using calculation rules and mass functions, create dynamic plans and stress-test assumptions, and better anticipate their return by area and investment.
The future of FP&A Is An Integrated Cloud
Service organizations are quicker to migrate to the cloud versus their product-based counterparts. That’s because procurement, order-to-cash, and supply chain management workflows tend to be less complex than product-based businesses. Services organizations also need financial management, procure-to-pay, and Professional Services Automation (PSA), all on the same platform to support operational planning with FP&A.
FinancialForce’s Multi-X functionality is expanded in the Spring 2022 release to simplify the consolidation of financial statements and meet the needs of multi-entity organizations. In the latest release, it’s possible to record taxes due from intercompany tax transactions, accelerating the intercompany process for taxation and reporting. The Spring 2022 release also streamlines the creation of multi-company sales invoices and simplifies consolidated financial statement preparation with consolidation group structure capabilities.
Multi-X enables the recording and sharing across a multi-tier or multi-entity business.
New localization features that are essential to running a global business were added, including support for Switzerland, Denmark, Finland, and Austria, as well as enhanced business operations in Germany and Australia. In addition, multi-X supports multi-company invoicing support and advanced invoice consolidations for multi-revenue billing. Calculating and recording tax on intercompany transactions and enabling cash matching process across companies are also supported.
FP&A’s future is an integrated cloud, further validated by FinancialForce’s’ launch of ERP Cloud, Professional Services Cloud, and enhancements to its Customer Success solutions. “In today’s business environment, organizations must be able to respond to disruptions quickly while continuing to innovate and deliver tangible outcomes to their customers,” said Dan Brown, Chief Product and Strategy Officer at FinancialForce. “Our Spring 2022 release gives our customers a richer toolset to help pursue their primary goal, delivering exceptional customer outcomes while improving the customer experience across the opportunity-to-renewal journey.”
New Professional Services (PS) Cloud additions in the Spring 2022 release include customer-requested improvements to skills and resource management, services estimating, and project management capabilities. FinancialForce’s customers have also requested improved resource management to scale their efforts to train and retain their workforce. As a result, the Spring 2022 Release adds intelligent automation to the staffing process by enabling auto-assignment of resource requests that meet specific criteria and an expanded capability to model ideal staffing scenarios across a project, opportunity, or region. These enhancements improve PS Cloud’s resource optimization capabilities and enable resource managers to deploy ever larger and more complex teams efficiently and cost-effectively.
Conclusion
Services organizations are looking for cloud-based professional services ERP systems that deliver greater forecast accuracy, faster forecasting and budgeting, and improved accountability, visibility, and control. Integrated clouds are the future of FP&A for all these factors and the need all services organizations have to improve revenue and operations performance. In addition, given the growing economic uncertainty today, CFOs also want to increase better predictability and better risk management strategies while also supporting more collaboration. All these factors combined are defining the future of FP&A in an integrated cloud, which is what FinancialForce has been doing for decades on the Salesforce platform.
AI and machine learning’s potential to drive greater visibility, control, and insight across shop floors while monitoring machines and processes in real-time continue to attract venture capital. $62 billion is now invested in 5,396 startups concentrating on the intersection of AI, machine learning, manufacturing, and Industry 4.0, according to Crunchbase.
PwC’s broader tech sector analysis shows a 30% year-over-year growth in funding rounds that reached $293.2 billion in 2021. Smart manufacturing startups are financed by seed rounds at 52%, followed by early-stage venture funding at 33%. The median last funding amount was $1.6 million, with the average being $9.93 million.
Abundant AI startup opportunities in smart manufacturing and industry 4.0
According to Gartner, “The underlying concept of Industry 4.0 is to connect embedded systems and smart production facilities to generate a digital convergence between industry, business, and internal functions and processes.” As a result, Industry 4.0 is predicted to grow from $84.59 billion in 2020 to $334.18 billion by 2028. AI and machine learning adoption in manufacturing are growing in five core fields: smart production, products and services improvements, business operations and management, supply chain, and business model decision-making. Deloitte’s survey on AI adoption in manufacturing found that 93% of companies believe AI will be a key technology to drive growth and innovation.
Machine intelligence (MI) is one of the primary catalysts driving increased venture capital investment in smart manufacturing. Startup CEOs and their customers want AI and machine learning models based on actual data, and machine intelligence is helping to make that happen. An article by McKinsey & Company provides valuable insights into market gaps for new ventures. McKinsey’s compelling data point is that those leading companies using MI achieve 3X to 4X the impact of their peers. However, 92% of leaders also have a process to track incomplete or inaccurate data – which is another market gap startups need to fill.
Based on the uplift MI creates for new smart manufacturing startup funding and the pervasive need manufacturers have to improve visibility & control across shop floors, startups have many potential opportunities. The following are five that AI and machine learning is helping to create:
AI-enabled Configure, Price, and Quote (CPQ) systems that can factor in supply chain volatility on product costs are needed. Several startups are already using AI and machine learning in CPQ workflows, and they compete with the largest enterprise software providers in the industry, including Salesforce, SAP, Microsoft, and others. However, no one has taken on the challenge of using AI to factor in how supply chain volatility changes standard and actual costs in real-time. For example, knowing the impact of pricing changes based on an allocation, how does that impact standard costs per unit on each order? Right now, an analyst needs to spend time doing that. AI and machine learning could take on that task so analysts could get to the larger, more complex, and costly supply chain problems impacting CPQ close rates and revenue.
Using AI-enabled real-time data capture techniques to identify anomalies in throughput as an indicator of machine health. The aggregated data manufacturing operations produced every day holds clues regarding each machine’s health on the shop floor. Automated data capture can identify scrap rates, yield rates and track actual costs. However, none of them can analyze the slight variations in process flow product outputs to warn of possible machine or supply chain issues. Each process manufacturing machine runs at its cadence or speed, and having an AI-based sensor system track and analyze why speeds are off could save thousands of dollars in maintenance costs and keep the line running. In addition, adding insight and intelligence to the machine’s real-time data feeds frees quality engineers to concentrate on more complex problems.
Industrial Internet of Things (IIoT) and edge computing data can be used for fine-tuning finite scheduling in real-time. Finite scheduling is part of the broader manufacturing systems organizations rely on to optimize shop floor schedules, machinery, and staff scheduling. It can be either manually intensive or automated to provide operators with valuable insights. A potential smart manufacturing opportunity is a finite scheduler that relies on AI and machine learning to keep schedules on track and make trade-offs to ensure resources are used efficiently. Finite schedulers also need greater accuracy in factoring in frequent changes to delivery dates. AI and machine learning could drive greater on-time delivery performance when integrated across all the shop floors a manufacturer relies on.
Automated visual inspections and quality analysis to improve yield rates and reduce scrap. Using visual sensors to capture data in real-time and then analyze them for anomalies is in its nascent stages of deployment and growth. However, this is an area where captured data sets can provide machine learning algorithms with enough accuracy to identify potential quality problems on products before they leave the factory. Convolutional neural networks are an effective machine learning technique for identifying patterns and anomalies in images. They’re perfect for the use case of streamlining visual inspection and in-line quality checks in discrete, batch, and process manufacturing.
Coordinated robotics (Cobots) to handle assemble-to-order product assembly. The latest cobots can be programmed to stay in sync with each other and perform pick, pack, ship, and place materials in warehouses. What’s needed are advanced cobots that can handle simple product assembly at a more competitive cost as manufacturers continue to face chronic labor shortages and often run a shift with less than half the teams they need.
Talent remains an area of need
Manufacturers’ CEOs and COOs say that recruiting and retaining enough talent to run all the production shifts they need is the most persistent issue. In addition, those manufacturers located in remote regions of the world are turning to robotics to fulfill orders, which opens up opportunities for integrating AI and machine learning to enable cobots to complete assemble-to-order tasks. The unknown impact of how fast supply chain conditions change needs work from startups, too, especially in tracking actual cost performance. These are just a few opportunities for startups looking to apply AI and machine learnings’ innate strengths to solve complex supply chain, manufacturing, quality management, and compliance challenges.
19 of the 50 top companies in the U.S. are in the tech industry, including Dell, Intel, Oracle, Salesforce, Cisco, and others.
LinkedIn identified four key trends in their analysis, with flexible work is becoming table stakes for recruiting and retaining employees.
These and many other insights are from LinkedIn Top Companies 2022: The 50 best workplaces to grow your career in the U.S., published today. All 50 companies are currently hiring and have over 530,000 jobs open across the U.S, with over 70,000 being remote positions. The LinkedIn analysis of the best companies to grow your career spans 35 global markets, including the U.S., Canada, Mexico, Brazil, Argentina, Colombia, Chile, Ireland, France, Switzerland, Austria, Germany, Israel, Italy, Spain, the U.K., Sweden, Belgium, Denmark, the Netherlands, Portugal, India, Japan, Singapore, Philippines, Malaysia, Indonesia, Australia, New Zealand, UAE, Egypt, Saudi Arabia, South Africa, Nigeria, and Kenya.
LinkedIn’s Top Companies 2022 spotlights the organizations investing in employee success and career development. LinkedIn’s methodology and internal analysis ranked companies based on seven pillars that display career progression: ability to advance, skills growth, company stability, external opportunity, company affinity, gender diversity, and educational background.
The 19 Best Tech Companies To Grow Your Career In 2022
The following are profiles of the top 19 tech companies hiring in the U.S. today with links to available positions accessible via LinkedIn:
Global headcount: 1,600,000 (with 1,100,000 in the U.S.) | Top U.S. locations: Seattle, San Francisco Bay Area, New York City | Most notable skills: Warehouse Operations, Data Entry, AWS Lambda| Most common job titles: Software Engineer, Fulfillment Associate, Warehouse Associate | Largest job functions: Operations, Engineering, Program and Project Management | What you should know: Even as the country’s second-largest private employer, Amazon continues to compete in recruiting and retaining top talent amid a competitive labor market. The company recently announced that it’s doubling its maximum base salary for corporate and tech workers, and it raised average wages for warehouse workers late last year, increasing pay for more than half a million of its employees. But the e-commerce giant is going beyond compensation, too: investing $1.2 billion over the next three years to expand its education and skills training initiatives. Amazon now pays 100% of college tuition for frontline employees as part of its Career Choice program and covers high school diploma programs, GEDs, and English proficiency certifications.
Global headcount: 156,000 | Top U.S. locations: San Francisco Bay Area, New York City, Seattle | Most notable skills: Video Editing and Production, Google Cloud Platform (GCP), C++| Most common job titles: Software Engineer, Program Manager, Product Manager | Largest job function: Engineering, Information Technology, Program and Project Management |What you should know: It’s been a big year for Alphabet: The company onboarded nearly 6,500 employees last quarter and saw significant growth across Google’s Cloud service and YouTube (whose revenues are now growing at a faster rate than Netflix). For those interested in flexibility, the tech giant has a robust offering. In addition to adopting a hybrid work model, the company told LinkedIn that Alphabet offers four ‘work from anywhere’ weeks per year, sabbaticals for long-term employees, and ‘no meeting’ days. But Alphabet has also worked to maintain a collaborative culture and support career growth while working remotely. Employees can take advantage of resource groups like Women@Google and its Googler-to-Googler training, which lets its workers get first-hand knowledge across different fields from other employees.
Global headcount: 250,000 | Top U.S. locations: New York City; Raleigh-Durham, N.C.; San Francisco Bay Area | Most special skills: Kubernetes, Openshift, Hybrid Cloud| Most common job titles: Software Engineer, Project Manager, Data Scientist | Largest job functions: Engineering, Information Technology, Sales |What you should know: The perennial IT giant has re-upped its benefits offerings amid the Great Reshuffle, IBM told LinkedIn. The new initiatives are increased paid time off, more promotion and pay reviews, backup dependent care, virtual tutoring, and ‘compassionate leave’ for parents who experience stillbirth or miscarriage. In addition, as the company moves forward with a hybrid working model that allows employees to decide how often they want to be onsite, IBM has also transformed its onboarding process with “a focus on empathy and engagement” to help remote new hires feel more connected.
Global full-time headcount: 202,600 | Top U.S. locations: Atlanta, Dallas, New York City | Most notable skills:Design Thinking, Customer Experience, Futurism| Most common job titles: Retail Sales Consultant, Client Solutions Executive, Customer Service Representative | Largest job functions: Sales, Information Technology, Engineering |What you should know: Just three years after the acquisition of Time Warner, AT&T is changing course. The company agreed to a deal last year that will combine WarnerMedia’s assets with Discovery’s to create a new, separate global entertainment giant. Once the spinoff is completed (likely mid-2022), the telecom company will be focused on its core business — expanding access to broadband internet. For its employees, AT&T offers several advancement opportunities. For example, it invests $2 million annually in ‘AT&T University,’ an internal training program to help its workers upskill, and has partnered with groups like Udacity and Coursera to offer advanced online courses.
Global headcount: 154,000 | Top U.S. locations: San Francisco Bay Area; Austin, Texas; New York City | Most notable skills: Apple Software and Hardware, Technical Learning, iOS| Most common job titles: Software Engineer, Technical Specialist, Mac Genius | Largest job functions: Engineering, Information Technology, Sales |What you should know: Apple is increasing benefits and pay for retail workers to attract and retain employees at its 270 retail stores across the U.S. — including doubling sick days for both full-time and part-time employees and granting more vacation days. Its retail employees are also eligible for paid parental leave and can access discounted emergency childcare. In addition, after being one of the first companies to tell its corporate employees to work remotely in March 2020, Apple is now asking that they return to the office three days a week.
Global headcount: 189,000 (with 130,000 in the U.S.) | Top U.S. locations: Philadelphia, New York City, Los Angeles | Most notable skills: Media Production, Cable Modems, Broadcast Television | Most common job titles: Software Engineer, Communications Technician, Salesperson | Largest job functions: Engineering, Sales, Information Technology |What you should know: Comcast prioritizes career growth and development among its employees through various benefits — including mentorship programs, department rotations and tuition assistance for continuing education and skills development. As a part of its commitment to wellbeing, it also pays for 78% of its employees’ health care costs. Want an in? Comcast says the #1 skill it looks for in new hires is authenticity. “We believe that by being yourself, you are empowered to do your best work,” the company told LinkedIn.
Global headcount: 71,900 | Top U.S. locations: San Francisco Bay Area, Seattle, New York City | Most notable skills: PHP, Program Management, Social Media Marketing| Most common job titles: Software Engineer, Technical Recruiter, Data Scientist | Largest job functions: Engineering, Information Technology, Human Resources
Dell Technologies is the parent company of Dell EMC, SecureWorks, and others.
Global headcount: 133,000 | Top U.S. locations: Austin, Texas; Boston; San Francisco Bay Area | Most notable skills: Software as a Service (SaaS), Kubernetes, Salesforce| Most common job titles: Account Executive, Software Engineer, Inside Sales Representative | Largest job functions: Sales, Information Technology, Engineering
Global headcount: 674,000 | Top U.S. locations: Washington D.C., New York City, Chicago | Most notable skills: Amazon Web Services (AWS), Management Consulting, Software Development Life Cycle (SDLC)| Most common job titles: Managing Director, Management Consultant, Business Integration Manager | Largest job functions: Information Technology, Business Development, Engineering
Global headcount: 119,400 (with 105,800 in the U.S.) | Top U.S. locations: New York City, Dallas, Washington D.C. | Most notable skills: Quotas, Wireless Technologies, Solution Selling| Most common job titles: Solutions Specialist, Customer Service Representative, Business Account Manager | Largest job functions: Sales, Engineering, Information Technology
Global headcount: 121,000 (with 55,700 in the U.S.) | Top U.S. locations: Portland, Ore.; Phoenix; San Francisco Bay Area | Most notable skills: JMP, System on a Chip (SoC), Statistical Process Control (SPC) | Most common job titles: Software Engineer, Process Engineer, System-on-Chip Design Engineer | Largest job functions: Engineering, Operations, Information Technology
Global headcount: 133,000 (46,600 in the U.S.) | Top U.S. locations: San Francisco Bay Area, Boston, Denver | Most notable skills: Oracle Cloud, NetSuite, OCI | Most common job titles: Software Engineer, Business Development Consultant, Application Sales Manager | Largest job functions: Engineering, Sales, Information Technology
Global headcount: 74,300 (41,000 in the U.S.) | Top U.S. locations: San Francisco Bay Area, Seattle, New York City | Most notable skills: Salesforce.com Administration, Salesforce Sales Cloud, Slack | Most common job titles: Account Executive, Software Engineer, Solutions Engineer | Largest job functions: Sales, Engineering, Information Technology
Cisco is the parent company of Duo Security and others.
Global headcount: 81,800 (38,800 in the U.S.) | Top U.S. locations: San Francisco Bay Area; Raleigh-Durham, N.C.; Dallas | Most notable skills: Software as a Service (SaaS), Kubernetes, Network Engineering | Most common job titles: Software Engineer, Account Manager, Program Manager | Largest job functions: Engineering, Information Technology, Sales
Global headcount: 330,600 (34,680 in the U.S.) | Top U.S. locations: New York City, Dallas, Chicago | Most notable skills: Amazon Web Services (AWS), Software Development Life Cycle (SDLC), Agile & Waterfall Methodologies| Most common job titles: Project Manager, Software Engineer, Technical Lead | Largest job functions: Engineering, Information Technology, Program and Project Management
Siemens is the parent company of Mendix and others.
Global headcount: 303,000 (with 40,000 in the U.S.) | Top U.S. locations: New York City, Philadelphia, Atlanta | Most notable skills: Building Automation, HVAC Controls, Electrical Troubleshooting | Most common job titles: Project Manager, Software Engineer, Senior Sales Executive | Largest job functions: Engineering, Sales, Operations
Global headcount: 10,400 (with 4,400 in the U.S.) | Top U.S. locations: San Francisco Bay Area, Boston, Washington D.C. | Most notable skills: Junos, Kubernetes, Border Gateway Protocol (BGP)| Most common job titles: Software Engineer, System Engineer, Technical Support Engineer | Largest job functions: Engineering, Sales, Information Technology
Viasat is the parent company of RigNet and others.
Global headcount: 5,800 | Top U.S. locations: San Diego, Denver, Atlanta | Most notable skills: RF Test, Amazon Web Services (AWS), Satellite Communications (SATCOM)| Most common job titles: Software Engineer, Program Manager, System Engineer | Largest job functions: Engineering, Information Technology, Operations
Global headcount: 5,000 (with 3,000 in the U.S.) | Top U.S. locations: Boston, Detroit, Los Angeles | Most notable skills: MATLAB, Simulink, Deep Learning| Most common job titles: Software Engineer, Application Support Engineer, Principal Software Engineer | Largest job function: Engineering, Information Technology, Sales
Flexible work is becoming table stakes for recruiting and retaining employees. With job seekers and employees in the driver’s seat and able to ask for the work-life balance they need, flexible work has become required to attract and retain top talent. Most companies on this year’s list offer some form of work-from-anywhere flexibility, with more than 70,000 remote jobs open now across the top 50 companies. Many companies also allow employees to set their schedules and work custom “on” hours through asynchronous work. Some, like Amazon (#1), Raytheon Technologies (#21), and General Motors (#44), are encouraging work-life balance with company-wide days off, while others offer unlimited paid vacation and sabbaticals. In addition, many companies are testing out new flexible offerings – employees at Cisco (#30) have adopted a four-day workweek through the company’s Interim Reduced Workweek program, IBM (#6) has set mandatory “off” hours, Cognizant (#33) offers the option to work a compressed week through its WorkFlex program, Realogy (#40) has a no meetings policy on “Focus Fridays,” Publicis Groupe (#41) allows employees the freedom to work from anywhere they like for up to six weeks per year and PwC (#32) allows employees to step away from work for up to six months while paid through its new Leave of Absence program.
Top companies offer stability in an unstable world. While many companies across the U.S. have faced challenges and disruptions over the last year, the Top Companies offer stability and upskilling opportunities that employees can count on – from tuition assistance and PTO for professional development to mentorship programs and job shadowing. Many organizations instituted new programs to retain employees. For example, Deloitte (#11) introduced a new Talent Experience Office focused on employee sentiments and preferences to help inform company choices, EY (#22) offers a Pathway to Purpose virtual program to help employees discover and live their personal purpose and vision, and Kimley-Horn (#31) offers job rotations, so employees learn from different roles and departments. Amazon (#1) is investing $1.2 billion to expand its education and skills training initiatives, Walmart (#5) gives field-based associates access to a no-cost college degree through its Live Better U program, and Verizon (#18) offers an apprenticeship program for those facing employment loss due to automation in technology to prepare them for the jobs of the future. PwC (#32) invested $3 billion in a “New World. New Skills” commitment to equip employees with digital training and awarded a “thank you” bonus of one-week extra pay. Bank of America (#8) provided an additional $1 billion in compensation stock awards to employees globally, and Northrop Grumman (#38) enhanced their annual bonus plan in addition to their ongoing stay interviews.
Mental health care is going mainstream across hiring and talent management. To keep employees healthy and happy at work, almost all of this year’s honorees now provide services that address mental health and well-being. Companies like Intel (#23), Salesforce (#28), and Juniper Networks (#46) provide dedicated mental health days, with many – including FedEx (#47) and Blackstone (#43) – offering company-paid mental health benefits. In addition, EY (#22) has expanded its no-cost counseling and mental health coaching sessions to 25 per year for employees and family. Deloitte (#11) provides a $1,000 well-being subsidy in addition to individualized psychological health resources. Unitedhealth Group (#13) provides complimentary access to wellness apps offering coaching, talk therapy, and more.
Authenticity, compassion, and curiosity are must-have skills. Most of the Top Companies do not require college degrees and instead look for soft skills that can translate across departments and roles. For example, the #1 skill Comcast (#10) seeks in new hires is authenticity, HCA Healthcare (#37) wants new hires to possess compassion, and Dell Technologies (#14) looks for people who thrive in an environment with a diversity of people and ideas. Accenture (#17), Oracle (#27), and Lockheed Martin (#29) value candidates with curiosity and eagerness to learn and grow. Alphabet (#2) looks for problem-solving skills and a growth mindset.
Bottom Line: Every business needs to resolve in 2022 to treat cybersecurity as a business decision first because the risk to operations and revenue are too great if they don’t.
Predictions don’t protect businesses, professional guidance does. Intending to provide every business, especially startups, with insights they can use to protect themselves in 2022, I’ve interviewed several cybersecurity CEOs. Their recommendations on what every business can do to improve their cybersecurity and avert a potential breach, ransomware attempt, or worse are provided below:
BOS Framework Founder and CEO Sashank Purighalla
Before BOS, Sashank founded and served as the CEO of 5Y Solutions, Inc., a DevOps company that provides SaaS and enterprise-class technology solutions based in the cloud, AR, VR, IoT, Media Streaming, and Big Data spaces. 5Y has offices in the US, Australia, and India. Much of Sashank’s 20+ years of experience has involved developing enterprise-class technology solutions, strong strategic and long-range planning, setting business and technology strategies in B2B and B2C environments, and leading and motivating diverse teams to build high-impact SaaS and PaaS products. Sashank has a bachelor’s degree in Mechanical Engineering and a master’s degree in Computer Science.
Advice from Sashank Purighalla Founder and CEO at BOS Framework
“The biggest problem that enterprises are dealing with is with fractured technology architectures. The playbook for how technology systems are designed and maintained has fundamentally changed over the past 5 years with the advent of DevOps as a new disciple geared toward bringing efficiency to the PDLC process. To help meet this growing demand, there has been nearly a 570% increase in the number of known niche tools. Here’s the strange dichotomy: In the same timeframe, there has been an over 630% increase in the number of cyber breaches and over 600% increase in technology management and maintenance costs.
The fact is that you cannot patch disparate systems with non-standardized implementations using niche tools and expect to achieve security. Breach resilience and systemic integration can only result from sound systemic architectures that are based on best practices.
Enterprises must shift their focus from thinking of the next tool for efficiency or patching gaps to consistent architectures for effective holistic outcomes. This is an ecosystem problem and can only be addressed at an organizational architecture level”.
Founder Shield Co-Founder & CEO Benji Markoff
Benji Markoff is the Co-Founder & CEO of Founder Shield. He has an obsession with culture and the science behind it. He wants his legacy to be the success and positivity that everyone who works at Founder Shield brings to the world, whether at Founder Shield or in any their future endeavors. He hopes that Founder Shield provides a platform for unlimited success and happiness for all that work there.
Advice from Benji Markoff, Co-Founder & CEO of Founder Shield
“It’s old news that cybercriminals have beefed up their attacks, with ransomware and phishing topping every bad actor’s to-do list, it seems. The pandemic spotlighted weak links in cybersecurity systems nationwide, and hackers didn’t waste one minute to attack — back door, front door, didn’t matter. Hybrid work schedules and burnt-out IT specialists make the waters even murkier. Naturally, cyber liability insurance is a hot commodity currently, and the insurance industry plays a significant role in helping companies stay protected. Unfortunately, the attacks keep coming. Flip the script, though, and all these negative headlines can serve as lessons learned. For starters, let’s remember that cross-functionality value also translates to cybersecurity training. The more employers raise awareness and implement in-depth training, the lower they’ll fall on a hacker’s checklist. Keep cybersecurity top-of-mind throughout your entire company. Also, don’t be shy about relying more heavily on your managed service provider (MSP). These companies are ever-broadening their scope of services. If eyes and ears are what you need, start negotiating new MSP contracts.”
Hexnode Founder and CEO Apu Pavithran
Apu Pavithran is the founder and CEO of Hexnode. Recognized in the IT management community as a consultant, speaker, and thought leader, Apu has been a strong advocate for IT governance and Information security management. In addition, he’s passionate about entrepreneurship and spends significant time working with startups and empowering young entrepreneurs.
Advice from Apu Pavithran, founder and CEO of Hexnode
“Enterprise customers in 2022 are looking for a seamless digital experience that they can adopt immediately. Unfortunately, while catering to this need businesses tend to overlook the cybersecurity risks involved in making this possible.
In practice, cybersecurity decisions mostly take the backseat when associated with budgetary needs and business priorities, however, what comes with that is a successful ransomware attack that can completely turn the equation upside down. So, while adopting a flexible working environment in a constantly changing IT landscape, I would strongly recommend having a device security policy and a UEM in place. This helps keep your sensitive information safe by making sure employee devices are always compliant.
A patch management solution that comes along with the UEM solution will monitor your devices to make sure that there are no security vulnerabilities. The solution will also make sure that your device is running on the latest OS update and protected from threat actors.
Endpoint security solutions like UEM’s will help secure businesses to an extent, But having the right tools can’t always ensure that your businesses are 100% secure. The biggest threat is always the human element in cyber security. So make sure that in your flexible work environment your employees are cyber aware with regular cyber awareness classes that cover updated cybersecurity best practices.”
Ivanti CEO Jeff Abbott
As CEO of Ivanti, Jeff Abbott oversees all aspects of the company’s growth strategy and direction. Before becoming CEO of Ivanti in October 2021, Jeff served as Ivanti’s President since January 2020. Jeff has over 25 years of experience working for enterprise software and services companies, including Accenture, Oracle, and Infor. Jeff holds degrees from the University of Tennessee and Georgia State University. He sits on the National Alumni Board at the University of Tennessee and has previously held board positions with the Georgia Leukemia and Lymphoma Society and the Posse Foundation.
Advice from Ivanti CEO Jeff Abbott:
The rapid shift to remote work has accelerated growth in new digital systems and workflows, leading to expanded enterprise attack surfaces. At the same time, threat actors have matured their tactics and targeted enterprise security gaps. For example, attackers have increasingly waged phishing attacks at mobile devices, which remote workers are using more than ever before, via text and SMS messages, instant messages, social media, and other modes of communication, beyond just corporate email. Ransomware has also continued to evolve, with attackers increasingly leveraging known vulnerabilities that have remote code execution and privilege escalation capabilities. Ransomware is a business, and threat actors are incentivized to find companies that are more likely to pay.
Organizations are struggling to proactively combat these growing cyber threats. A new study by Ivanti revealed that 71% of IT and security professionals found patching to be overly complex and time-consuming. 57% of respondents stated that the global transition towards a decentralized workspace has made patch management more complex to deal with. And 53% said that organizing and prioritizing vulnerabilities takes up most of their time. This is alarming because the longer vulnerabilities remain unpatched, the more exposed a business is at risk of an attack or ransomware.
To effectively mitigate risk, companies should implement a Zero Trust security strategy. At its simplest, Zero Trust provides organizations continuous evaluation of their employee devices, endpoints, assets, and networks that business relies on. As part of an overall Zero Trust strategy, companies should invest in automated controls that proactively perform cyber hygiene tasks and reduce security risk across infrastructure and applications. This includes leveraging a combination of risk-based vulnerability prioritization and automated patch intelligence to identify and prioritize vulnerability weaknesses and then accelerate remediation. A proactive, end-to-end risk-based assessment strategy can drive business value and further reduce the mean time to detect, discover, remediate, and respond to cyber threats.
Orchestral Founder and EVP Dale Smith As Orchestral’s Head of Revenue Technology & Operations, Dale leads the digital infrastructure team responsible for integrating customer-facing operations across marketing, sales, and customer success to deliver extraordinary customer experiences that accelerate revenue performance. Dale has over 30+ years of experience in the tech industry, including several roles that include engineering, marketing, business development, and product management. His current startup, Orchestral.ai, provides AI-enabled IT workflow automation & orchestration technologies that facilitate digital transformation for some of the world’s largest enterprises.
Advice from Orchestral Founder and EVP Dale Smith
“Although there is an increasing amount of attention given to automation within the cybersecurity sector, there are still many gaps between the countless tools and SOAR/SIEM platforms found in a typical enterprise’s cybersecurity infrastructure.
To be sure, cybersecurity automation is a welcome and necessary focus for innovation in threat intelligence and response. But, as organization’s adopt cybersecurity automation, they are likely to discover that significant human intervention is still required to bridge the “silos of automation” that naturally develop around highly specialized security tools and platforms. It is at this point when the focus should shift to “cybersecurity orchestration”. Cybersecurity orchestration intelligently integrates all of the different and disparate tools, platforms and siloed automations so that information is shared across the entire cybersecurity infrastructure. In this context, cybersecurity automation and cybersecurity orchestration are complimentary stages of focus for developing security infrastructure capable of coordinating a truly “autonomous” threat response.”
Prometeo Co-Founder and CEO Rodrigo Tumaián
Rodrigo Tumaián is co-founder of Prometeo, a startup in the fintech area. He is also a co-founder of Truss, a company that provides information security services in the financial sector. His extensive experience working with national and international companies has enabled him to learn to adapt to any type of environment and help customers across a broad spectrum of business models, industries and revenue levels.
Advice from Prometeo Co-Founder and CEO Rodrigo Tumaián
“When we talk about Cybersecurity month to encourage awareness around the topic, we should keep in mind that it is something we must take action on every day. The repercussions that are caused when we find ourselves in the middle of a problem or a serious cybersecurity issue, profoundly impact our digital ecosystem. Constantly promote cybersecurity awareness – that’s what we’re focused on internally and with every customer – and we’re product of what we’re accomplishing with them and seeing them and we are very proud of what we have accomplished.”
Rapid.Space Founder and CEO Jean Paul Smets
Jean Paul is an entrepreneur, with 20 year experience and success in enterprise open source software for B2B markets. As Founder and CEO At Rapid.Space, he leads product and business development . Before Rapid.Space, Jean Paul founded Nexedi S.A the largest FLOSS publisher in the EU (4 M€ income). He founded VIFIB which invented edge computing in 2009 and contributed its technology to Rapid.Space. He holds a PhD in computer science, graduated from ENS Ulm and joined “corps des mines”.
Advice from Jean Paul Smets, Founder and CEO at Rapid.Space
“If you use a cloud service, make sure your cloud provider does not have access to your passwords or credentials (most have access and password leaks happen in average every year, as we all experienced). If you use containers, make sure you understand that they do not provide strong isolation (containers from other users on the same host may be able to access your sensitive data through security escalation, such as the one which happened to Azure in 9/2021)”
ThycoticCentrify CEO Art Gilliland
Art Gilliland is CEO at Centrify and brings proven success in the global enterprise software industry-leading large organizations in product development, enterprise infrastructure, cybersecurity, go-to-market strategy, and SaaS operations. He most recently was SVP/GM of the Symantec Enterprise Division of Broadcom, reporting to the CEO, where he led the integration and business operations post-acquisition. Before Symantec, Art held executive positions at Skyport Systems, HP, Symantec, and IMlogic.
Advice from ThycoticCentrify CEO Art Gilliland:
“As organizations execute on their digital transformations to adopt cloud and SaaS infrastructure it will become more essential to adopt tighter control over who has access to what. Investments in tighter controls over privileged access by using multi-factor authentication, centralizing identities, and enforcing least privilege can go a long way to securing modern infrastructure. This investment can not only make the user experience more seamless for those who need and should have access, but can also simultaneously harden defenses to reduce risk of becoming the next hack or ransomware victim.” — Art Gilliland, CEO, ThycoticCentrify
Bottom Line: Professional services (PS) organizations need to close the gaps in their CPQ selling strategies to win more deals, capture more revenue and protect margins from ongoing price pressure.
Why Services CPQ Is Too Slow Today
When PS organizations compete in sales cycles, the first competitor to have a complete quote with accurate pricing, schedules, and an engagement plan will often win. However, getting a complete quote out fast is a major challenge for most PS organizations today. Many PS organizations manually create their quotes by taking into account a broad base of factors that include the following: talent profiles of employees and the market value of their skills; utilization rates; direct and indirect engagement costs; typical gross margins by type of engagement; and, competitive pricing. The average PS organization takes six weeks to deliver a quote or proposal. John Ragsdale’s excellent recent article Automating Services Quote-to-Cash: Emergence of CPQ for Services provides useful insights into what needs to change for PS quoting and selling to increase its velocity.
Getting Services CPQ Right Is Hard
Gaps that drain revenue and margin grow wider when PS organizations attempt to use product-centric CPQ platforms to sell services. Too often, PS organizations attempt to wedge their quoting, pricing, and revenue management into a product-based CPQ system – and get mediocre results at best. Earlier in my career, I led a product management team that defined, created, and launched a quoting system for professional services inside a large IT organization. The most valuable lessons learned from that experience include the following:
PS bundles only work if they have simple, solid direct cost structures. Adding a synthetic SKU that represents a PS bundle only works for the most simple, automated PS engagements. Think of those PS engagements with long-standing direct cost structures that are simple, clear and easy to implement. Attempting to group PS bundles can easily lead to quoting mistakes that drain margin when a product-centric CPQ system is used for PS.
The greater the differences in PS revenue management, the more the need for a new CPQ platform. Many PS organizations are making a mistake by attempting to make product-centric CPQ platforms work for their unique costing, pricing, and selling needs. My team and I learned that the more a PS revenue model is unique and one-of-a-kind, the more it requires a unique CPQ platform.
Getting product-based CPQ rules and constraint logic right is hard in PS. Our teams’ biggest challenge in recycling IT’s CPQ app for PS was how difficult it was to get the rules-based engine to work for the wide variety of variables in a common service engagement. Rules created for transaction velocity needed to be reworked for greater variety. PS engagements didn’t follow a common logic structure like a product, making the constraint logic code only somewhat usable.
Only launch after CRM and Revenue Management integration is complete. Our team was handed a project that had languished in IT for nearly a year because PS selling teams wouldn’t use it. The problem was that the quoting module ran batch updates to a series of databases to get customer records and fetch the latest price tables off of a mainframe. In addition, CPQ wasn’t connected in real-time to CRM or Revenue Management.
Closing Long-Standing Services CPQ Gaps
The more a Services CPQ app can close the gaps between CRM, PSA, Revenue Management, and CPQ apps and their workflows, the more effective it will be stopping margin and revenue leakage. Having APIs that share data in real-time between CRM, PSA, and Revenue Management within each quote creation session has the potential to save thousands of hours a year. FinancialForce’s recently announced Services CPQ shows how a platform-based integration strategy works. The following graphic shows how revenue potential increases as a Services CPQ’s systems become more integrated.
FinancialForce’s approach to taking on the challenge of providing an enterprise-grade Services CPQ is noteworthy for several reasons, including the following:
Real-time visibility and control of Services CPQ Effectiveness. Having Services CPQ, PSA and Revenue Management on the same Salesforce platform provides the visibility and control PS sales managers need to track quoting effectiveness by program, geography, customer segment, and rep. The more real-time the data integration across these systems the greater the potential for revenue growth in existing accounts and winning new ones.
Changing professional services quotes in real-time without impacting sales cycles is possible. Due to the integrated design of Services CPQ, one change made anywhere on a quote will replicate through the entire system and change all related factors immediately.
Getting in control of professional services engagement dates and utilization rates by associates helps reduce time-to-market and assures better time-to-customer performance. Keeping track of the myriad of factors that influence a services quote using a manually-based process is too slow for how quickly engagements are decided. Instead, having a single, unified data model that can track effectiveness and provide updates on how they impact engagement project plans is needed to excel at selling with Services CPQ. Adopting an agile CPQ strategy that relies on an integration thread to unify all systems is the secret to scaling and selling more with an agile approach to services CPQ.
Pricing needs to be one of the core strengths in an integrated Services CPQ platform. Realizing how a customers’ requested changes to a professional services engagement will impact costs and margins gives PS teams with an integrated system a formidable pricing advantage. FinancialForce’s approach to solving the Services CPQ challenge shows the potential to take on this challenge and provide its PS customers with the insights they need to upsell engagements – and not lose margin doing it.
A must-have for any Services CPQ platform is support for channel partner collaboration and team quoting. For any Services CPQ to scale up and deliver its full potential value, there needs to be support for customizing partner selling experiences while providing for team selling and quoting. FinancialForce solves this by relying on the Salesforce platform. By closing the gaps between the systems Services CPQ relies on, the channel selling teams and partners gain greater flexibility in defining customized products.
Conclusion
Services CPQ needs to scale out on a platform to achieve its full potential by providing the analytical insights to track engagement lifecycles and customer lifetime value by engagement. FinancialForce has proven they can do this in their Spring 2021 release. Taking on the most challenging aspects of a Services CPQ architecture starts by providing insights and guidance on how best to optimize the mix of associates and their utilization and billing rates, locations of each engagement, margin threshold levels, and the expected duration of each engagement. Additionally, the world’s leading professional services organizations could use an automated Services CPQ solution as many of them don’t rely on enough data, letting revenue leakage happen without knowing it.
59% of all large enterprises are deploying data science (DS) and machine learning (ML) today.
Nearly 50% of all organizations have up to 25 or more ML models in use today.
29% of enterprises are refreshing their data science and machine learning models every day.
The higher the data literacy an enterprise can achieve before launching Data Science & Machine Learning initiatives, the higher the probability of success.
These and many other insights defining the state of the data science and machine learning market in 2021 are from Dresner Advisory Services’2021 Data Science and Machine Learning Market Study. The 7th annual report is noteworthy for its depth of analysis and insight into how data science and machine learning adoption is growing stronger in enterprises. In addition, the study explains which factors drive adoption and determine the key success factors that matter the most when deploying data science and machine learning techniques. The methodology uses crowdsourcing techniques to recruit respondents from over 6,000 organizations and vendors’ customer communities. As a result, 52% of respondents are from North America and 34% from EMEA, with the balance from Asia-Pacific and Latin America.
“The perceived importance of data science and machine learning correlates with organizational success with BI, with users that self-report as completely successful with BI almost twice as likely to rate data science as critical,” said Jim Ericson, vice president, and research director at Dresner Advisory. “The perceived level of data literacy also correlates directly and positively with the current or likely future use of data science and machine learning in 2021.”
Key insights from the study include the following:
59% of large enterprises are deploying data science and machine learning in production today. Enterprises with 10K employees or more lead all others in adopting and using DS and ML techniques, most often in R&D and Business Intelligence Competency Center (BICC)-related work. Large-scale enterprises often rely on DS and ML to identify how internal processes and workflows can be streamlined and made more cost-efficient. For example, the CEO of a manufacturing company explained on a recent conference call that DS and ML pilots bring much-needed visibility and control across multiple plants and help troubleshoot inventory management and supply chain allocation problems.
The importance of data science and ML to enterprises has doubled in eight years, jumping from 25% in 2014 to 70% in 2021. The Dresner study notes that a record level of enterprises sees data science and ML as critically important to their business in 2021. Furthermore, 90% of enterprises consider these technologies essential to their operations, rating them critically important or very important. Successful projects in Business Intelligence Competency Centers (BICC) and R&D helped data science and ML gain broad adoption across all organizations. Larger-scale enterprises with over 10K employees are successfully scaling data science and ML to improve visibility, control, and profitability in organizations today.
Enterprises dominate the recruiting and retention of data science and machine learning talent. Large-scale enterprises with over 10K employees are the most likely to have BI experts and data scientists/statisticians on staff. In addition, large-scale enterprises lead hiring and retention in seven of the nine roles included in the survey. It’s understandable how the Business Intelligence (BI) expertise of professionals in these roles is helping remove the roadblocks to getting more business value from data science and machine learning. Enterprises are learning how to scale data science and ML models to take on problems that were too complex to solve with analytics or BI alone.
80% of DS and ML respondents most want model lifecycle management, model performance monitoring, model version control, and model lineage and history at a minimum. Keeping track of the state of each model, including version control, is a challenge for nearly all organizations adopting ML today. Enterprises reach ML scale when they can manage ML models across their lifecycles using an automated system. The next four most popular features of model rollback, searchable model repository, collaborative, model co-creation tools, and model registration and certification are consistent with the feedback from Data Science teams on what they need most in an ML platform.
Financial Services prioritize model lifecycle management and model performance monitoring to achieve greater scale from the tens of thousands of models they’re using today. Consistent with other research that tracks ML adoption by industry, the Dresner study found that Financial Services leads all other industries in their need for the two most valuable features of ML platforms, model lifecycle management and model performance monitoring. Retail and Wholesale are reinventing their business models in real-time to become more virtual while also providing greater real-time visibility across supply chains. ML models in these two industries need automated model version control, model lineage and history, model rollback, collaborative, model co-creation tools, and model registration and certification. In addition, retailers and Wholesalers are doubling down on data science and machine learning to support new digital businesses, improve supply chain performance and increase productivity.
Enterprises need support for their expanding range of regression models, text analytics functions, and ensemble learning. Over the last seven years, text analytics functions and sentiment analysis’ popularity has continually grown. Martech vendors and the marketing technologists driving the market are increasing sentiment analysis’ practicality and importance. Recommendation engines and geospatial analysis are also experiencing greater adoption due to martech changing the nature of customer- and market-driven analysis and predictive modeling.
R, TensorFlow, and PyTorch are considered the three most critical open-source statistical and machine learning frameworks in 2021. Nearly 70% of respondents consider R important to getting work done in data science and ML. The R language has established itself as an industry standard and is well-respected across DevOps, and IT teams in financial services, professional services, consulting, process, and discrete manufacturing. Tensorflow and Pytorch are considered important by the majority of organizations Dresner’s research team interviewed. They’re also among the most in-demand ML frameworks today, with new applicants having experience in all three being recruited actively today.
Data literacy predicts DS and ML program success rates. 64% of organizations say they have extremely high literacy rates, implying that DS and ML have reached mainstream adoption thanks partly to BI literacy rates in the past. Enterprises that prioritize data literacy by providing training, certification, and ongoing education increase success odds with ML. A bonus is that employees will have a chance to learn marketable skills they can use in their current and future positions. Investing in training to improve data literacy is a win/win.
On-database analytics and in-memory analytics (both 91%), and multi-tenant cloud services (88%) are the three most popular technologies enterprises rely on for greater scalability. Dresner’s research team observes that the scalability of data science and machine learning often involves multiple, different requirements to address high data volumes, large numbers of users, data variety while supporting analytic throughput. Apache Spark support continues to grow in enterprises and is the fourth-most relied-on industry support for ML scalability.
Apple, Alphabet, Amazon, Microsoft, and Tesla are considered the five most innovative companies, according to BCG’s analysis of the 50 most innovative companies of 2021.
Abbott Labs, AstraZeneca, Comcast, Mitsubishi, and Moderna join the top 50 most innovative companies for the first time this year.
The fastest movers include Toyota, who jumped from 41st to 21st; Salesforce, who jumped from 35th to 22nd; and Coca-Cola, who jumped from 48th to 28th.
90% of companies that outperform on innovation outcomes demonstrate clear C-suite ownership of the innovation agenda.
These and many other insights are from the Boston Consulting Group’s (BCG) 15th annual report defining the world’s 50 most innovative companies in 2021. BCG surveyed 1,500 global innovation executives and found a 10% point increase, to 75%, in executives reporting that innovation is a top-three priority at their companies today. That’s the most significant year-over-year increase in the 15 global innovation surveys BCG has conducted since 2005. BCG’s Most Innovative Companies 2021: Overcoming the Innovation Readiness Gap is available for download free here (28 pp., PDF). This years’ report methodology focuses on identifying the factors causing a large innovation readiness gap between the world’s most innovative companies and their peers across industries. Please see page 23 of the study for the methodology.
Key insights from BCGs’ most innovative companies of 2020 include the following:
Creating a new COVID-19 vaccine in less than a year, inventing test kits in weeks to protect public health, and redefining online shopping and safe home delivery reflect the versatility of the world’s most innovative companies in 2021. Pzifer, Moderna, and Merck & Company’s innate ability to innovate gave everyone a decade of their lives back. Delivering a vaccine in a year when the initial projection was a decade reflects the innovative efficiency of these companies. 2021 is the first year Abbott Labs, who invented and scaled the production of COVID-19 test kits, is included in the 50 most innovative companies worldwide. Amazon and Walmart’s logistics and e-commerce expertise helped ensure safe online shopping and fast home delivery was available to millions of people under stay-at-home orders.
Five factors most differentiate the most and least innovative companies. The basis of BCG’s methodology to identify the 50 most innovative companies in 2021 centers on their innovation-to-impact (i2i) framework. The framework is designed to help companies measure the readiness of their innovation programs to operate at a consistently high level of efficiency and effectiveness. The BCG i2i scoring system identified five factors that most differentiate innovative company leaders and laggards. The five factors that best indicate how innovative a company has the potential to be are shown in the following graphic:
Lack of collaboration between sales, marketing & R&D is the major obstacle to innovation. 31% of all companies surveyed see poor collaboration between marketing and R&D as the most significant obstacle to improving the return on their innovation investments. According to BCG, the collaboration between marketing, sales, and R&D is the most challenging in the Pharmaceutical industry, where 42% of respondents say it’s the biggest hurdle to achieving more significant returns on innovation.
Digital transformation of the core business is now a top priority for 75% of CEOs, and 65% of firms are doubling down on their plans for transformation with renewed urgency. BCG identified six success factors that together—and only together—flip the odds of digital transformation success from 30% to 80%. Those six success factors are close integration of digital strategy with the business strategy, commitment from the CEO through middle management, a talent core of digital superstars, business-led and flexible technology and data platforms, agile governance, and effective monitoring of progress toward defined outcomes.
Conclusion
Companies that know how to collaborate quickly between customer and R&D teams have an inside edge on being innovation leaders. The world’s most innovative companies also have senior management teams committed to the long-term success of nascent, unproven programs. There’s greater tolerance for risk, more of a focus on customers first and innovating around their needs, and an intuitive sense of how to close innovation gaps that hold other companies back.
There are a record number of 9,977 machine learning startups and companies in Crunchbase today, an 8.2% increase over the 9,216 startups listed in 2020 and a 14.6% increase over the 8,705 listed in 2019.
Artificial Intelligence (A.I.) and machine learning (ML)-related companies received a record $27.6 billion in funding in 2020, according to Crunchbase.
Of those A.I. and machine learning startups receiving funding since January 1, 2020, 62% are seed rounds, 31% early-stage venture rounds and 6.7% late-stage venture capital-funded rounds.
A.I. and machine learning startups’ median funding round was $4.4 million and the average was $29.8 million in 2020, according to Crunchbase.
Throughout 2020, venture capital firms continued expanding into new global markets, with London, New York, Tel Aviv, Toronto, Boston, Seattle and Singapore startups receiving increased funding. Out of the 79 most popular A.I. & ML startup locations, 15 are in the San Francisco Bay Area, making that region home to 19% of startups who received funding in the last year. Israel’s Tel Aviv region has 37 startups who received venture funding over the last year, including those launched in Herzliya, a region of the city known for its robust startup and entrepreneurial culture.
The following graphic compares the top 10 most popular locations for A.I. & ML startups globally based on Crunchbase data as of today:
Top 20 Machine Learning Startups To Watch In 2021
Augury – Augury combines real-time monitoring data from production machinery with AI and machine learning algorithms to determine machine health, asset performance management (APM) and predictive maintenance (PdM) to provide manufacturing companies with new insights into their operations. The digital machine health technology that the company offers can listen to the machine, analyze the data and catch any malfunctions before they arise. This enables customers to adjust their maintenance and manufacturing processes based on actual machine conditions. The platform is in use with HVAC, industrial factories and commercial facilities.
Alation – Alation is credited with pioneering the data catalog market and is well-respected in the financial services community for its use of A.I. to interpret and present data for analysis. Alation has also set a quick pace to evolving its platform to include data search & discovery, data governance, data stewardship, analytics and digital transformation. With its Behavioral Analysis Engine, inbuilt collaboration capabilities and open interfaces, Alation combines machine learning with human insight to successfully tackle data and metadata management challenges. More than 200 enterprises are using Alation’s platform today, including AbbVie, American Family Insurance, Cisco, Exelon, Finnair, Munich Re, New Balance, Pfizer, Scandinavian Airlines and U.S. Foods. Headquartered in Silicon Valley, Alation is backed by leading venture capitalists including Costanoa, Data Collective, Icon, Sapphire and Salesforce Ventures.
Algorithmia – Algorithmia’s expertise is in machine learning operations (MLOps) and helping customers deliver ML models to production with enterprise-grade security and governance. Algorithmia automates ML deployment, provides tooling flexibility, enables collaboration between operations and development and leverages existing SDLC and CI/CD practices. Over 110,000 engineers and data scientists have used Algorithmia’s platform to date, including the United Nations, government intelligence agencies and Fortune 500 companies.
Avora – Avora is noteworthy for its augmented analytics platform, making in-depth data analysis intuitively as easy as performing web searches. The company’s unique technology hides complexity, empowering non-technical users to run and share their reports easily. By eliminating the limitations of existing analytics, reducing data preparation and discovery time by 50-80% and accelerating time to insight, Avora uses ML to streamline business decision-making. Headquartered in London with offices in New York and Romania, Avora helps accelerate decision making and productivity for customers across various industries and markets, including Retail, Financial Services, Advertising, Supply Chain and Media and Entertainment.
Boast.ai – Focused on helping companies in the U.S. and Canada recover their R&D costs from respective federal governments, Boast.ai enables engineers and accountants to gain tax credits using AI-based tools. Some of the tax programs Boast.ai works with include US R&D Tax Credits, Scientific Research and Experimental Development (SR&ED) and Interactive Digital Media Tax Credits (IDMTC). The startup has offices in San Francisco, Vancouver and Calgary.
ClosedLoop.ai – An Austin, Texas-based startup, ClosedLoop.ai has created one of the healthcare industry’s first data science platforms that streamline patient experiences while improving healthcare providers’ profitability. Their machine learning automation platform and a catalog of pre-built predictive and prescriptive models can be customized and extended based on a healthcare provider’s unique population or client base needs. Examples of their technology applications include predicting admissions/readmissions, predicting total utilization & total risk, reducing out-of-network utilization, avoiding appointment no-shows, predicting chronic disease onset or progression and improving clinical documentation and reimbursement. The Harvard Business School, through its Kraft Precision Medicine Accelerator, recently named ClosedLoop.ai as one of the fastest accelerating companies in its Real World Data Analytics Landscapes report.
Databand – A Tel Aviv-based startup that provides a software platform for agile machine learning development, Databand was founded in 2018 by Evgeny Shulman, Joshua Benamram and Victor Shafran. Data engineering teams are responsible for managing a wide suite of powerful tools but lack the utilities they need to ensure their ops are running properly. Databand fills this gap with a solution that enables teams to gain a global view of their data flows, make sure pipelines complete successfully and monitor resource consumption and costs. Databand fits natively in the modern data stack, plugging seamlessly into tools like Apache Airflow, Spark, Kubernetes and various ML offerings from the major cloud providers.
DataVisor – DataVisor’s approach to using AI for increasing fraud detection accuracy on a platform level is noteworthy. Using proprietary unsupervised machine learning algorithms, DataVisor enables organizations to detect and act on fast-evolving fraud patterns and prevent future attacks before they happen. Combining advanced analytics and an intelligence network of more than 4.2B global user accounts, DataVisor protects against financial and reputational damage across various industries, including financial services, marketplaces, e-commerce and social platforms. They’re one of the more fascinating cybersecurity startups using AI today.
Exceed.ai – What makes Exceed.ai noteworthy is how their AI-powered sales assistant platform automatically communicates the lead’s context and enables sales and marketing teams to scale their lead engagement and qualification efforts accordingly. Exceed.ai follows up with every lead and qualifies them quickly through two-way, automated conversations with prospects using natural language over chat and email. Sales reps are freed from performing error-prone and repetitive tasks, allowing them to focus on revenue-generating activities such as phone calls and demos with potential customers.
Indico – Indico is a Boston-based startup specializing in solving the formidable challenge of how dependent businesses are on unstructured content yet lack the frameworks, systems and tools to manage it effectively. Indico provides an enterprise-ready A.I. platform that organizes unstructured content while streamlining and automating back-office tasks. Indico is noteworthy given its track record of helping organizations automate manual, labor-intensive, document-based workflows. Its breakthrough in solving these challenges is an approach known as transfer learning, which allows users to train machine learning models with orders of magnitude fewer data than required by traditional rule-based techniques. Indico enables enterprises to deploy A.I. to unstructured content challenges more effectively while eliminating many common barriers to A.I. & ML adoption.
LeadGenius – LeadGenius is noteworthy for its use of AI to provide personalized and actionable B2B lead information that helps its clients attain their global revenue growth goals. LeadGenius’s worldwide team of researchers uses proprietary technologies, including AI and ML-based techniques, to deliver customized lead generation, lead enrichment and data hygiene services in the format, methods and frequency defined by the customer. Their mission is to enable B2B sales and marketing organizations to connect with their prospects via unique and personalized data sets.
Netra – Netra is a Boston-based startup that began as part of MIT CSAIL research and has multiple issued and pending patents on its technology today. Netra is noteworthy for how advanced its video imagery scanning and text metadata interpretation are, ensuring safety and contextual awareness. Netra’s patented A.I. technology analyzes videos in real-time for contextual references to unsafe content, including deepfakes and potential cybersecurity threats.
Particle – Particle is an end-to-end IoT platform that combines software including A.I., hardware and connectivity to provide a wide range of organizations, from startups to enterprises, with the framework they need to launch IoT systems and networks successfully. Particle customers include Jacuzzi, Continental Tires, Watsco, Shifted Energy, Anderson EV, Opti and others. Particle is venture-backed and has offices in San Francisco, Shenzhen, Las Vegas, Minneapolis and Boston. Particle’s developer community includes over 200,000 developers and engineers in more than 170 countries today.
RideVision – RideVision was founded in 2018 by motorcycle enthusiasts Uri Lavi and Lior Cohen. The company is revolutionizing the motorcycle-safety industry by harnessing the strength of artificial intelligence and image-recognition technology, ultimately providing riders with a much broader awareness of their surroundings, preventing collisions and enabling bikers to ride with full confidence that they are safe. RideVision’s latest round was $7 million in November of last year, bringing their total funding to $10 million in addition to a partnership with Continental AG.
Savvie – Savvie is an Oslo-based startup specializing in translating large volumes of data into concrete actions that bakery and café owners can utilize to improve their bottom line every day. In doing so, we help food businesses make the right decisions to optimize their operations and increase profitability while reducing waste at its source. What’s noteworthy about this startup is how adept they are at fine-tuning ML algorithms to provide their clients with customized recommendations and real-time insights about their food and catering businesses. Their ML-driven insights are especially valuable given how bakery and café owners are pivoting their business models in response to the pandemic.
SECURITI.ai – One of the most innovative startups in cybersecurity, combining AI and ML to secure sensitive data in multi-cloud and mixed platform environments, SECURITI.ai is a machine learning company to watch in 2021, especially if you are interested in cybersecurity. Their AI-powered platform and systems enable organizations to discover potential breach risk areas across multi-cloud, SaaS and on-premise environments, protect it and automate all private systems, networks and infrastructure functions.
SkyHive – SkyHive is an artificial intelligence-based SaaS platform that aims to reskill enterprise workforces and communities. It develops and commercializes a methodology, Quantum Labor Analysis, to deliver real-time, skill-level insights into internal workforces and external labor markets, identify future and emerging skills and facilitate individual-and company-level reskilling. SkyHive is industry-agnostic and supporting enterprise and government customers globally with a mission to reduce unemployment and underemployment. Sean Hinton founded the technology company in Vancouver, British Columbia, in 2017.
Stravito – Stravito is an A.I. startup that’s combining machine learning, Natural Language Processing (NLP) and Search to help organizations find and get more value out of the many market research reports, competitive, industry, market share, financial analysis and market projection analyses they have by making them searchable. Thor Olof Philogène and Sarah Lee founded the company in 2017, who identified an opportunity to help companies be more productive, getting greater value from their market research investments. Thor Olof Philogène and Andreas Lee were co-founders of NORM, a research agency where both worked for 15 years serving multinational brands, eventually selling the company to IPSOS. While at NORM, Anders and Andreas were receiving repeated calls from global clients that had bought research from them but could not find it internally and ended up calling them asking for a copy. Today the startup has Carlsberg, Comcast, Colruyt Group, Danone, Electrolux, Pepsi Lipton and others. Stravito has offices in Stockholm (H.Q.), Malmö and Amsterdam.
Verta.ai – Verta is a startup dedicated to solving the complex problems of managing machine learning model versions and providing a platform to launch models into production. Founded by Dr. Manasi Vartak, Ph.D., a graduate of MIT, who led a team of graduate and undergraduate students at MIT CSAIL to build ModelDB, Verta is based on their work define the first open-source system for managing machine learning models. Her dissertation, Infrastructure for model management and model diagnosis, proposes ModelDB, a system to track ML-based workflows’ provenance and performance. In August of this year, Verta received a $10 million Series A round led by Intel Capital and General Catalyst, who also led its $1.7 million seed round. For additional details on Verta.ai, please see How Startup Verta Helps Enterprises Get Machine Learning Right. The Verta MLOps platform launch webinar provides a comprehensive overview of the platform and how it’s been designed to streamline machine learning models into production:
V7 – V7 allows vision-based A.I. systems to learn continuously from training data with minimal human supervision. The London-based startup emerged out of stealth in August 2018 to reveal V7 Darwin, an image labeling platform to create training data for computer vision projects with little or no human involvement necessary. V7 specializes in healthcare, life sciences, manufacturing, autonomous driving, agri-tech, sporting clients like Merck, GE Healthcare and Toyota. V7 Darwin launched at CVPR 2019 in Long Beach, CA. Within its first year, it has semi-automatically annotated over 1,000 image and video segmentation datasets. V7 Neurons is a series of pre-trained image recognition applications for industry use. The following video explains how V7 Darwin works:
Cybersecurity, privacy and security startups have raised $1.9 billion in three months this year, on pace to reach $7.6 billion or more in 2021, over four times more than was raised throughout 2010 ($1.7 billion), according to a Crunchbase Pro query today.
22,156 startups who either compete in or rely on cybersecurity, security and privacy technologies and solutions as a core part of their business models today, 122 have pre-seed or seed funding in the last twelve months based on a Crunchbase Pro query.
From network and data security to I.T. governance, risk measurement, and policy compliance, cybersecurity is a growing industry estimated to be worth over $300B by 2025, according to C.B. Insight’s Emerging Trends Cybersecurity Report downloadable here.
Today, 680 cybersecurity, privacy, and security startups have received $6.8 billion in funding over the last twelve months, with $4 million being the median funding round and $12.6 million the average funding round for a startup. The number of startups receiving funding this year, funding amounts and the methodology to find the top 20 cybersecurity startups are all based on Crunchbase Pro analysis done today.
New startups and established vendors are attracting record levels of investment as all organizations look to thwart increasingly complex, costly and unpredictable cyberattacks. There is an arms race going on between cyber attackers using A.I. and machine learning and the many startups and existing vendors whose goal is to contain them. CBInsights and PwC recently published their latest quarterly joint study of the venture capital landscape, MoneyTree™ Report, Q4, 2020. The study finds that monitoring and security deals were the third fastest-growing vertical in 2020, with Q4 being exceptional for all verticals, as the heat map below shows:
The 20 Best Cybersecurity Startups To Watch In 2021
Based on a methodology that equally weighs a startup’s ability to attract new customers, current and projected revenue growth, ability to adapt their solutions to growing industries and position in their chosen markets, the following are the top 20 cybersecurity startups to watch in 2021:
Axis Security – Axis Security’s Application Access Cloud™ is a purpose-built cloud-based solution that makes application access across networks scalable and secure. Built on zero-trust, Application Access Cloud offers a new agentless model that connects users online to any application, private or public, without touching the network or the apps themselves. Axis Security is a privately held company backed by Canaan Partners, Ten Eleven Ventures, and Cyberstarts. Axis is headquartered in San Mateo, California, with research and development in Tel Aviv, Israel.
Bitglass – What makes Bitglass unique and worth watching is how they are evolving their Total Cloud Security Platform to combine cloud access security brokerage, on-device secure web gateways, and zero-trust network access to secure endpoints across all devices. Its Polyscale Architecture is delivering uptimes of 99.99% in customer deployments. Bitglass’s 2020 Insider Threat Report has several interesting insights based on their recent interviews with a leading cybersecurity community. One interesting takeaway is 61% of those surveyed experienced an insider attack in the last 12 months (22% reported at least six).
Cado Security – Cado Security’s cloud-native forensics and response platform helps organizations respond to security incidents in real-time, averting potential breaches and security incidents. The Cado Response platform is built on analytics components that perform thorough forensic analyses of compromised systems. Cado’s platform, Cado Response, is an agentless, cloud-native forensics solution that allows security professionals to quickly and comprehensively understand an incident’s impact across all environments, including cloud and containers as well as on-premise systems. “Finding the root cause of security incidents in cloud or container environments is incredibly difficult. Traditional tools don’t support these new environments, and there is a shortage of people who know both forensics and cloud security,” said CEO James Campbell, formerly Director, Cyber Threat Detection and Response at PricewaterhouseCoopers. “Our Cado Response platform completely changes how security professionals can respond to incidents in the cloud.”
Confluera – Originally mentioned as one of the 20 Best Cybersecurity Startups To Watch In 2020, Confluera’s sustained innovation pace in the middle of a pandemic deserves special mention. They are one of the most resilient startups to watch in 2021.Confluera is a cybersecurity startup helping organizations find sophisticated security attacks going on inside of corporate infrastructures. The startup delivers autonomous infrastructure-wide cyber kill chain tracking and response by leveraging the ‘Continuous Attack Graph’ to stop and remediate cyber threats in real-time deterministically. Confluera’s platform is designed to detect and prevent attackers from navigating infrastructure. Confluera technology combines machine comprehended threat detection with accurately tracked activity trails to stop cyberattacks in real-time, allowing companies to simplify security operations radically. It frees up human security personnel to focus on more important work instead of spending hours trying to join the dots between the thousands of alerts they receive daily, many of which are false positives. The following is a video that explains how Confluera XDR for Cloud Infrastructure works:
DataFleets – DataFleets is a privacy-preserving data engine that unifies distributed data for rapid access, agile analytics, and automated compliance. The platform provides data scientists and developers with a “data fleet” that allows them to create analytics, ML models, and applications on susceptible data sets without direct access to the data. Each data fleet has easy-to-use APIs, and under-the-hood, they ensure data protection using advances in federated computation, transfer learning, encryption, and differential privacy. DataFleets helps organizations overcome data privacy and innovation struggle by maintaining data protection standards for compliance while accelerating data science initiatives.
DefenseStorm – DefenseStorm’s unique approach to providing cybersecurity and cyber-compliance for the banking industry make them one of the top startups to watch in 2021. Their DefenseStorm GRID is the only co-managed, cloud-based and compliance-automated solution of its kind for the banking industry. It monitors everything on a bank’s network. It matches it to defined policies for real-time, complete and proactive cyber exposure readiness, keeping security teams and executives updated on bank networks’ real-time security status. The company’s Threat Ready Active Compliance (TRAC) Team augments its bank customers’ internal teams to protect business continuity and skills availability while ensuring cost-effective coverage and management.
Enso Security – Enso is an application security posture management (ASPM) platform startup known for the depth of its insights and expertise in cybersecurity. With Enso, software security groups can scale and gain control over application security programs to protect applications systematically. The Enso ASPM platform discovers application inventory, ownership, and risk to help security teams quickly build and enforce security policies and transform AppSec into an automated, systematic discipline.
Ethyca – Ethyca is an infrastructure platform that provides developers and product teams with the ability to ensure consumer data privacy throughout applications and services design. It also provides your product, engineering, and privacy teams with unmatched ease of use and functionality to better care about your user’s data. The company helps companies discover sensitive data and then provides a mechanism for customers to delete, see, or edit their data from the system. Ethyca’s mission is to increase trust in data-driven business by building automated data privacy infrastructure. Ethyca’s founder and CEO Cillian Kiernan is a fascinating person to speak with on the topics of privacy, security, GDPR, and CCPA compliance. He continues to set a quick pace of innovation in Ethyca, making this startup one of the most interesting in data privacy today. Here’s an interview he did earlier this year with France 24 English:
Havoc Shield – Havoc Shield reduces the burden on small and medium businesses (SMBs) by giving them access to advanced security technology that protects against data breaches, phishing, dark web activity, and other threats. The Havoc Shield platform offers comprehensive security and compliance features that meet the standards of Fortune 100 companies, making it easier for businesses working to win deals with those companies. “For a long time, cybersecurity technology has been virtually inaccessible to small businesses, who largely can’t afford those resources,” said Brian Fritton, CEO and co-founder of Havoc Shield. “We created Havoc Shield because we believe in democratizing cybersecurity for the little guy. Small businesses deserve the ability to protect what they’ve built, just as much as larger companies that have dedicated cybersecurity staff.” Since the end of Q2 2020, Havoc Shield has quadrupled its client list. In the coming months, the company aims to grow its team to help more small businesses protect themselves from threats and achieve customer trust.
Illumio – Widely considered the leader in micro-segmentation that prevents the spread of breaches inside data centers and cloud environments, Illumio is one of the most interesting cybersecurity startups to watch in 2021. Enterprises such as Morgan Stanley, BNP Paribas, Salesforce, and Oracle NetSuite use Illumio to reduce cyber risk and achieve regulatory compliance. The Illumio Adaptive Security Platform® uniquely protects critical information with real-time application dependency and vulnerability mapping coupled with micro-segmentation that works across any data center, public cloud, or hybrid cloud deployment on bare-metal, virtual machines, and containers. The following video explains why Illumio Core is a better approach to segmentation.
Immuta – Immuta was founded in 2015 based on a mission within the U.S. Intelligence Community to build a platform that accelerates self-service access to and control sensitive data. The Immuta Automated Data Governance platform creates trust across data engineering, security, legal, compliance, and business teams to ensure timely access to critical data with minimal risk while adhering to global data privacy regulations GDPR, CCPA, and HIPAA. Immuta’s automated, scalable, no-code approach makes it easy for users to access the data they need when they need it while protecting sensitive information and ensuring customer privacy. Selected by Fast Company as one of the World’s 50 Most Innovative Companies, Immuta is headquartered in Boston, MA, with offices in College Park, MD, and Columbus, OH.
Isovalent – Isovalent makes software that helps enterprises connect, monitor and secure mission-critical workloads in modern, cloud-native ways. Its flagship technology, Cilium, is the choice of leading global organizations, including Adobe, Capital One, Datadog, GitLab, and many more. Isovalent is headquartered in Mountain View, CA, and is backed by Andreessen Horowitz, Google and Cisco Investments. Earlier this month, Isovalent announced that it had raised $29 million in Series A funding, led by Andreessen Horowitz and Google with participation from Cisco Investments. Google recently selected Cilium as the next-generation dataplane for its GKE offering calling Cilium “the most mature eBPF implementation for Kubernetes out there” in its “New GKE Dataplane V2 increases security and visibility for containers” blog: https://cloud.google.com/blog/products/containers-kubernetes/bringing-ebpf-and-cilium-to-google-kubernetes-engine.
JupiterOne – JupiterOne, Inc. reduces cloud security cost and complexity, replacing guesswork with granular data about cyber assets and configurations. The company’s software helps security operations teams shorten the path to security and compliance and improve their overall posture through continuous data aggregation and relationship modeling across all assets. JupiterOne customers include Reddit, Databricks, HashiCorp, Addepar, Auth0, LifeOmic, and OhMD. Earlier this year, JupiterOne received $19 million in venture funding. The Series A round was led by Bain Capital Ventures, with additional investment from Rain Capital, LifeOmic, and individual investors. “JupiterOne has developed a compelling product that integrates quickly, has applicability across enterprise segments, and is highly reviewed by current customers,” said Enrique Salem, partner at Bain Capital Ventures and former CEO at Symantec. Salem now joins the JupiterOne board. “We see a multibillion-dollar market opportunity for this technology across mid-market and enterprise customers. Asset management is the first step in building a successful security program, and it’s currently a tedious, imperfect process that’s well-suited for automation.”
Lightspin – Lightspin is a pioneer in contextual cloud security protecting native, Kubernetes, and microservices from known and unknown risks and has recently announced a $4 million seed funding round on November 24th. They will use the proceeds of the round to finance continued R&D on how to secure cloud infrastructures. The financing round was led by Ibex Investors LLC, the firm’s first global investment from its new $100 million early-stage fund, and also included participation from private angel investors. Lightspin’s technology uses graph-based tools and algorithms to provide rapid, in-depth visualizations of cloud stacks, analyze potential attack paths and detect the root causes, all of which are the most critical vulnerabilities that attackers can exploit.
Orca Security – Orca Security is noteworthy for its innovative approach to providing instant-on, workload-deep security for AWS, Azure, and GCP without the gaps in agents’ coverage and operational costs.Orca integrates cloud platforms as an interconnected web of assets, prioritizing risk based on environmental context. Delivered as SaaS, Orca Security’s patent-pending SideScanning™ technology reads cloud configuration and workloads’ runtime block storage out-of-band, detecting vulnerabilities, malware, misconfigurations, lateral movement risk, weak and leaked passwords, and unsecured PII.
SECURITI.ai – SECURITI.ai is an AI-Powered PrivacyOps company that helps automate all significant functions needed for privacy compliance on a single platform. It enables enterprises to grant individual and group rights to data and comply with global privacy regulations like CCPA and bolster their brands. They collect and manage consent from multiple sources, including web properties, web forms, and SaaS applications. Their AI-Powered PrivacyOps platform is a full-stack solution that operationalizes and simplifies privacy compliance using robotic automation and a natural language interface. SECURITI.ai was founded in November 2018 and is headquartered in San Jose, California.
SecureStack – SecureStack helps software developers find security & scalability gaps in their web applications and offers ways to fix those gaps without forcing them to become security experts. The results are faster time to business and a 60%-70% reduction in the app attack surface.
The SecureStack platform’s intelligent automation manages security controls across distributed infrastructures using rules and profiles customizable by customers. SecureStack is noteworthy for its analytics and logging expertise in helping enterprises scale applications across cloud infrastructures.
Stairwell – What makes Stairwell one of the top startups to watch in 2021 is its unique approach to cybersecurity built around a vision that all security teams should be able to determine what alerts are threat-related or not and why. Mike Wiacek, the founder of Google’s Threat Analysis Group and co-founder and former Chief Security Officer of Alphabet moonshot Chronicle, leads the company as its CEO and founder. Wiacek is joined by Jan Kang, former Chief Legal Officer at Chronicle, as COO and General Counsel. Stairwell is backed by Accel Venture Partners, Sequoia Capital, Gradient Ventures, and Allen & Company LLC.
Ubiq Security – What makes Ubiq Security one of the top cybersecurity startups to watch in 2021 is how rapidly their API-based developer platform is maturing while gaining traction in the market. Ubiq Security recently signed commercial agreements with the United States Army and the Department of Homeland Security. This month, the startup announced it had raised $6.4 million in a seed equity investment round. Okapi Venture Capital, an early investor in Crowdstrike, led the round with participation from TenOneTen Ventures, Cove Fund, DLA Piper Venture, Volta Global, and Alexandria Venture Investments. Ubiq will use the funds to accelerate platform development, developer relations, and customer acquisition.
Unit21 – Unit21 helps protect businesses against adversaries through a simple API and dashboard to detect and manage money laundering, fraud, and other sophisticated risks across multiple industries. Former Affirm and Shape Security employees Trisha Kothari and Clarence Chio founded Unit21 in 2018 and work with customers like Intuit, Coinbase, Gusto, and Line to create a powerful & customizable rules engine for risk and compliance teams. Unit21’s highly flexible, customizable, and intelligent cloud-based system provides a configurable engine for transaction monitoring, identity verification, case management, operations management, and analytics and reporting. On October 19th of this year, Unit21 announced a $13 million funding round led by A.Capital Ventures. Additional participation includes investors such as Gradient Ventures (Google’s A.I. venture fund), Core V.C., South Park Commons, Diane Greene (founder of VMWare), William Hockey (founder of Plaid), Chris Britt and Ryan King (founders of Chime), Sumit Agarwal (founder of Shape Security), and Michael Vaughan (former COO of Venmo). Unit21 will use the new capital to grow its product and distribution-focused management team, increase sales and marketing efforts, and sell into new industries.
