Bottom Line: Amazon’s Identity and Access Management (IAM) centralizes identity roles, policies and Config Rules yet doesn’t go far enough to provide a Zero Trust-based approach to Privileged Access Management (PAM) that enterprises need today.
Top-performing companies are more than twice as likely to be using AI for marketing (28% vs. 12%) according to Adobe’s latest Digital Intelligence Briefing.
Retailers are investing $5.9B this year in AI-based marketing and customer...Read more
26,792 startups are relying on IoT as one of their main technologies to launch new products and services and support platform-based business models according to Crunchbase.
78.4% of IoT startups Crunchbase tracks have had...Read more
In 2017 Google outspent Microsoft, Apple, and Facebook on R&D spending with the majority being on AI and machine learning.
Google needs new AI- and machine learning-driven businesses that have lower Total Acquisition Costs...Read more
70% of Americans with incomes of $150,000 or more who shop online have Amazon Prime memberships.
Amazon Prime international customers will grow at a 56% compound annual growth rate (CAGR) between 2016 to...Read more
84% of marketing organizations are implementing or expanding AI and machine learning in 2018.
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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.
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.
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
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
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
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.
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.
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.
“The worldwide CRM market grew from $61.6 billion in 2019. The CRM market grew 12.6% to $69.3 billion in 2020, a strong performance but with wide variations in growth due to pandemic impacts. However, CRM generally continues to thrive and grow above the overall software industry average rates, which were 8.8% in 2020”.
“CRM accounted for the largest share in the overall enterprise software market at 29%”
“Salesforce’s CRM revenue grows by 18.8%, Reaching $13.5 billion In 2020”.
“SAP and Oracle each witnessed a slight decrease in market share to 5.2% and 4.4%, respectively, in 2020, down slightly from 5.7% and 4.7% in 2019”.
Gartner found that “Digital commerce grew at a rate of 17.1%, up from 13.2% growth in the prior year, highlighting the shift to digital”. The research firm also defined a new CRM submarket called Cross-CRM comprised of Customer Data Platform (CDP) and Voice of the Customer (VoC) spending. According to Gartner, “Customer Service and Support (CSS) also continues to be the largest segment in the overall CRM market, accounting for 35.5%share. The following graphic compares the top five vendors’ revenue by subsegments:
Additional interesting insights from Gartner latest CRM market share update include the following:
Five vendors comprise 35.6% of an increasingly fragmented CRM market. “Salesforce, SAP, Oracle, Adobe, and Microsoft jointly held share in the CRM market is at 35.6%, up slightly from 35.2% in 2019, while still leaving a highly fragmented 23% stake for 81 named vendors (that we track in market share) and 41.5% stake for the remaining large number of other software vendor”s. “Shopify grew 41.5% year on year, a higher rate than the previous year’s 38%”.
Salesforce, Microsoft, and Adobe grew faster than the market in 2020. “Salesforce’s CRM revenue grows by 18.8%, Reaching $13.5 Billion in 2020”. Microsoft’s CRM Revenue grew by 17.5% in 2020. Sales is its largest segment with 61% of its CRM revenue and achieved 13.7% growth, above the sales average growth of 10.9% suggesting Dynamics attractive price point, integrated with Power Platform and Office and as a unified CRM suite, are appealing to buyers”. Adobe is the most significant marketing software vendor with its “CRM revenue totaling $2.4 billion in 2020 (just ahead of Salesforce at $2.35 billion), up from $2.1 billion in 2019”.
$55 billion of 2020 CRM sales were cloud-based, comprising 79.4% of all sales, increasing from $47.7 billion in 2019. Gartner believes that “Cloud growth was slightly slower due to the pandemic, and on-premises software (new license and software support services) still had very small growth of just over 4% up from the previous year”. Vertical market niche-based applications are sold on-premise, including those tailored to the specific needs of banking, financial services, manufacturing, and process industries’ operations.
“North America and Western Europe hold the largest share in the CRM market, with 59.6% and 20.7% stakes, respectively”. According to Gartner, “Mature APAC and Japan emerged as the fastest-growing regions with 19.2% and 17.5% growth rates respectively. Adoption lags in these markets compared with North America and Western Europe, and this higher growth rate shows more investment as companies catch up. At the moment however, Mature APAC and Japan together only account for about 9% of the overall CRM market share”.
Global spending on Customer Service and Support (CSS) grew 12.9% in 2020, down from 14.78% in 2019. “The CSS market saw growth of 12.9% in 2020, down from 14.78% in 2019, reaching $24.6 billion, up from $21.8 billion in 2019”. “The leading vendor in the CSS segment is Salesforce , with $5.3 billion in revenue,with service being its biggest cloud, overtaking sales in 2020”, according to Gartner. The next three top vendors include Genesys, Oracle and Zendesk – with Zendesk replacing SAP at No. 4 Zendesk, achieved revenue of $866 million and a growth rate of 25.1%”.
Demand for machine learning expertise, as reflected in LinkedIn open positions, also shows strong growth. Increasing from 44,864 available jobs in 2020 to 78,372 in 2021 in the U.S. alone, organizations continue to staff up to support new initiatives quickly. Globally, LinkedIn’s open positions requiring machine-learning expertise grew from 98,371 in 2020 to 191,749 in 2021.
Market forecasts and projections also reflect strong growth for AI and machine learning spending globally for the long term. The following are key takeaways from the machine learning market forecasts from the last year include the following:
Forrester says the AI market will be defined and grow within four software segments, with AI maker platforms growing the fastest, reaching $13 billion by 2025, helping drive the market to $37 billion by 2025. Forrester is defining the four AI software segments as follows: AI maker platforms for general-purpose AI algorithms and data sets; AI facilitator platforms for specific AI functions like computer vision; AI-centric applications and middleware tools built around AI for specialized tasks like medical diagnosis; and AI-infused applications and middleware tools that differentiate through advanced use of AI in an existing app or tool category. New AI-centric apps built on AI functions such as medical diagnosis and risk detection solutions will be the second-largest market, valued at nearly $10 billion by 2025. Source: Sizing The AI Software Market: Not As Big As Investors Expect But Still $37 Billion By 2025, December 10, 2020.
IDC predicts worldwide revenues for the artificial intelligence (AI) market, including software, hardware, and services, will grow from $327.5 billion in 2021 to $554.3 billion in 2024, attaining a five-year compound annual growth rate (CAGR) of 17.5%. IDC further predicts that the AI Software Platforms market will be the strongest, with a five-year CAGR of 32.7%. The slowest will be AI System Infrastructure Software, with a five-year CAGR of 13.7% while accounting for roughly 36% of AI software revenues. IDC found that among the three technology categories, software represented 88% of the total AI market revenues in 2020. It’s the slowest growing category with a five-year CAGR of 17.3%. AI Applications took the largest share of revenue within the AI software category at 50% in 2020. Source: IDC Forecasts Improved Growth for Global AI Market in 2021, February 23, 2021
AI projects continued to accelerate in 2020 in the healthcare, bioscience, manufacturing, financial services, and supply chain sectors despite economic & social uncertainty. Two dominant themes emerge from the combination of 30 diverse AI technologies in this year’s Hype Cycle. The first theme is the democratization or broader adoption of AI across organizations. The greater the democratization of AI, the greater the importance of developers and DevOps to create enterprise-grade applications. The second theme is the industrialization of AI platforms. Reusability, scalability, safety, and responsible use of AI and AI governance are the catalysts contributing to the second theme. The Gartner Hype Cycle for Artificial Intelligence, 2020, is shown below: Source: Software Strategies Blog, What’s New In Gartner’s Hype Cycle For AI, 2020, October 20, 2020.
Capgemini finds that Life Sciences, Retail, Consumer Products, and Automotive industries lead in the percentage of successfully deployed AI use cases today. Life Sciences leads all interviewed industries to AI maturity, with 27% of companies saying they have deployed use cases in production and at scale. Retail is also above the industry average of 13% of companies that have deployed AI in production at scale, with 21% of companies in the industry has adopted AI successfully. 17% of companies in the Consumer Products and Automotive industries now have AI in production, running at scale. Source: Capgemini, Making AI Work For You, (The AI-powered enterprise: Unlocking the potential of AI at scale) 2021
Between 2018 and 2020, there’s been a 76% increase in sales professionals using AI-based apps and tools. Salesforce’s latest State of Sales survey found that 57% of high-performance sales organizations use AI today. High-performing sales organizations are 2.8x more likely to use AI than their peers. High-performing sales organizations rely on AI to gain new insights into customer needs, improve forecast accuracy, gain more significant visibility of rep activity, improve competitive analysis, and more. Source: Salesforce Research, 4th Edition, State of Sales, June 2020
While 24% of companies are currently using AI for recruitment, that number is expected to grow, with 56% reporting they plan to adopt AI next year. In addition, Sage’s recent survey of 500 senior HR and people leaders finds adoption of AI as an enabling technology for talent management increasing. AI is proving effective for evaluating job candidates for potential, improving virtual recruiting events, and reducing biased language in job descriptions. It’s also proving effective in helping to improve career planning and mobility. Josh Bersin, a noted HR industry analyst, educator, and technologist, recently published an interesting report on this area titled The Rise of the Talent Intelligence Platform. Leaders in the field of Talent Intelligence Platforms include Eightfold.ai. Grounded in Equal Opportunity Algorithms, the Eightfold® Talent Intelligence Platform uses deep-learning AI to help each person understand their career potential, and each enterprise understands the potential of their workforce.Sources: VentureBeat, 8 ways AI is transforming talent management in 2021, March 25, 2021, and Eightfold.ai.
84% of marketers are using AI-based apps and platforms today, up from 28% in 2018. Salesforce Research’s latest State of Marketing survey finds that high-performing marketers use an average of seven different applications or use cases. The familiarity high-performing marketers have with AI is a primary factor in 52% of them predicting they will increase their use of AI-based apps in the future. Source: Salesforce Research, 6th Edition, State of Marketing, June 2020
Marketing and Sales lead revenue increases due to AI adoption, yet lag behind other departments on cost savings. 40% of the organizations McKinsey interviewed see between a 6 and 10% increase in revenue from adopting AI in their marketing and sales departments. Adopting Ai to reduce costs delivers the best manufacturing and supply chain management results based on the McKinsey survey results. Revenue increases and cost reductions based on AI adoption are shown in the graphic below. Source: McKinsey & Company, The state of AI in 2020, November 17, 2020
AI sees the most significant adoption by marketers working in $500M to $1B companies, with conversational AI for customer service as the most dominant. Businesses with between $500M to $1B lead all other revenue categories in the number and depth of AI adoption cases. Just over 52% of small businesses with sales of $25M or less use AI for predictive analytics for customer insights. It’s interesting to note that small companies are the leaders in AI spending, at 38.1%, to improve marketing ROI by optimizing marketing content and timing. Source: The CMO Survey: Highlights and Insights Report, February 2019. Duke University, Deloitte, and American Marketing Association. (71 pp., PDF, free, no opt-in).
Three out of four companies are fast-tracking automation initiatives, including AI. Bain & Company found that executives would like to use AI to reduce costs and acquire new customers, but they’re uncertain about the ROI and cannot find the talent or solutions they need. Bain research conducted in 2019 found that 90% of tech executives view AI and machine learning as priorities that they should be incorporating into their product lines and businesses. But nearly as many (87%) also said they were not satisfied with their Company’s current approach to AI. Source: Bain & Company, Will the Pandemic Accelerate Adoption of Artificial Intelligence? May 26, 2020
Gartner’s Magic Quadrant for Data Science and Machine Learning Platforms predicts a continued glut of exciting innovations and visionary roadmaps from competing vendors. Competitors in the Data Science and Machine Learning (DSML) market focus on innovation and rapid product innovation over pure execution. Gartner said key areas of differentiation include UI, augmented DSML (AutoML), MLOps, performance and scalability, hybrid and multicloud support, XAI, and cutting-edge use cases and techniques (such as deep learning, large-scale IoT, and reinforcement learning). Please see my recent article on VentureBeat, Gartner’s 2021 Magic Quadrant cites ‘glut of innovation’ in data science and ML, March 14, 2021.
76% of enterprises are prioritizing AI & machine Learning In 2021 IT Budgets. Algorithmia’s survey finds that six in ten (64%) organizations say AI and ML initiatives’ priorities have increased relative to other IT priorities in the last twelve months. Algorithmia’s survey from last summer found that enterprises began doubling down on AI & ML spending last year. The pandemic created a new sense of urgency regarding getting AI and ML projects completed, a key point made by CIOs across the financial services and tech sectors last year during interviews for comparable research studies. Source: Algorithmia’s Third Annual Survey, 2021 Enterprise Trends in Machine Learning.
Technavio predicts the Artificial Intelligence platforms market will grow to $17.29 billion by 2025, attaining a compound annual growth rate (CAGR) of nearly 35%. The research firm cites the increased levels of AI R&D investments globally combined with accelerating adoption for pilot and proof of concept testing across industries. Technavio predicts Alibaba Group Holding Ltd., Alphabet Inc., and Amazon.com Inc. will emerge as top artificial intelligence platforms vendors by 2025. Source: Artificial Intelligence Platforms Market to grow by $ 17.29 Billion at 35% CAGR during 2021-2025. June 21, 2021
Tractica predicts the AI software market will reach $126 billion in worldwide revenue by 2025. The research firm predicts AI will grow fastest in consumer (Internet services), automotive, financial services, telecommunications, and retail industries. As a result, annual global AI software revenue is forecast to grow from $10.1 billion in 2018 to $126.0 billion by 2025. Source: T&D World, AI Software Market to Reach $126.0 Billion in Annual Worldwide Revenue by 2025.
Salesforce Q1, FY22 revenue was $5.96B, the best quarter in the company’s history.
$1M+ deals hit an all-time high and were up 120% year-over-year. New $1M+ sales are averaging four or more Clouds, with senior management calling out Service Cloud during the earnings call as gaining strong traction in enterprises. Eight of the top 10 deals included Tableau, and five included MuleSoft.
FY22 Revenue guidance raised from $25.9B to $26B, approximately 22% year-over-year growth.
Service Cloud Q1, FY22 revenue is $1.5B, growing 20% year-over-year.
Tableau sales grew 38% year-over-year, reaching $394M in sales. MuleSoft grew 49% year-over-year, reaching $380M in sales in Q1, FY22.
The Slack acquisition is expected to close at the end of Q2, FY22.
Key takeaways from their Q1, FY22 results include the following:
Q1, FY22 revenue is up 23% year-over-year to $5.96B. Operating margins reached 5.9%, with non-GAAP operating margins reaching 20.2% in Q1. Salesforce successfully capitalizes on its customers’ urgency to transform their businesses while providing them with proven, well-integrated apps and platform strategies to help them build new digital businesses. Salesforce is also well-positioned to increase revenue based on the growing interest in analytics apps, combined with strong demand for mobile and social apps and multi-cloud integration. Combining proven apps and platforms with their ongoing R&D work in machine learning, AI, and predictive intelligence shows Salesforce is well-positioned for long-term growth in an increasingly multi-cloud enterprise world.
Successful multi-cloud sales strategies are propelling double-digit growth in the platform side of the business. Five of the ten $1M+ deals Salesforce signed in Q1 included MuleSoft. The Platform business is the fastest-growing segment of Salesforce today, attaining 28% year-over-year growth. Marketing and Commerce are next at 25% year-over-year revenue growth, driven by many Salesforce customers digitally transforming their selling and service strategies online. The latest quarters’ financial results by product area show how well-integrated and revenue-generating the ExactTarget, MuleSoft, and Tableau are turning out to be today.
Salesforce will reach $50B in revenue by 2026, supported by their Total Available Market (TAM), reaching $204B by CY2025. During the Q1, FY22 earnings call, Marc Benioff predicted Salesforce would nearly double in size in four years, reaching $50B from $26B, which is the projected FY22 revenue target. During the earnings call, Marc Benioff also said, “but I’ll tell you that it’s awesome to see not just be number one in CRM, but we’re going to be the number one enterprise software applications company in the world passing SAP.” The seven core product areas Salesforce compete are combining to create a TAM growing at an 11% CAGR between 2021 and 2025.
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.
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.