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.
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:
30% of US and UK remote workers say their organizations don’t require them to use a secure access tool, including VPN, to log into corporate databases and systems, according to Ivanti’s 2021 Secure Consumer Cyber Report.
Plus, 25% of remote workers in the US and UK aren’t required to have specific security software running on their devices to access certain applications while working remotely.
And one in four US remote workers use their work email and passwords to log in to consumer websites and apps.
Cybersecurity gaps have continued to widen during the pandemic. A noteworthy survey by Ivanti illustrates exactly how remote workers are putting organizations at risk and where enterprise security is falling short, making those cybersecurity gaps challenging for CISOs to close. Ivanti’s 2021 Secure Consumer Cyber Report outlines the challenges that cybersecurity and IT teams have faced when securing remote workers in what’s being described as the “Everywhere Workplace.” Based on interviews with more than 2,000 US and UK respondents working from home in November 2020, the survey shows that authentication and endpoint security needs to improve across all devices that employees use.
IT Organizations Need Help Closing Their Cybersecurity Gaps
Of the many lessons learned from 2020, among the most valuable are how virtual workforces need self-diagnosing and self-remediating endpoints, while IT organizations need improved unified endpoint management (UEM) as part of a zero-trust strategy. Bad actors continue to target remote workers’ privileged access credentials to gain access and exfiltrate customer, financial and proprietary data, including intellectual property. Ivanti’s survey provides insights into where cybersecurity gaps need attention first:
The most challenging threat surface to protect is a person’s identity because it’s exposed across so many threat surfaces, including personal and work devices, consumer websites, and IoT devices in homes. The pandemic is proving identities are the new security perimeter. A person’s cell phone, personal tablet, and laptop is a real-time digital definition of a person’s identity. Nearly half (49%) of US remote workers use personal devices for their jobs, often without two-factor authentication enabled. The graphic below shows how organizations can close this cybersecurity gap by adopting UEM as part of their go-forward initiatives in 2021 and beyond:
Lack of consistent security software and password standards is a big contributor to US and UK organizations’ cybersecurity gaps today. One in four remote workers can access enterprise resources without any security software in place. An even more surprising finding is that 30% of remote workers in the US and UK can access corporate data without a secure access tool or VPN connection. If a remote worker’s identity is compromised, there’s a one in three chance that their organization will be breached, enabling cyberattackers to move laterally through the company’s systems:
Protecting remote workers’ identities & devices at scale requires Zero Trust. Automating as many tasks as possible while providing a continuous and seamless user experience is the surest way to close cybersecurity gaps. Getting rid of passwords and automating two-factor authentication using Zero Sign-On (ZSO), a core part of the Ivanti platform, is proving essential today. Zero Sign-On relies on proven biometrics, including Apple’s Face ID, as a secondary authentication factor to gain access to work email, unified communications and collaboration tools, and corporate-shared databases and resources. CISOs and their teams also need to consider how mobile threat defense can better secure personal devices against phishing, device, network, and malicious app threats. Late last year, MobileIron (now part of Ivanti) received its second mention in two years in the Forrester Wave™: Zero Trust eXtended Ecosystem Platform Providers, Q3 2020. The Forrester Wave graphic is shown below:
In conclusion, enterprise cybersecurity gaps are widening due to a combination of risky consumer behavior and a lack of consistent security for mobile workforces. And these gaps will only increase as employees increasingly work from anywhere, using their personal devices to connect to corporate resources. To secure and enable the future of work, organizations need to start implementing and maturing an end-to-end zero trust security model today by leveraging new technologies and protecting their current security technology investments.
Bottom Line: CHROs and the HR teams they lead need to commit to keep learning and adopting digital technologies that help improve how they hire, engage and retain talent if they’re going to stay competitive.
Driven by the urgency to keep connected with employees, customers and suppliers, McKinsey’s recent Covid-19 survey finds global organizations are now seven years ahead of schedule on digital transformation initiatives. HR’s role is proving indispensable in enabling the fast pace of digital adoption today. By providing Business Continuity Planning (BCP), HR’s contributions to digital transformation separate the organizations that thrive despite crises versus those left behind, according to McLean & Company’s 2021 HR Trends Report. The graphic below from the report shows how effective HR has been in supporting the rapid changes needed to keep employees communicating and engaged.
The McLean and Company Trends Report also shows that talent management’s major gaps need attention now before they grow wider. These areas include analyzing the employee skills gap (24%), developing employees on new competencies (24%), and training new employees in specific new skills (21%). Improving talent acquisition, retention, diversity and inclusion, and employee experiences by digitally transforming them with greater personalization at scale and visibility is key. CHROs and the HR teams they lead need to close these gaps now.
How To Get Started Digitally Transforming Talent Management
Start with the gaps in talent management you see in your organization. The largest gaps are often in the following four areas: recruiting and talent acquisition; retention of top talent and diverse talent; lack of visibility into employee capabilities; and workforce strategies not aligned to business strategies. Key challenges that need to drive digital transformation in these four areas include the following:
Legacy recruiting and Applicant Tracking Systems prioritize HR’s needs to capture thousands of resumes instead of delivering an excellent candidate experience. Attracting and recruiting the most qualified candidates in a virtual-first world is a daunting task. Organizations who are leaders in digital transformation quickly realized this and relied on automating the applicant experience so much it began to resemble the Amazon 1-Click Ordering experience. McKinsey’s recent Covid survey found that 75% of organizations digitally transforming their operations, including HR, were able to fill tech talent gaps during the crisis:
Source: McKinsey & Company, 2020, How Covid-19 has pushed companies over the technology tipping point—and transformed business forever
Top talent retention is more of a problem than many organizations realize, with top performers receiving between five and ten recruiter calls a month or more. The average tenure of employees at companies has been decreasing for nearly two decades. And a primary driver is not for lack of opportunity, but because employees can’t find a career path internally as easily as they can find a growth opportunity at another company. It’s possible to retain the top talent by guiding employees to what’s next in their careers. Of the many approaches to providing employees a self-service option for personalized coaching guidance at scale, Eightfold’s Talent Intelligence Platform is delivering results at such notable companies as Air Asia, Micron, NetApp, and others. Eightfold found that 47% of top talent leave within two years, but most would happily stay if given the right opportunity. The following video explains how Eightfold helps its customers retain talent:
Employees often lack visibility into new internal opportunities, and both HR and business leaders lack visibility into employees’ unique capabilities. There’s often a 360-degree lack of visibility into new internal career positions from the employee’s side and a lack of awareness on the employer’s side of their employee’s innate capabilities. The lack of visibility from the employer side limits their ability to benchmark talent, create programmatic, scalable, and flexible career development opportunities and ultimately redeploy talent in an agile way that serves business strategies that are evolving rapidly in response to the impacts of the global pandemic.
Workforce strategies that don’t align and support business strategies waste opportunities to improve morale, productivity, and employees’ professional growth. While organizations have invested heavily in valuable infrastructure, including Learning Management Systems (LMS) and other employee experience and development tools, they often lack a unified platform to help deliver the right growth opportunities to the right person at the right time.
Achieving Greater Automation, Visibility And Personalization At Scale
Talent management is core to any digital business and the competitive outcomes each can produce today and in the future. To make greater contributions, Talent Management needs to deliver the following by relying on a unified platform:
Talent Management platforms need to combine ongoing business insights based on operations data, technology management data, and business transformation apps and tools to create new digitally-driven employee experiences quickly.
A key design goal of any Talent Management platform has to be delivering personalized candidate or prospect experiences at scale through every communications channel an organization relies on, both digital and human.
The best Talent Management platforms provide the apps, data, and contextual intelligence to drive task and mission ownership deep into an organization and reinforce accountability. What’s noteworthy about Eightfold’s Talent Intelligence Platform is that it has designed-in empathy and the ability to deliver quick, effective decisions that further reinforce team inclusion. Eightfold’s many customer wins in Talent Management illustrate how combining empathy, inclusion, and accountability in a platform’s design pays off.
As McLean & Company’s 2021 HR Trends Report shows, taking a band-aid approach to solving Talent Management’s many challenges is effective in the short-term. Turning Talent Management into a solid contributor to business strategies for the long-term needs to start at the platform level, however. Eightfold’s approach to combining their Talent Management, Talent Insights and Talent Acquisition modules, all supported by their Talent Intelligence Platform, enables their customers to define their digital transformation goals and strategies and get results.
The Talent Management goal many organizations aspire to today is to digitally transform candidate or prospect experiences so well that people have an immediate affinity for the company they apply to, and the self-service options are so intuitive they rival Amazon’s 1-Click Ordering Experience. Across any industry, digital transformation succeeds when customers’ expectations are exceeded so far that a new category gets created. Uber’s contextual intelligence, rating system, and ability to optimize ride requests is an example. UberEats provides the same real-time visibility into every step of each order, creating greater trust. Domino’s Pizza Tracker app keeps customers informed of every phase of their orders. What’s common across all these examples is personalization at scale, real-time automation across service providers, and real-time visibility. Those same core values need to be at the center of any Talent Management digital transformation effort today.
Bottom Line: LogicMonitor knows first-hand how much pressure DevOps teams are under to produce high-quality code in record time during the pandemic. Acquiring Airbrake proves they get it: DevOps has a high need for speed right now.
LogicMonitor Aims To Solve Today’s DevOps Paradox
The pandemic is forcing every business to make DevOps a core part of their DNA faster than any of them expected. The competitive strengths many banked on in a pre-pandemic world aren’t as relevant as having a steady pipeline of new apps, platforms, and digital channels are. It’s creating a paradox for DevOps: on the one hand, they’re expected to deliver perfect code, and on the other, it needs to be delivered in record time. Pre-pandemic, a typical DevOps team in a $500M+ enterprise has over 200 concurrent projects in progress, with over 70% dedicated to safeguarding and improving customer experiences according to IDC. Today, there are up to 2X more projects, and up to 80% are focused on cybersecurity.
No organization is perfect at DevOps today. Everyone is at various stages of maturity and growth. The pandemic puts a lot of pressure on DevOps teams to get their code right quickly and into a released app in record time. LogicMonitor must see it in their customer base every day. The trade-offs DevOps teams have to make for speed versus quality – and even security – when pushing out a release are real and often tend to overlook diagnostics. That’s why the Airbrake acquisition makes so much sense today. LogicMonitor bought Airbrake to help DevOps teams do what they do best.
The often-quoted Boston Consulting Group (BCG) article, Going All In With DevOps, illustrates the typical pressure DevOps is under to perform, including catching bugs early, solving them, and getting code into test and deployment. According to Airbrake, 73% of their DevOps customers are pushing code multiple times per week – and many said they were deploying code “multiple times per day.” What makes Airbrake a perfect fit for LogicMonitor is how their developer-centric application error and performance monitoring service provides detailed diagnostics beyond the first layer of a bug or problem. In the context of the BCG graphic below, LogicMonitor buying Airbrake gives DevOps teams the diagnostics they need to move faster through error detection and into the test, deploy and release phases.
36% of DevOps team members are struggling to keep up with increased dev speeds and demands, according to Checkmarx’s survey.
55% of DevOps team members have taken on more security responsibility during the pandemic, according to Checkmark’s survey.
DevOps teams are struggling to keep up with their workloads today. LogicMonitor believes that by automating more monitoring processes and providing deeper contextual data and insight, DevOps teams can improve their response times and quality.
Automation pays off with more efficient continuous integration and deployment (CI/CD) cycles across DevOps teams, speeding up time-to-market and improving software quality in the process. Buying Airbrake extends LogicMonitor into developer environments and enables their shared customers to gain visibility into CI/CD workflows while reducing risk and ensuring every code release meets customer expectations. The following graphic illustrates how the CI/CD pipelines support DevOps. The more efficient continuous integration, testing, delivery, and operations, the more code releases DevOps can deliver at a higher quality, on time, and to customers’ expectations.
Source: Deloitte, DevOps Point of View, An Enterprise Architecture perspective, Amsterdam, 2020
The best aspect of LogicMonitor acquiring Airbrake is how practical, pragmatic, and immediately useful their vision of providing unified observability is in supporting DevOps teams under pressure to perform today. Airbrake is LogicMonitor’s second acquisition in just over a year, having also acquired Stockholm-based log analytics company Unomaly in January 2020. LogicMonitor’s Airbrake page provides additional information.
Bottom Line: Using AI to measure and predict revenue, costs, and margin across all Professional Services (PS) channels leads to greater accuracy in predicting payment risks, project overruns, and service forecasts, reducing revenue leakage in the process.
Professional Services’ Revenue Challenges Are Complex
Turning time into revenue and profits is one of the greatest challenges of running a Professional Services (PS) business. What makes it such a challenge is incomplete time tracking data and how quickly revenue leaks spring up, drain margins, and continue unnoticed for months. Examples of revenue leaks across a customers’ life cycles include the following:
Billing errors are caused by the booking and contract process not being in sync with each other leading to valuable time being wasted.
When products are bundled with services, there’s often confusion over recognizing each revenue source, when, and by which PS metric.
Inconsistent, inaccurate project cost estimates and actual activity lead to inaccurate forecasting, delaying the project close and the potential for bad debt write-offs and high Days Sales Outstanding (DSO).
Revenue leakage gains momentum and drains margins when the following happens:
Un-forecasted delays and timescale creep
Reduced utilization rates across each key resource required for the project to be completed
Invoice and billing errors that result in invoice disputes that turn into high DSOs & write-offs
Incorrect pricing versus the costs of sales & service often leads to customer churn.
Revenue leakage gains momentum as each of these factors further drains margin
Adding up all these examples and many more can easily add up to 20-30% of actual lost solution and services margin. In many ways, it’s like death by a thousand small cuts. The following graphic provides examples across the customer lifecycle:
Why Professional Services Are Especially Vulnerable To Revenue Leakage
Selling projects and the promise of their outcomes in the future create a unique series of challenges for PS organizations when it comes to controlling revenue leakage. It often starts with inaccurately scoping a project too aggressively to win the deal, only to determine the complexity of tasks originally budgeted for will take 10 – 30% longer or more. Disconnects on project scope are unfortunately too common, turning small revenue leaks into major ones and the potential of long Days Sales Outstanding (DSO) on invoices. When revenue leaks get ingrained in a project’s structure, they continue to cascade into each subsequent phase, growing and costing more than expected.
The SPI 2021 Professional Services Maturity™ Benchmark Service published by Services Performance Insight, LLC in February of this year provides insights into the hidden costs and prevalence of revenue leakage. The following table illustrates how organizations with high levels of revenue leakage also perform badly against other key metrics, including client referencability. The more revenue leakage an organization experiences, the more billable utilization drops, on-time project deliveries become worse, and executive real-time visibility becomes poorer.
How FinancialForce Is Using AI To Fight Revenue Leakage
It’s noteworthy that FinancialForce is now on its 12th consecutive product release that includes Salesforce Einstein, and many customers, including Five9, are using AI to manage revenue leakage across their PS business. Throughout the pandemic, the FinancialForce DevOps, product management, and software quality teams have been a machine, creating rich new releases on schedule and with improved AI functionality based on Einstein. The 12th release includes prebuilt data models, lenses, dashboards, and reports.
Andy Campbell, Solution Evangelist at FinancialForce, says that “FinancialForce customers have access to best practices to minimize revenue leakage by scoping and selling the right product and services mix to allocating the optimal range and amount of services personnel and finally billing, collecting and recognizing the right amount of revenue for services provided.” Andy continued, saying that recent dashboards have been built for resource managers to automate demand and capacity planning and service revenue forecasting and assist financial analysts in managing deferred revenue and revenue leakage.
By successfully integrating Einstein into their ERP system for PS organizations, FinancialForce helps clients find new ways to reduce revenue leakage and preserve margin. Relying on AI-based insights for each phase of a PS engagement delivered a 20% increase in Customer Lifetime Value according to a FinancialForce customer. And by combining FinancialForce and Salesforce, customers see an increased bid:win ratio of 10% or more. The following graphic illustrates how combining the capabilities of Einstein’s AI platform with FinancialForce delivers results.
FinancialForce’s model building in Einstein is based on ten years of structured and unstructured data, aggregated and anonymized, then used for in-tuning AI models. FinancialForce says these models are used as starting points or templates for AI-based products and workflows, including predict to pay. Salesforce has also done the same for its Sales Cloud Analytics and Service Cloud Analytics. In both cases, Salesforce and FinancialForce customers benefit from best practices and recommendations based on decades of data, which should be particularly interesting considering the “black swan” nature of 2020 data for most of their customers.
Cybersecurity professionals with cloud security skills can gain a $15,025 salary premium by capitalizing on strong market demand for their skills in 2021.
DevOps and Application Development Security professionals can expect to earn a $12,266 salary premium based on their unique, in-demand skills.
413,687 job postings for Health Information Security professionals were posted between October 2019 to September 2020, leading all skill areas in demand.
Cybersecurity’s fastest-growing skill areas reflect the high priority organizations place on building secure digital infrastructures that can scale. Application Development Security and Cloud Security are far and away from the fastest-growing skill areas in cybersecurity, with projected 5-year growth of 164% and 115%, respectively. This underscores the shift from retroactive security strategies to proactive security strategies. According to The U.S. Bureau of Labor Statistics’ Information Security Analyst’s Outlook, cybersecurity jobs are among the fastest-growing career areas nationally. The BLS predicts cybersecurity jobs will grow 31% through 2029, over seven times faster than the national average job growth of 4%.
Key takeaways from their analysis include the following:
Cloud Security skills are the most lucrative of all, predicted to deliver a $15,008 salary boost in 2021. Demand for specific Cloud Security skills is far outpacing the broader demand for cybersecurity skills in the labor market. Burning Glass predicts the fastest-growing skills over the next five years include Azure Security (+164%), Cloud Security Infrastructure (+144%), Google Cloud Security (+135%), Public Cloud Security (+121%), Cloud Security Architecture (+103%). There are 19,477 positions available for cybersecurity professionals with Cloud Security skills.
The fastest-growing cybersecurity skill is Application Development Security, predicted to see a 164% increase in available positions over five years. Cybersecurity professionals with Application Development Security, DevSecOps, Container Security, Microservices Security, Application Security Code Review are predicted to see an average $12,266 salary boost starting next year given the strong marketability of their skills. Like Cloud Security, market demand for Application Development Security professionals’ skillsets far outpaces average cybersecirty jobs growth over five years.
Knowing where the most cybersecurity job postings are by metro area and state provides job seekers with the insights they need to narrow their job search. Cyberseek partnered with Burning Glass to create an interactive U.S.-based heat map that shows cybersecurity positions by state or metro area. The heat map can be configured to show total job openings, supply of workers, supply/demand ratio,and location quotients. You can access the heat map here.
73% of enterprises (over 500 employees) accelerated their cloud migration plans to support the shift to remote working across their organizations due to the pandemic.
81% of enterprises accelerated their IT modernization processes due to the pandemic.
48% of all companies surveyed have accelerated their cloud migration plans, 49% have sped up their IT modernization plans because of Covid-19.
32% of large-scale enterprises, over 500 employees, are implementing more automation using artificial intelligence-based tools this year.
These and many other insights are from a recent survey of IT leaders completed by CensusWide and sponsored by Centrify. The survey’s objectives on understanding how the dynamics of IT investments, operations and spending have shifted over the last six months. The study finds that the larger the enterprise, the more important it is to secure remote access to critical infrastructure to IT admin teams. Remote access and updating privacy policies and notices are two of the highest priorities for mid-size organizations to enterprises today. The methodology is based on interviews with 215 IT leaders located in the U.S.
Key insights from the survey include the following:
The overwhelming majority of enterprises have transformed their cybersecurity approach over the last six months, with 83% of large-scale enterprises leading all organizations. It’s encouraging to see small and medium-sized businesses adjusting and improving their approach to cybersecurity. Reflecting how digitally-driven many small and medium businesses are, cybersecurity adjustments begin in organizations with 10 to 49 employees. 60% adjusted their cloud security postures as a result of distributed workforces.
48% of all organizations had to accelerate cloud migration due to the pandemic, with larger enterprises leading the way. Enterprises with over 500 employees are the most likely to accelerate cloud migration plans due to the pandemic. 73.5% of enterprises with more than 500 employees accelerated cloud migration plans to support their employees’ remote working arrangements, leading all organization categories. This finding reflects how cloud-first the largest enterprises have become this year. It’s also consistent with many other surveys completed in 2020, reflecting how much the cloud has solidly won the enterprise.
49% of all organizations and 81% of large-scale enterprises had to accelerate their IT modernization process due to the pandemic. For the largest enterprises, IT modernization equates to digitizing more processes using cloud-native services (59%), maintaining flexibility and security for a partially remote workforce (57%) and revisiting and adjusting their cybersecurity stacks (40%).
51% of enterprises with 500 employees or more are making remote, secure access their highest internal priority. In contrast, 27% of all organizations’ IT leaders say that providing secure, granular access to IT admin teams, outsourced IT and third-party vendors is a leading priority. The larger the enterprise, the more important remote access becomes. The survey also found organizations with 250 – 500 employees are most likely to purchase specific cybersecurity tools and applications to meet compliance requirements.
Conclusion & Wrap-Up
IT leaders are quickly using the lessons learned from the pandemic as a crucible to strengthen cloud transformation and IT modernization strategies. One of every three IT leaders interviewed, 34%, say their budgets have increased during the pandemic. In large-scale enterprises with over 500 employees, 59% of IT leaders have seen their budgets increase.
All organizations are also keeping their IT staff in place. 63% saw little to no impact on their teams, indicating that the majority of organizations will have both the budget and resources to maintain or grow their cybersecurity programs. 25% of IT leaders indicated that their company plans to keep their entire workforce 100% remote.
It’s encouraging to see IT leaders getting the support they need to achieve their cloud transformation and IT modernization initiatives going into next year. With every size of organization spending on cybersecurity tools, protecting cloud infrastructures needs to be a priority. Controlling administrative access risk in the cloud and DevOps is an excellent place to start with a comprehensive, modern Privileged Access Management solution. Leaders in this field, including Centrify, whose cloud-native architecture and flexible deployment and management options, deliver deep expertise in securing cloud environments.
Instead of relying on data-driven signals of past accomplishments, Eightfold.ai is using AI to discover the innate capabilities of people and matching them to new opportunities in their own companies.
Bottom Line: Eightfold.ai’s innovative approach of combining their own AI and virtual hackathons to create and launch new additions to their Project Marketplace rapidly is a model enterprises need to consider emulating.
Eightfold.ai was founded with the mission that there is a right career for everyone in the world. Since its founding in 2016, Eightfold.ai’s Talent Intelligence Platform continues to see rapid global growth, attracting customers across four continents and 25 countries, supporting 15 languages with users in 110 countries. Their Talent Intelligence Platform is built to assist enterprises with Talent Acquisition and Management holistically.
What’s noteworthy about Eightfold.ai’s approach is how they have successfully created a platform that aggregates all available data on people across an enterprise – from applicants to alumni – to create a comprehensive Talent Network. Instead of relying on data-driven signals of past accomplishments, Eightfold.ai is using AI to discover the innate capabilities of people and matching them to new opportunities in their own companies. Eightfold’s AI and machine learning algorithms are continuously learning from enterprise and individual performance to better predict role, performance and career options for employees based on capabilities.
How Eightfold Sets A Quick Pace Innovating Their Marketplace
Recently Eightfold.ai announced Project Marketplace, an AI-based solution for enterprises that align employees seeking new opportunities and companies’ need to reskill and upskill their employees with capabilities that line up well with new business imperatives. Eightfold wanted to provide employees with opportunities to gain new skills through experiential learning, network with their colleagues, join project teams and also attain the satisfaction of helping flatten the unemployment curve outside. Project Marketplace helps employers find hidden talent, improve retention strategies and gain new knowledge of who has specific capabilities and skills. The following is a screen from the Marketplace that provides employees the flexibility of browsing all projects their unique capabilities qualify them for:
Employees select a project of interest and are immediately shown how strong of a match they are with the open position. Eightfold provides insights into relevant skills that an employee already has, why they are a strong match and the rest of the project team members – often a carrot in itself. Keeping focused on expanding employee’s capabilities, Eightfold also provides guidance of which skills an employee will learn. The following is an example of what an open project positions looks like:
Employee applicants can also view all the projects they currently have open from the My Projects view shown below:
Project Marketplace is the win/win every employee has yearned for as they start to feel less challenged in their current position and start looking for a new one, often outside their companies. I recently spoke with Ashutosh Garg, CEO and Co-Founder and Kamal Ahluwalia, Eightfold’s President, to see how they successfully ran a virtual hackathon across three continents to keep the Marketplace platform fresh with new features and responsive to the market.
How to Run A Virtual Hackathon
Starting with the hackathon, Eightfold relied on its own Talent Intelligence Platform to define the teams across all three continents, based on their employees’ combined mix of capabilities. Ashutosh, Kamal and the senior management team defined three goals of the hackathon:
Solve problems customers are asking about with solutions that are not on the roadmap yet.
Accelerate time to value for customers with new approaches no one has thought of before.
Find new features and unique strengths that further strengthen the company’s mission of finding the right career for everyone in the world.
It’s fascinating to see how AI, cybersecurity and revenue management software companies continue to innovate at a fast pace delivering complex apps with everyone being remote. I asked Ashutosh how he and his management team approached the challenge of having a hackathon spanning three continents deliver results. Here’s what I learned from our discussion and these lessons are directly applicable to any virtual hackathon today:
Define the hackathon’s purpose clearly and link it to the company mission, explaining what’s at stake for customers, employees and the millions of people looking for work today – all served by the Talent Intelligence Platform broadening its base of features.
Realize that what you are building during the hackathon will help set some employees free from stagnating skills allowing them to be more employable with their new capabilities.
The hackathon is a chance to master new skills through experiential learning, further strengthening their capabilities as well. And often learning from some of the experts in the company by joining their teams.
Reward risk-taking and new innovative ideas that initially appear to be edge cases, but can potentially be game changers for customers.
I’ve been interviewing CEOs from startups to established enterprise software companies about how they kept innovation alive during the lockdown. CEOs have mentioned agile development, extensive use of Slack channels and daily virtual stand-ups. Ashutosh Garg is the only one to mention how putting intrinsic motivation into practice, along with these core techniques, binds hackathon teams together fast. Dan Pink’s classic TED Talk, The Puzzle of Motivation, explains intrinsic motivators briefly and it’s clear they have implications on a hackathon succeeding or not.
Measuring Results Of the Hackathon
Within a weekend, Project Marketplace revealed several new rock stars amongst the Eightfold hackathon teams. Instead of doing side projects for people who had time on their hands, this Hackathon was about making Eightfold’s everyday projects better and faster. Their best Engineers and Services team members took a step back, re-looked at the current approaches and competed with each other to find better and innovative ways. And they all voted for the most popular projects and solutions – ultimate reward in gaining the respect of your peers. As well as the most “prolific coder” for those who couldn’t resist working on multiple teams.
Remote work is creating daunting challenges for individuals at home as well as for companies. Business models need to change and innovation cannot take a back seat while most companies have employees working from home for the foreseeable future. Running a hackathon during a global lockdown and making it deliver valuable new insights and features that benefit customers now is achievable as Eightfold’s track record shows. Project marketplace may prove to be a useful ally for employees and companies looking to stay true to their mission and help each other grow – even in a pandemic. This will create better job security, a culture of continuous learning, loyalty and more jobs. AI will change how we look at our work – and this is a great example of inspiring innovation.
Customers’ expectations, preferences, changing patterns in how and why they purchase need to be the core of any digital transformation effort. With it, digital transformation projects flourish and take on a life of their own. Without it, I’ve seen digital transformation projects become myopic, narrowly focused, substituting internal metric gains for measures that matter most to customers.
Digital Maturity Drives Revenue
Anyone who has worked on a digital transformation project quickly sees how the most digitally mature organizations can turn their investments in transformation into revenue by overwhelming customers with value. Initiatives that put customers first can serve to generate greater confidence among C-level executives and board members, leading to more funding. This is because business cases for customer-centric digital transformation projects are easier to create, more defensible and best of all, point to revenue gains and cost reductions.
Deloitte Insights’ recent survey uncovering the connection between digital maturity and financial performance accurately reflects the true state of customer-centric digital transformation. The article explains how the more digitally mature an organization is, the more achievable gains are in diversity and inclusion, Corporate Social Responsibility (CSR), customer satisfaction, product quality, gross margin and long-term financial performance. Deloitte’s latest study finds a strong correlation between the digital maturity of an enterprise and its net revenue and net profit margin. The following graphic makes clear how valuable pursuing digital maturity is, with customers being at the center of all transformation efforts. This contributes to greater net revenue and net profit margin growth:
A fascinating point regarding Deloitte Insights’ research is the correlation it uncovered between an organization’s digital transformation maturity and the benefits they gain in efficiency, revenue growth, product/service quality, customer satisfaction and employee engagement. They found a hierarchy of pivots successful enterprises make to keep pursuing more agile, adaptive organizational structures combined with business model adaptability, all driven by customer-driven innovation. The most digitally mature organizations can adopt new frameworks that prioritize market responsiveness, customer-centricity and have analytics and data-driven culture with actionable insights embedded in their DNA.
Mastering Data & Removing Roadblocks Are Key To Driving Customer Value
The two highest-payoff areas for accelerating digital maturity and achieving its many benefits are mastering data and creating more intelligent workflows. Deloitte Insights’ research team looked at the seven most effective digital pivots enterprises can make to become more digitally mature. The pivots that paid off the best as measured by revenue, margin, customer satisfaction, product/service quality and employee engagement combined data mastery and improving intelligent workflows. The following graphic shows how 51% of revenue growth can be explained by these two factors alone and 49% of improved customer satisfaction.
Data mastery and intelligent workflows are among the easiest areas to measure and include in a business case for digital transformation projects aimed at delivering a transcendent customer experience. Choosing to excel on the dimension of customer-centric data mastery gives enterprises the insights they need to create their unique omnichannel platforms. Adding in intelligent workflows that give customers the freedom to buy how, where and when they choose across any digital platform is the cornerstone of entirely new digital business models today. Capturing the voice of the customer and combining data mastery and intelligent workflows to gain an accurate, true 360-degree view of customers is invaluable for every aspect of go-to-market strategies.
Achieving Digital Maturity Requires A Framework
Enterprises that have customer centricity and a data-driven mindset are the most likely to succeed with a digital transformation initiative. As the Deloitte Insights study inferred, the most digitally mature organizations are continually adapting to customer and market dynamics. They’re prioritizing market responsiveness, striving to improve customer-centricity and have data-driven cultures with actionable insights as part of their DNA. Enterprises who see new digital business model opportunities and act on them capitalize on these three areas of organizational strength. They’re also able to combine their data mastery and intelligent workflows to identify areas of competitive opportunity to help them excel for their customers.
Consider how cybersecurity is now part of any customer experience, for good and bad. Multi-factor Authentication (MFA) and many other forms of identity verification secure customer transactions, yet they can also cause dissatisfaction. For any digitally mature enterprise, integrating cybersecurity into their existing framework is a challenge. The growth of new frameworks designed to empower greater customer-centricity, agility and actionable insights across every facet of a business is a fascinating area of watch.
One of the more interesting is BMC’s Autonomous Digital Enterprise (ADE) framework, which is shown below. Mapping Deloitte Insights’ top investment priorities for the next 12 months across all digital maturity levels to the ADE framework shows why frameworks like BMC’s are gaining adoption, particularly as organizations look to run and reinvent themselves with new digital business models built around AI/ML capabilities. The following graphic provides insights into how Deloitte’s top investment priorities are integral to BMC’s Autonomous Digital Enterprise Framework and its many contributions to the success of new digital business growth.
Quantifying the impact of having a customer-centric digital transformation strategy has proved elusive until recently. Deloitte Insights’ research shows how digital maturity enables greater gains from customer-centric digital transformation efforts. What’s fascinating about their research is how the progression of digital pivots leads to improved margin, revenue, customer satisfaction, diversity and inclusion and product quality gains. Equally interesting is the growing utility of frameworks like BMC’s, which are designed to enable long-standing enterprises to seamlessly embrace new digital business models, so they can flex and change with the world around them.