Executive Profile: Public Sector Chief Information Officer

Director of Customer Programs, Constellation Research
Constellation Research

Carole oversees the Constellation Executive Network, an executive community for innovative senior leaders who value strategic guidance from trusted advisors who understand the power of disruptive technologies. Carole brings over 15 years of marketing, strategic account management, and operations experience, specializing in high technology and professional services. She holds a BA from Santa Clara University and a MBA from Thunderbird, School of Global Management.     ...

Read more

R "Ray" Wang

Principal Analyst and Founder
Constellation Research

R “Ray” Wang is the CEO of Silicon Valley-based Constellation Research Inc. He co-hosts DisrupTV, a weekly enterprise tech and leadership webcast that averages 50,000 views per episode and blogs at www.raywang.org. His ground-breaking best-selling book on digital transformation, Disrupting Digital Business, was published by Harvard Business Review Press in 2015. Ray's new book about Digital Giants and the future of business, titled, Everybody Wants to Rule The World was released in July 2021. Wang is well-quoted and frequently interviewed by media outlets such as the Wall Street Journal, Fox Business, CNBC, Yahoo Finance, Cheddar, and Bloomberg. Short Bio R “Ray” Wang (pronounced WAHNG) is the Founder, Chairman, and Principal Analyst of Silicon Valley-based Constellation Research Inc. He…...

Read more

If you know of a forward-thinking leader who we should consider profiling and who buys enterprise technology, we look forward to hearing from you at CEN.

David L. Stevens

Chief Information Officer
maricopa County, Arizona -Fourth Largest and Fastest Growing County in the US 

Digital Adoption Platform WalkMe acquires Jaco

Alan Lepofsky

Vice President & Principal Analyst
Constellation Research

Alan Lepofsky - VP and Principal Analyst, Constellation Research. With almost two decades of experience in the collaboration software industry, Lepofsky helps organizations improve the way their employees work together to get their jobs done. Lepofsky’s primary research area The Future of Work, focuses on: integrating collaboration and business processes (Purposeful Collaboration), structuring work via Social Task Management, leveraging analytics and digital assistants to work more productively, the strategic impact of mobile computing on business transformation, and measuring workforce culture based on Digital Proficiency instead of age. Twitter: @alanlepoLinkedIn: https://ca.linkedin.com/in/alanlepo     , Title: Big IdeasIntelligent Collaboration: The Intersection of…...

Read more

WalkMe has a simple goal, they want to help companies make sure their employees and customers have the best possible experience with their applications and websites. If your Sales team is struggling using your CRM system, WalkMe will help guide them through the trouble spots. If your customers are not finding what they need on your website, WalkMe can show them the way. Think of it as the modernization of the Help file.

This week WalkMe announced the acquisition of Jaco, who’s product records the clicks people perform as they navigate around a website or web-based applications. This data can then be played back allowing administrators and designers to get insight into the trouble spots people are experiencing, then fix those problems to provide an improved experience.

Jaco’s technology will be integrated into WalkMe’s Digital Adoption Platform, providing a media player like experience, where people can replay, click by click, the interactions people take.

This is WalkMe’s second acquisition of the year, the first being ABBI.io, a tool that helps optimize the experience of mobile applications.

Helping People Get Work Done

One of the biggest challenges with applications and websites is that everyone has a different style in how they use them. Digital Adoption Platforms such as WalkMe provide a way to monitor, study, and ultimately fix the roadblocks people are having. This leads to improved workflows, less support calls, and happier users. WalkMe is aggressively improving their platform, constantly seeking new ways to help organizations improve the adoption of the tools they provide their employees and customers.

Anaplan Steps Up Investment In Connected Planning

Doug Henschen

Former Vice President and Principal Analyst
Constellation Research

Doug Henschen is former Vice President and Principal Analyst where he focused on data-driven decision making. Henschen’s Data-to-Decisions research examines how organizations employ data analysis to reimagine their business models and gain a deeper understanding of their customers. Henschen's research acknowledges the fact that innovative applications of data analysis requires a multi-disciplinary approach starting with information and orchestration technologies, continuing through business intelligence, data-visualization, and analytics, and moving into NoSQL and big-data analysis, third-party data enrichment, and decision-management technologies. Insight-driven business models are of interest to the entire C-suite, but most particularly chief executive officers, chief digital officers,…...

Read more

Anaplan says increased R&D investment will keep it ahead of cloud-based performance management arena. Here’s what connected planning is all about.

When Frank Calderoni, Anaplan’s new CEO, took the stage at the March 27-29 Anaplan Hub 17 event, he cited positive company statistics including signing 250 new customers in the last year (bringing the total count above 660) and more than 75 percent annual year-over-year subscription revenue growth to a $120-million-annual run rate. Just two months on the job, Calderoni also promised a “significant increase” in R&D investment, saying the company intends to stay ahead of the competition.

At Anaplan Hub 17, Frank Calderoni, who joined the company as CEO in January, promised
increased R&D investment. He was previously CFO at RedHat and Cisco, respectively.

Indeed, competition is tightening in the corporate performance management arena, in which the lion’s share of growth is going to cloud-based offerings. Incumbents including Oracle (Hyperion) and SAP (BPC) have introduced their own software-as-a-service options while SaaS rivals Adaptive Insights and Host Analytics have been courting larger and larger customers. Even partners are getting in on the act, with Workday adding Workday Planning to its cloud-based performance management application portfolio in 2016.

Anaplan stands apart among the cloud options in that it focuses on a broader range of business planning challenges than any of its competitors, most of which concentrate on the needs of finance departments. Financial planning and sales planning are Anaplan’s most mature use cases, but the company also supports supply chain, workforce, marketing, IT and other planning needs with more than 195 starting-point applications on its Anaplan App Hub. Roughly two thirds of these domain- and industry-specific apps are offered by partners, such as Accenture, Deloitte and Workforce Insight, who help customers build out and customize apps to their specific needs.

Customers typically start with one planning challenge, such as financial planning and analysis or sales planning, but Anaplan educates customers on the need for “connected planning” as part of its land-and-expand strategy. By connecting plans, companies can understand and account for interdependencies, cascading changes in plans and what-if scenarios across interconnected data, people and processes.

Why do companies need connected planning? Anaplan founder and CTO Michael Gould cited the example of U.K.-based companies that are now in the cross hairs of Brexit. Adequate preparation and forecasting demands more than a single plan; these companies need interconnected plans around possible changes in exchange rates, border tariffs, trade deals, supply costs, pricing and resulting demand. In the U.S. it’s easy to imagine the complex, interconnected planning healthcare organizations will need to come to grips with potential changes in the Affordable Care Act.

Of course, planning and forecasting challenges are more often triggered by routine business dynamics rather than legislative or geopolitical sea changes. Routine business changes such as mergers, acquisitions, digital disruption and emerging market opportunities all trigger complex planning and forecasting challenges. Anaplan customers are typically large companies and fast-growing companies – mostly in retail, banking, technology, healthcare and consumer packaged goods – that face complexity and constant change.

MyPOV on Anaplan’s Progress

There weren’t a lot of high-profile announcements at Anaplan Hub 17 in part because the company is still in the process of delivering capabilities promised at Anaplan Hub 16 (thus, Calderoni’s promise to step up R&D investment). For example, a Business Map feature announced at Hub 16 is still a few weeks away. The Business Map will support connected planning by giving customers a holistic view of all business planning activities, with tagging, searching and filtering by use case, business process and geography.

Also still in the works is a promised expansion of existing predictive capabilities to better support workforce optimization, supply planning, transportation assignment, product marketing, and risk modeling, among other forward-looking analyses. Anaplan did release a module in a limited private beta, but executives say they’re reworking the module to support mathematical optimization without requiring coding.

Late last year Anaplan did deliver on Application Lifecycle Management (ALM) capabilities promised at Hub 16. The new ALM capabilities brought an important productivity advance, enabling customers to split large models and synchronize model versions so they don’t have to replicate changes across development, testing and production instances.

At Hub 17, Anaplan did announce a new data-integration option called Anaplan HyperConnect, which is a licensed version of Informatica Cloud that Anaplan will sell and support under its own brand. It also announced reporting integrations with Tableau, and the company is days away from releasing a DocuSign integration that will take paperwork and, thus, time out of approval processes.

Anaplan didn’t play up the announcement, but in a roadmap session it unveiled plans for two important coming platform capabilities that will unlock yet more growth. A Bring-Your-Own-Key encryption requested by security-conscious banks and financial institution is due out later this year. And a lightweight workflow capability will improve planning throughput, governance and collaboration by routing tasks, approvals and alerts. Release dates weren’t disclosed, and one Anaplan executive quipped that the company wants to live down recent product delays by under-promising and overdelivering.

Anaplan has had its share of executive changes over the last year, as is common in any CEO regime change. But as Calderoni settles in and the company pours more of its considerable venture funding into development, I expect innovation to accelerate and the connected planning story to get stronger.

Related Reading:
Anaplan Scales Platform, Prepares for Prediction
SAP Feels Your Pain, ‘Storms Ahead’ on New Apps, Consumer Insights
Cloud-Based Performance Management: Why the Digital Era Demands Agile Planning

Does Oracle and Accenture make sense - or never ever!

Holger Mueller

Vice President and Principal Analyst
Constellation Research

Holger Mueller is VP and Principal Analyst for Constellation Research for the fundamental enablers of the cloud, IaaS, PaaS and next generation Applications, with forays up the tech stack into BigData and Analytics, HR Tech, and sometimes SaaS. Holger provides strategy and counsel to key clients, including Chief Information Officers, Chief Technology Officers, Chief Product Officers, Chief HR Officers, investment analysts, venture capitalists, sell-side firms, and technology buyers.  Coverage Areas: Future of Work Tech Optimization & Innovation  Background: Before joining Constellation Research, Mueller was VP of Products for NorthgateArinso, a KKR company. There, he led the transformation of products to the cloud and laid the foundation for new Business Process as a…...

Read more

So before I get more questions on Oracle possibly buying Accenture and getting back on the road this - week... better to have a blog post out there on the topic...

 

First things first - quick thoughts in the video: (if the video doesn’t show up, check here)



 

 

No time to watch - here is the one slide update:
(if the slide doesn’t show up, check here)



 

Musings - Why Oracle and Accenture make sense.. or maybe not! from Holger Mueller

 

 

Definitively, because

 

• The Future is Services - We know services are the future - vs. CAPEX style perpetual licenses. Combos of software and human services (aka BPO, more modern BPaaS) have a future, not doubt.
   
• Accenture can bring cloud load - The idea would be that Accenture can 'persuade' most of its customers to move to Oracle products, and provide the services. Stands and falls with 'client leakage'. But Oracle needs load for its cloud to be competitive.
   
• The 21st century "IBM" needs services - Ellison wants Oracle to become the IBM of the 21st century - what the IBM of the 20th century had was services. So Accenture is the missing piece.
   

Never ever, because

• Product vs Services DNA - These are like fire and water - they need each other but never live well together.
   
• Accenture dilutes Oracle's margin - It's all about P/E ratio, less E means a smaller P... not good for Oracle shareholders, who may not be happy.
   
• Services under pressure - There is a lot of talk about digital disruption - but a function that has been thoroughly disrupted by software - is system integrator services. Gone are the 1000+ FTE projects, a dozen consultants is a large project these days. So why would Oracle acquire a player in a systematically struggling industry - and one that Oracle disrupts itself with its cloud products?

 

MyPOV

I would be very surprised if this merger would happen. It’s unlikely that Oracle / Larry Ellison will make the mistake from the 90ies twice – when the integrated product and services Oracle offering feel short in the market when competing with the SAP (product only) and SI combo (back then the Big 7 in case you remember). Basically, the Big 7 influenced customers to implement… where there would be revenue stream for them.

On the flip side one could argue that the market is no longer the same as in the 90ies. Customer want all in one shot, and want it as fast as possible, maybe even need their solution as fast as possible to keep operating. But what has not changed is the stock market: Predictable revenues with predictable margins – and that is so much more attractive with (cloud) software than with cloud related services.

 

What’s your POV?

 

 

Updated Constellation ShortLists - Cloud identity and Blockchain

Steve Wilson

Former Vice President and Principal Analyst
Constellation Research

Steve Wilson is former VP and Principal Analyst at Constellation Research, leading the business theme Digital Safety and Privacy. His coverage includes digital identity, data protection, data privacy, cryptography, and trust. His advisory services to CIOs, CISOs, CPOs and IT architects include identity product strategy, security practice benchmarking, Privacy by Design (PbD), privacy engineering and Privacy [or Data Protection] Impact Assessments (PIA, DPIA). Coverage Areas: -  Identity management, frameworks & governance-  Digital identity technologies-  Privacy by Design -  Big Data; “Big Privacy”-  Identity & privacy innovation Previous experience: Wilson has worked in ICT innovation, research, development and analysis for over 25 years. With double…...

Read more

Last year Constellation Research launched a new analysis product, the Constellation ShortList.  As part of the research lifecycle, our analysts periodically capture the state of play of particular vendor sub-categories, and short list the companies we think are most important at that time.  The ratings are based on the characteristics that make a certain technology transformative or disruptive.  We update the shortlists regularly not only because new products and players constantly emerge, but because the metrics themselves change as categories evolve. 

Constellation ShortLists are free to download.

I’ve recently updated two ShortLists, for Distributed Ledger Technology Labs, and Cloud Identity Management.  Both of these have been relatively stable for the past three months, but please stay tuned for a step change in the Distributed Ledger landscape.  The recent announcements of Hyperledger Fabric, IBM’s Blockchain-as-a-Service built on Fabric, and the Enterprise Ethereum Alliance prove how dynamic this field has become. 

The next Distributed Ledger Labs shortlist will almost certainly see several new players, from tech companies and the consulting houses, and maybe even a start-up.

If you have any news in the blockchain technology or identity management ecosystems, new applications we should look at, or R&D that is coming out of the labs, do let me know.  Reach me at [email protected]. And check out my latest analysis at https://www.constellationr.com/users/steve-wilson.

Digital Business Distributed Business and Technology Models Part 3a; Distributed Service Management (Technology)

Andy Mulholland

Vice President and Principal Analyst, Constellation Research
Constellation Research

Andy Mulholland is Vice President and Principal Analyst focusing on cloud business models. Formerly the Global Chief Technology Officer for the Capgemini Group from 2001 to 2011, Mulholland successfully led the organization through a period of mass disruption. Mulholland brings this experience to Constellation’s clients seeking to understand how Digital Business models will be built and deployed in conjunction with existing IT systems. Coverage Areas Consumerization of IT & The New C-Suite: BYOD, Internet of Things, IoT, technology and business use Previous experience: Mulholland co authored four major books that chronicled the change and its impact on Enterprises starting in 2006 with the well-recognised book ‘Mashup Corporations’ with Chris Thomas of Intel. This was followed in…...

Read more

Service Management is a very broad term, and in the framework of Digital Business has a particularly broad and crucial role. A further complication is that the role is split between the Service Management of the enabling technologies, overlaid by the Service Management of distributed Business interactions/transactions. In the short term the Distributed Service Technology Management will dominate, and must support/integrate both on-premise Enterprise owned infrastructure, and the use of external ‘As a Service’ Cloud Service provider infrastructure.

However for a Digital Business, as defined in Part 1 of this series, to trade in the Digital Economy does require the implementation of an external Distributed Service Business management capability as well. Part 3b of this series provides a briefing on the requirement, and in particular, the potential role of Blockchain technologies.

The preceding part two, see appendix for details, focused on the first layer of simple four layer abstracted framework defining the technologies supporting a Digital Enterprise. Dubbed ‘Dynamic Infrastructure’ this base layer provides on demand access to networking and computational resources with the necessary Service Management directly associated with provisioning. The Distributed Service Technology Management Layer sits above this layer to provide and manage a wide range of sophisticated functions that enable the delivery of Business value.

The separation between the Service Management of the Dynamic Infrastructure and the Distributed Service Technology Management may seem odd, but it is important. The provisioning infrastructure may be provided by the enterprise, but increasingly a large portion will be provided ‘as a Service’ by market leading vendors such as AWS, Google or Microsoft, amongst many others. Enterprises can expect to operate across both Private and Public Infrastructure, and as such their Distributed Service Technology Management must operate seamlessly across both.

Distributed Service Technology Management should be used as a term to refer to those functions that must operate in an independent manner above the Dynamic Infrastructure layer. The over used popular term ‘Platform’ is frequently used to describe these capabilities, but the differences between various Platforms is so large as to render the term meaningless as a requirement definition.

The comparison of ‘Platform’ products is difficult due to the wide range of functions contained in this layer, some of which are very focused on a particular aspect. In addition most Platforms are continually developing in line with deployment experience and market demands. Discussion on standard may be actively underway but it will take both time and market maturity before significant impact. The definition of an IoT Platform started around the connectivity of sensors with associated functionality for data management, but today a Platform are increasingly seen as an integral part of CAAST, (Clouds, Apps, AI, Services & Things). High function Platforms from leading technology vendors support the integrated operation of these technologies as the enabler for Digital Business.

Specialized Platforms, particularly as part of final mile IoT connectivity, are still required and as a further complication these are usually designed to connect into the sophisticated high function Platforms. With such wide diversity in capabilities it makes the term ‘Platform’ effectively meaningless as a capability definition. To gain an insight on the numbers of products defined as an ‘IoT Platform’ then visit a product-listing site such as Postscapes.

Platforms can be broken into four major groupings, a methodology that allows the positioning of major technology vendors to be more readily identified in alignment with their core market focus;

1. Enterprise operated Dynamic Infrastructure; examples; Cisco, Dell, HPE
2. Cloud Services providers+; examples; AWS, Google, Microsoft, Salesforce, SAP,
3. IoT ‘final mile’ focused; examples; Labellum, PTC, ThingsWorx
4. Open Source Development*; examples; AllJoyn, GE Predix, OpenIoT

+IBM, Salesforce and SAP all offer Platforms that connect to their respective Clouds, but their focus is on providing Business Apps, not Cloud capacity. They have been included to avoid questions that would occur if their names were omitted.

*See a list of 21 Open Source Projects here

As is usually the case in the initial stages of a new technology market Vendor proprietary solutions are likely to provide the most attractive solutions for the requirements of first generation deployments. Such deployments tend to be focused and do not require the full range of functions that will be required later when maturity and scale drive product selection. Not unnaturally there will be concern as to vendor lock-in, and/or, restrictions on the development of a fully functional Distributed Services Technology Management layer, but this may be less concerning then it might seem.

For any Digital Enterprise the successful implementation of an independent Distributed Service Management of Technology layer able to integrate ‘any to any’ combinations of Private or Public Dynamic Infrastructure provision into advanced operational Services in support of the higher business layers is a crucial success factor.

A great deal of Technology attention is focused upon the architecture and standards necessary to achieve this as by definition the Distributed Service Management layer be based on standardized principles to ensure ‘open’ operation. Leading technology vendors are active in addressing the requirement for standards. Almost all references to IoT Architecture are in reality references to the Architecture of the Distributed Services Technology Management layer, and have relatively little to contribute to the remaining three layers of the Digital Business framework.

If the number of Platforms, each with different features, available in the market are confusing, then the confusion is made worse when the numbers of communities developing architectural models and standards are added into consideration. This is not the place to examine, even list, each individually. This blog is aimed at providing an informed overview to build understanding of the necessary considerations for enterprise deployment and product evaluation.

Commercially sponsored standards activities often have a scope, or point of view driven by the market positioning and products of particular vendors. This often fragments the overall architecture required as well as making it difficult to use for objective evaluation. Those charged with managing the introduction of the Distributed Services Technology Management into their enterprise need a comprehensive future framework to help them ensure the various tactical deployment choices will come together in a cohesive transformation of capabilities.

Perhaps the best example of an independent approach but with a scope to cover the entire architectural framework comes from the IoT Forum. This body took over the work of the EU on IoT Architecture and extended the reach to be global, as well as to more inclusive with a series of events held around the world. EU funding has reduced reliance on technology vendor sponsorship, enabling the production of detailed report on what is required, and why, under the title of ‘Architectural Reference Model, or ‘ARM’ introduction.

The IoT Forum work on ARM provides an excellent background to understanding this complex requirement, as well as offering a strategic definition as a longer-term target for the development of an Enterprise Distributed Services Technology Management layer. Current deployment requirements can be assessed against this framework to establish requirement definitions for product choice. This is particular useful given the lack of reliable standards to guide choice.

The value of the work on Architectural Frameworks by various bodies on across the Technology industry currently provides guidance on incorporating the first standards. However, in determining how the Technology elements will support interworking internally, and externally, it is easy to lose sight of the real question. The technology aspect is there to support and enable the Distributed Services Business Management capabilities.

The Digital Business Enterprise only exists because it is part of the Digital Economy conducting business through exchanging Services with its industry ecosystem of partners. In this continuously dynamic model with ever changing Business partners and transactions a distributed, and decentralized, commercial transaction recording capability is a necessity.

In a decentralized distributed Digital Business ecosystem operating in a loose coupled, stateless format existing forms transaction management based on predefined close coupled relationships and managed state cannot be applied. The huge interest in Blockchain technology is to provide this new and radically different capability.

It should be noted that BitCoin, often quoted as an example of Blockchain, is not indicative of the overall capabilities that can de developed using Blockchain technologies. BitCoin is a particular implementation that uses the technology in a certain manner with corresponding limitations.

Part 3b of this series provides a briefing on decentralized Distributed Services Business management.

Summary; Background to this series

This is third part in a series on Digital Business and the Technology required to support the ability of an Enterprise to do Digital Business. An explanation for the adoption of a simple definition shown in the diagram below to classify the technology requirements rather than attempt any form of conventional detailed Architecture is provided, together with a fuller explanation of the Business requirements.

Part One - Digital Business Distributed Business and Technology Models;

Understanding the Business Operating Model

Part Two - Digital Business Distributed Business and Technology Models;

The Dynamic Infrastructure

Machine Learning Is The New Proving Ground For Competitive Advantage

• 50% of organizations are planning to use machine learning to better understand customers in 2017.
• 48% are planning to use machine learning to gain greater competitive advantage.
• Top future applications of machine learning include automated agents/bots (42%), predictive planning (41%), sales & marketing targeting (37%), and smart assistants (37%).

These and many other insights are from a recent survey completed by MIT Technology Review Custom and Google Cloud, Machine Learning: The New Proving Ground for Competitive Advantage (PDF, no opt-in, 10 pp.). Three hundred and seventy-five qualified respondents participated in the study, representing a variety of industries, with the majority being from technology-related organizations (43%). Business services (13%) and financial services (10%) respondents are also included in the study.  Please see page 2 of the study for additional details on the methodology.

Key insights include the following:

• 50% of those adopting machine learning are seeking more extensive data analysis and insights into how they can improve their core businesses. 46% are seeking greater competitive advantage, and 45% are looking for faster data analysis and speed of insight. 44% are looking at how they can use machine learning to gain enhanced R&D capabilities leading to next-generation products.

If your organization is currently using ML, what are you seeking to gain?

• In organizations now using machine learning, 45% have gained more extensive data analysis and insights. Just over a third (35%) have attained faster data analysis and increased the speed of insight, in addition to enhancing R&D capabilities for next-generation products. The following graphic compares the benefits organizations who have adopted machine learning have gained. One of the primary factors enabling machine learning’s full potential is service oriented frameworks that are synchronous by design, consuming data in real-time without having to move data. enosiX is quickly emerging as a leader in this area, specializing in synchronous real-time Salesforce and SAP integration that enables companies to gain greater insights, intelligence, and deliver measurable results.

If your organization is currently using machine learning, what have you actually gained?

• 26% of organizations adopting machine learning are committing more than 15% of their budgets to initiatives in this area. 79% of all organizations interviewed are investing in machine learning initiatives today. The following graphic shows the distribution of IT budgets allocated to machine learning during the study’s timeframe of late 2016 and 2017 planning.

What part of your IT budget for 2017 is earmarked for machine learning? 

• Half of the organizations (50%) planning to use machine learning to better understand customers in 2017. 48% are adopting machine learning to gain a greater competitive advantage, and 45% are looking to gain more extensive data analysis and data insights. The following graphic compares the benefits organizations adopting machine learning are seeking now.

If your organization is planning to use machine learning, what benefits are you seeking?

• Natural language processing (NLP) (49%), text classification and mining(47%), emotion/behavior analysis (47%) and image recognition, classification, and tagging (43%) are the top four projects where machine learning is in use today.  Additional projects now underway include recommendations (42%), personalization (41%), data security (40%), risk analysis (41%), online search (41%) and localization and mapping (39%). Top future uses of machine learning include automated agents/bots (42%), predictive planning (41%), sales & marketing targeting (37%), and smart assistants (37%).

• 60% of respondents have already implemented a machine learning strategy and committed to ongoing investment in initiatives. 18% have planned to implement a machine learning strategy in the next 12 to 24 months. Of the 60% of respondent companies who have implemented machine learning initiatives, 33% are in the early stages of their strategies, testing use cases. 28% consider their machine learning strategies as mature with between one and five use cases or initiatives ongoing today.