IBM Joins Hybrid, Multi-Cloud Data Science Chorus

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,…...

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IBM sings praises of build-anywhere, deploy-anywhere, open-source analytics. Here's a review of what's now a familiar refrain.

Lots of big tech vendors are now singing from the same hymn book when it comes to data platforms and data science. The message to customers is that they’re offering a range of deployment options, including hybrid-cloud and multi-cloud for agility. They’re also saying they’re open, supporting a range of open source languages, notebooks, frameworks and libraries. IBM hit on all these notes at its November 2 Cloud and Cognitive Summit in New York, but how does it stand out?

IBM’s Cloud and Cognitive Summit marked the introduction of two new tools and a new Hadoop and Spark service on the Watson Data Platform. Executives also revealed the Kubernetes-based containerization of IBM Data Science Experience, a move they said will enable organizations to build and deploy models wherever the data lives. Here’s a deeper look at the details.

It Starts with the Platform

“You can’t get to AI without IA.” That’s how Rob Thomas, general manager of IBM Analytics, explained the need for solid information architecture as an underpinning of artificial intelligence. Indeed, data management comes first, and IBM describes its Watson Data Platform as a kind of operating system for modern, data-driven applications, This cloud-based platform was launched last fall the Strata NY Conference 2016. The Cloud & Cognitive Summit was the launching pad for two new platform capabilities: Data Catalog and Data Refinery.

Data Refinery checks the box for self-service data-prep capabilities, though my sense is that it’s a starting point (see analysis below). Data Catalog helps users, particularly business users, get their arms around available data by tagging or ingesting preexisting metadata and creating an index of all available assets. IBM says its catalog is not just about data – whether on-premises or in the cloud, structured and unstructured. Using an API, IBM says admins can also inventory assets including models, pipelines and even dashboards.

The Summit also marked the general availability of the IBM Analytics Engine, which is the company’s new Hadoop and Apache Spark service. IBM already offered Hadoop and Spark services, of course, but the Analytics Engine was hatched this summer after the company ended development or its own IBM BigInsights distribution and related cloud service in favor of a partnership with Hortonworks. The new service separates storage and compute decisions, with persistence options including a new IBM Db2 Event Store that uses the Parquet data format to deliver what IBM says is much better performance that ordinary object stores.

Constellation’s analysis: Access control, governance and a shared collaborative and community workspace are the key concepts behind Watson Data Platform. The platform gives large organizations with lots of data sources, data pipelines, models and data-driven applications a centralized, project-oriented home in which to prepare, store and analyze data and then deploy and manage models. The analyze, deploy and manage aspects are handled with the IBM Data Science Experience (detailed below).

With the new Data Catalog and Data Refinery capabilities, Watson Data Platform adds depth as a data-management and governance layer. Seeing the demos and talking to multiple executives at the Summit, I came away wanting more detail. I liked the cataloging vision of being able to inventory pipelines, models, dashboards and other assets as well as data. But there wasn’t a lot of nitty, gritty insight into the out-of-the-box capabilities versus what you can do with APIs. As you can read in my Constellation ShortList on Data Cataloging, there’s a lot to a state-of-the-art product in terms of crawling sources, automatically tagging, applying machine learning to track and understand access patterns, supporting collaboration around assets and offering intelligent recommendations to catalog users. I need to see more and talk to customers before I would add IBM Data Catalog to my ShortList.

A couple of executives I spoke to at the Summit described the Data Refinery as a work in progress. The current plan is for the Refinery to be an extra-cost option, but as a buyer, I’d want to see the list of out-of-the-box connectors and details on assisted data-prep and recommendation capabilities, as outlined in my Self-Service Data Prep ShortList. At this writing there’s a free beta available, so it’s possible to do some comparison shopping before paying extra for this feature of the Watson Data Platform.

Every modern data platform worth its salt now separates storage and compute decisions, and the IBM Analytics Engine was an obvious and inevitable update given the end of BigInsights development. IBM has joined Microsoft, Oracle and Pivotal, among others, in offering cloud services based on the ODPi standard. Adding the Event Store is a good step for performant object storage, though I have no idea why IBM has saddled it with “Db2” branding given that it has nothing to do with that commercial relational database.

Data Science Experience Goes Multi-Cloud

IBM introduced Watson Data Platform and Data Science Experience (DSX) back in 2016 with support for open-source options including Apache Spark, R, Python, Scala and Jupyter notebooks. At last week’s event it joined the chorus of notable vendors (also including Microsoft, SAS and SAP) talking up hybrid and multi-cloud freedom of choice for data science work. In the case of DSX this multi-cloud support has been made possible by the recent containerization of the product by way of Kubernetes, so it can be deployed in Docker or CloudFoundry containers “wherever the data lives.” There was also mention of DSX integration with GitHub, although this is apparently in the formative stages (see analysis below).

IBM Data Science Experience provides a project-oriented management layer for unified,
controlled access to data, models, pipelines, notebooks and collaborative work spaces.

DSX is both a part of and, optionally, independent from Watson Data Platform as DSX Local, which can run behind corporate firewalls or on desktops. DSX provides permission-controlled, collaborative access to projects, data, data science tools, services, and a community space. With its support for R, Python and Scala and Jupyter and (now on DSX Local) Apache Zeppelin notebooks, DSX users can tap popular open source libraries including Spark MLlib, TensorFlow, Caffe, Keras and MXNet.

IBM says DSX’s big differentiator is its ability to support “clickers as well as coders.” I covered the coders part above. Clickers, meaning non-data scientists, use DSX as a gateway to SPSS, which is IBM’s commercial offering supporting point-and-click and drag-and-drop modeling and statistical analysis. SPSS is also the source of IBM’s machine-learning-driven, automated model development, deployment and optimization capabilities, which were rebranded from IBM Predictive Analytics to Watson Machine Learning in October 2016.

Constellation’s analysis: IBM and other leading commercial vendors have gotten the message that data scientists want open source options and hybrid and multi-cloud deployment options through which they can avoid vendor lock-in. This year I’ve seen lots of analytics and data science platform progress announcements, from Cloudera, Databricks, IBM, and Microsoft to Oracle, SAP, SAS, Teradata and more. Common themes include support for Spark for processing; object stores for the separation of storage and compute; column stores for performance; R, Python and, in some cases, Scala, for language support; Jupyter and Zeppelin notebook support; and access to Spark ML, TensorFlow, Caffe, Keras, and other leading frameworks and libraries.

These data science platforms provide a centralized environment for securely sharing access to data, collaborating around models and then deploying, monitoring and maintaining models at scale. Cloudera is focused on doing this work on its own Hadoop/Spark platform whereas IBM, Oracle, Microsoft, SAP and SAS also integrate with their respective commercial data warehousing platforms, streaming capabilities, analytics tools and libraries, and public clouds.

Amazon Web Services and Google both have enviable data platform and data science portfolios as well, but their emphasis is on doing it all in their respective public clouds, which isn’t always possible for big enterprises with lots of systems and data still on premises. IBM, Microsoft and SAS have embraced containerization for hybrid and multi-cloud deployment, acknowledging that customers want to be able to analyze data and build, deploy and run models anywhere, including rival public clouds.

IBM and SAS have had a lot to say about support for open source languages and libraries (and in IBM’s case, Apache Spark), but their commercial analytics software offerings are also part of their Data Science platforms. As a customer, I’d want to know exactly what commercial software I’m licensing or subscribing to along with the platform, the terms of that investment and whether there are options to consume that software in an elastic, services-oriented model on-demand.

I was heartened to hear that IBM is also pursuing GitHub integration with DSX, but few details were available on this push. Among the many data science platform announcements I’ve seen this fall, I’d have to say I was most impressed by Microsoft's next generation of Azure ML (currently in beta). Microsoft has integrated with GitHub to track the end-to-end lifecycle of code, configurations and data (as well as the lineage and provenance of data) used throughout the model development/deployment/optimization lifecycle.

Being able to track data lineage is crucial to satisfying regulatory requirements in the banking and insurance sectors. It’s also what’s needed to satisfy General Data Protection Regulation (GDPR) requirements looming in the European Union and to meet growing demand for explainable and interpretable predictions and recommendations. I suspect IBM is on the same track to bolstering data-governance capabilities with GitHub.

In a separate announcement on November 2, IBM, Hortonworks and ING Group are working with the Linux Foundation to promote an open data governance ecosystem that will define interfaces for diverse metadata tools and catalogs to exchange information about data sources, including where they are located, their origin and lineage, owner, structure, meaning, classification and quality. This work stands to benefit both cataloging and, more importantly, data-governance and GDPR compliance.

Related Reading:
Microsoft Stresses Choice, From SQL Server 2017 to Azure Machine Learning
Oracle Open World 2017: 9 Announcements to Follow From Autonomous to AI
SAP Machine Learning Plans: A Deeper Dive From Sapphire Now

Monday's Musing: Infinite Ambient Orchestration

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…...

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My Future of Work Coverage Areas

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…...

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I often get asked about which areas/markets/companies/products I cover, so I thought I'd make a graphic and a video that discusses some of them.

Fall Reading List 2017

Terri Griffith

Professor/Author/Speaker
Simon Fraser University

Terri Griffith holds the Keith Beedie Chair in Innovation and Entrepreneurship at Simon Fraser University’s Beedie School of Business. She spent two decades in the Silicon Valley and, in 2012 was honored as a Woman of Influence by the Silicon Valley Business Journal. Terri helps her students and their organizations accelerate performance and prepare for the futures of work. Through her speaking, writing, teaching, and research, she brings evidence-based leadership and innovation to high-tech, education, and global agribusiness organizations. She inspires and coaches groups on negotiating change and uniquely mixing existing and new capabilities. Her most recent work uses a “bottom-up” approach to automation, including artificial intelligence. Her award-winning book, The Plugged-In Manager:…...

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Some of these books are new for 2017. Others, published before 2017, may be even more important now than they were when first published... at least for me. You'll see a clear focus on the future of work, as well as some heavy hitting general management books. Some link to my earlier reviews, others I'll just share what I was looking for and what I found. If these sound good to you, here is a set from prior years. 

I'm trying something new and will be posting one a day. How long will this take? Depends on how fast I read! I started the list early in the summer, but still have a few in the hopper. Here is the full list if you can't wait. Disclaimers: Where I have received a free copy, I have also purchased at least one more. I am using affiliate links.

Only Humans Need Apply: Winners and Losers in the Age of Smart Machines By Thomas H. Davenport, Julia Kirby

I'm working on a new project focused on human-centric integration of artificial intelligence into work. You'll see many related books in this list. I started my reading here given Tom Davenport and Julia Kirby are key in the world of technology and work. They do a nice job outlining how AI might affect your work, and then given your situation, some personal strategies for action. (My focus is more proactive, how you might craft the work you do given new possibilities.)

What To Do When Machines Do Everything: How to Get Ahead in a World of AI, Algorithms, Bots, and Big Data By Malcolm Frank, Paul Roehrig, Ben Pring

Similar to Davenport & Kirby, this is a great heads-up for what is coming. The authors hail from Cognizant's Center for the Future of Work. Besides a nice job on the footnotes (thank you!) they offer new data from their survey of over 2000 companies. Five approaches from personal to strategic are offered for taking advantage of the changes to come.

Machine, Platform, Crowd: Harnessing Our Digital Future By Andrew McAfee, Erik Brynjolfsson

McAfee and Brynjolfsson have done the most to bring the idea of "racing with machines" versus racing against the machine (phrase from their prior books, The Second Machine Age, and Race Against the Machine) to the general public. In Machine, Platform, Crowd, they take a broad view of the roles digital tools play in organizations and work. If you haven't read their other books, you can start here to see their most recent perspectives.

Under New Management: How Leading Organizations Are Upending Business as Usual By David Burkus

This one is a great primer for the options we have in our futures of work (plural intended: we should be crafting these futures, not focused on any one). From killing email, to pay transparency and reduced hierarchies, this is a book that will appear when I do my "business books: fact or fiction" class (under fact). Students may not want to hear it from a professor, but maybe they'll take heed from Burkus. Many of the techniques in modern organizations are still built for the organizations, technology, and people of the 50s.

Analytics: The Agile Way (Wiley and SAS Business Series) By Phil Simon

I have to keep up my technical skills, and Phil Simon's work is a huge help. When contacted about teaching a short course on the managerial aspects of  business analytics, I suggested they contact Phil instead. They still thought my background would be a better fit given my "plugged-in" approach, but were happy to hear I'd use this book in the class. Didn't work out that time, but now I'm prepared!

Blockchain Revolution: How the Technology Behind Bitcoin Is Changing Money, Business, and the World By Don Tapscott, Alex Tapscott

This is another book I was reading to be sure I stay a step a head of at least some of my students. If you know that blockchain is something related to cryptocurrencies like bitcoin, but that's about it, this is the book for you. Reading it isn't like sitting down with a novel, but you will get a much better perspective of how blockchain technologies will enable new industries and vast improvements to the ones we have. My favorite is only mentioned in passing -- educational transcripts -- but you'll likely see something that affects the work you do today.

Information Rules: A Strategic Guide to the Network Economy By Carl Shapiro, Hal R. Varian

Shapiro and Varian are hardcore economists, but with important translation skills. Both started as academics, but Varian is now Chief Economist at Google. Margo Beth Fleming, then an editor at Stanford University Press, recommended Information Rules to me as the style of book I might try to write. Approachable book about complex issues.

The Power of Onlyness: Make Your Wild Ideas Mighty Enough to Dent the World By Nilofer Merchant

Here the list takes a turn away from digital organization and the future of work -- except that our digital world enables all of us to take a much taller stand and have vast impact if we want. Merchant notes, “You’re standing in the spot in the world that only you stand in, a function of your history and experiences, visions, and hopes. From this spot where only you stand, you offer a distinct point of view, novel insights, and even groundbreaking ideas.” Full review here from a prior post.

The Asshole Survival Guide: How to Deal with People Who Treat You Like Dirt By Robert I. Sutton

Bob Sutton is a Stanford professor and one of the first colleagues I point to as both able to take on tough academic topics and real world issues. This is an actionable follow-on to Bob's books, The No Asshole Rule, and Good Boss, Bad Boss. He mentions 8000 emails readers have sent his way. That makes me sad, but I guess I'm not surprised. Perhaps with this book, Nilofer Merchant's earlier, and the next two on my list, Leadership Learning, and The Advantage, we can all start enacting the changes to reduce Bob's in-box. Like his prior work, the background research is there, but presented in a way that brings you into the community.

Learning Leadership: The Five Fundamentals of Becoming an Exemplary Leader By James M. Kouzes, Barry Z. Posner

This is a recent contribution presenting Kouzes and Posner's deep expertise and data on leadership (over the years they've surveyed more than 2 million people from around the world) . Building from the foundations presented in The Leadership Challenge, Learning Leadership takes on damaging myths that may be holding you back. Many of these are tough to read as they take away excuses you may have lurking in the back of your mind (speaking from personal experience). As you're seeing in this list, I like actionable books. This one gives you chances to pause for preparation, then guides you through next steps to take action. My favorite nugget: "Great leaders are great learners." Excellent advice now, and for our futures of work.

The Advantage: Why Organizational Health Trumps Everything Else In Business By Patrick M. Lencioni

This is the book that is motivating me to build the course, Business Books: Fact or Fiction. Presented with deep examples from industry, I can then tie back to deep examples in research. Given the examples I see in Bob Sutton's books (e.g., The Asshole Survival Guide) and in the news, I don't think traditional organizational behavior and design courses are having the outcomes my colleagues and I hope for. The Advantage, built on Pat and his colleagues' deep experience in management and consulting, puts organizational health at the center of organizational design. It isn't enough to be organizationally smart (great strategy, technology, etc.), you also need to the organization to be healthy. I can teach an entire course by focusing on his key health issues of clarity, communication, reinforcement, and cohesion. Link to prior review.

Own It: The Power of Women at Work By Sallie Krawcheck

I read Own It after hearing Sallie Krawcheck interviewed on NPR. Besides describing her tumultuous career on Wall Street, she shares her reasons for starting her firm Ellevest, an investment platformed focused on women's needs. Women live longer, make less, and tend to be less risky (for good and for bad reasons). Yes, the book feels like marketing for Ellevest, but by the end I'd decided that was ok. 

The Golden Passport: Harvard Business School, the Limits of Capitalism, and the Moral Failure of the MBA Elite By Duff McDonald

Very interesting history and analysis. Given the early foundations of my field of organizational behavior were built at Harvard (Taylor, Mayo, Raiffa, Chandler, and more), it's a bit like People magazine for academics. For MBAs, it's a bit of a cautionary tale or a window into the sausage making of a business school. Especially interesting given the likely shifts we will see in the future of graduate business education. What can we learn from more than 100 years of history?

Rigor Mortis: How Sloppy Science Creates Worthless Cures, Crushes Hope, and Wastes Billions By Richard Harris

Just starting Rigor Mortis. Timely for me as my colleagues and I are looking at a new National Science Foundation proposal. This is another where an NPR interview triggered my interest. Harkens back to my time as a doctoral student involved in a secondary analysis of a medical study. Our results could be replicated. The opposing author's could not. Our results show up in another interesting book, Impure Science (1992, Robert Bell).

Change Agent: A Novel By Daniel Suarez

All work and no play.... Change Agent is fabulous hard science fiction. I heard about this one from the podcast, Triangulation. Suarez does his homework before starting in on a book and this one is set in a world with genetic editing available for hire. The big picture questions will have you ready for your next cocktail party, or will motivate you to take an online class about biohacking.

2017 Thinkers 50 Distinguished Achievement Awards Shortlist

I'll end my Fall Reading list with another list. The 2017 Thinkers50 includes authors already on my short list (e.g., Nilofer Merchant's, The Power of Onlyness, and Tapscott and Tapscott's, Blockchain Revolution), but there are many others I'll be taking a look at. I'm honored to be attending this year's Gala (as a guest) and expect the recommendations I hear there will go far beyond the books on my or their current list. Time to start on my 2018 reading....

Open Business Ecosystems and Closed Technology Platforms Business Enabler, or Business Market Disrupter?

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…...

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WARNING; If you work for an Industry Sector leading Enterprise this piece may serious disturb your piece of mind in respect of your Digital Business strategy. Shifting from Products, to Services, to Outcomes to gain increased revenues at higher margins will be at the heart of your Enterprise Digital Business strategy. To maximizing Business opportunities through interactions almost certainly requires participation in an industry sector Business Ecosystem, and, that requires functionality to be provided by a Technology Platform. Enterprise IT department view Technology Platforms as a mixed blessing trading internal functionality ease against the restrictions of a closed proprietary environment. Will it any different externally when the Platform provider is supporting a Business ecosystem?

The next big business word is; Ecosystem? This is a direct quote from a Forbes article that tracks the amazing rise in the frequency that the term is used, and makes an important statement about the what it should mean. Like a lot of terms with complex meanings all too often it is a short hand to avoid having to really understand the true definition. However, underlying the whole concept of ‘Ecosystems’ is a really big question, and like so many it arises from the collision of business and technology into increasingly becoming an interchangeable and ubiquitous environment.

Using the example of App Shops; How much alignment is there between a Business definition of the value to be found in the Apple, or Google, App shop Business Ecosystems versus the technology controls imposed by the proprietary Apple, or Google, Technology Platform? Extend the example to Amazon Books and ask who has control of the resulting Ecosystem; Amazon or the Publishing houses that controlled the market for more than one hundred years?

Does it matter? Are the technology platforms and business ecosystems just two sides of the same coin and nothing to consider? Arguably it does matter as its difficult, perhaps impossible, to have a business ecosystem without some form of common shared technology to support the interactions within it, but does that have to be a vendor provided technology ‘platform’ in the format above?

From a business point of view, the value in App Shops for Mobile Devices lies in opening up, or expanding, the available marketplace resulting in the creation of economic value through bringing sellers and buyers together. Thus, the business definition of an Ecosystem, first and foremost, lies in the creation of increased trading opportunities. The statistics for Apple and Google App Shops support this by showing the numbers of participants and the value of their activities together as rising at a remarkable fast level since their introduction.

Both App Shop ecosystems exist because Apple and Google have each developed a proprietary technology Platform to enable their respective market places to form and grow. The business value in the trade that each company has created is unquestionable, it’s the nature of the underlying, and necessary, Technology Platforms that warrant some thought. To enable the business functions each is a proprietary set of software that forces a choice to support one or other, or increasingly both, in a closed environment. Its arguably a good trade off in App shops case, but is the same true in other industry sectors.

Will the outcome of the creation of Industry sector Digital Business Ecosystems be the result of Darwinian competition in each industry sector ending with the establishment of one, or two, competitive Platforms? And will the resulting Platforms, and their controlling influence, belong to new entrants, or will the existing industry sector leaders be able to maintain their position?

Amazon is a perfect example; seen first and foremost as a market place created by a massive ecosystem of sellers and buyers, with the recognition of its enabling role as a Technology platform decidedly in second place. The function of what can, and cannot, be achieved is much more closely aligned to the commercial operation of the marketplace ecosystem then to the technology functionality. In fact, the sheer usefulness of the Amazon technology and the adoption across the market into a wide variety of reading devices has left the question of technology lock-in as largely irrelevant, unless you are a competitor!

The combination of the Amazon Kindle innovation as a reading device plus the Amazon Technology Platform quickly defined the emerging online Digital market for books. Industry sector leaders such as Barnes and Noble in the USA, were relegated to selling via Amazon to reach their ecosystem of buyers as their positioning and business model slowly failed in the face of this shift.

It is an interesting shift in perspective from the internally orientated Enterprise IT adoption case for a particular product suite to gain simpler, more reliable and less costly technical integration by using a Platform, to the high profile external business strategy requiring access to an Ecosystem. However, the principle of ‘lock-in’ is still present, and in time could become a strategic threat to a market sector leader.

The danger is that in enabling your Enterprise’s new high growth Digital Business market strategy by using a leading Platform to reach the market place ecosystem may well work short term, but in the longer term you may in actuality be helping to establish a new market sector leader. How many of the 90% of C Level Executives stating their Enterprise has a Digital Strategy have recognized this? In fact, unwittingly some Digital Business strategies will actively help to build their Industry ecosystem disrupter by channeling their business via the ubiquitous Technology Platform vendor![PD1]

The Market Mogul identified the importance of Technology Platforms in building and controlling Digital Business in an article entitled; Startup Unicorns and the power of the Digital Economy. The entire article is well worth reading and the following are isolated extracts;

Uber, Airbnb, Alibaba, eBay, Facebook – everyone will have heard of these companies and how they disrupted entire industries. ….. But if one takes a closer look, it is not necessarily their products or services that enabled these companies to change the game. It is the platforms through which they sell the products and services that drive the change in the most traditional and well-established industries… Today, the top 15 public companies which have adopted a platform business model, have a cumulated $2.6trn in market capitalization. At the same time, an increasing number of start-ups are entering well-established industries with a platform strategy…. Clearly, the platform business model has great potential, and increasingly more companies in every industry become aware of this potential.

The frustrations, and constraints, caused by a past generation of internally deployed Enterprise IT Technology Platforms seem to have been forgotten as the new generation of Technology Platforms arrive as external Business Ecosystems. Introducing Digital Business innovative within entrepreneurial ecosystems and opening up a wealth of business opportunities to bring new revenue and proprietary limitations are seen as insignificant. Dynamic interactive Digital Business must have new forms of shared distributed revenue creating activities, and that in turn means there has to be a shared Technology platform. From a Business management perspective, there is no case to consider as this is the ‘entry fee’ to gain access to the market the ecosystem provides.

With the advent of Cloud based Service model the ‘entry fee’ is minimal and the lock in risk from investment and pay back obsolesce minimal, as the saying goes ‘What’s not to like’! A read through the following which is from the Wikipedia entry on Ecosystems and their development introduces a note of caution based on past commercial experience. The definition also aligns with the examples of Digital Business ecosystems used above

An economic community supported by a foundation of interacting organizations and individuals—the organisms of the business world. The economic community produces goods and services of value to customers, who are themselves members of the ecosystem. The member organisms also include suppliers, lead producers, competitors, and other stakeholders. Over time, they coevolve their capabilities and roles, and tend to align themselves with the directions set by one or more central companies. Those companies holding leadership roles may change over time, but the function of ecosystem leader is valued by the community because it enables members to move toward shared visions to align their investments, and to find mutually supportive roles. https://en.wikipedia.org/wiki/Business_ecosystem - cite_note-3

Are there alternatives that place your brand and sector leading Enterprise at the center of an Industry sector ecosystem? More importantly, what would this Business Ecosystem look like and how would it function? A few industry sector leaders have seen the opportunity and, by moving fast, have created their Industry sector Business Ecosystem - with their brand and positioning at the center. Later Business entrants, unless directly competitive, now join as the de facto ecosystem.

John Deere, an established World leader in agricultural machinery has maintained, even strengthen its position by moving early and fast. A great deal has been written about John Deere and Precision Farming, the Digital revolution of Agriculture, but little makes the point quite so starkly as Digital Social Strategy in their article ‘How John Deere turned Technology into Business Transformation’.

This ecosystem helps farmers to gain insight into their current operations and manage their farms more proactively. Not only do farmers reap benefits from this approach, John Deere does so too. By creating an entire ecosystem, John Deere extends their offering beyond products into delivering services. Moreover, only allowing John Deere products access to the ecosystem creates a buyer lock-in for the farmers. Once they own John Deere equipment and make use of their services, it will be very expensive to switch to another supplier, thus strengthening John Deere’s strategic position.

At the heart of the John Deere approach is the need to be Open to allow the Ecosystem to grow by supporting wide spread active participation through Data sharing. The open source programming language R in combination with Open DataBase Connectivity, ODBC, underpins the John Deere ability to maximize Ecosystem value to participants through data, and proves that Open Source can be deployed successfully by Industry Leaders to build their own Ecosystems.

The power of open source levels the playing field for companies both big and small. It lowers barriers and offers a neutral environment that fuels and allows companies to innovate and evolve. This open collaboration helps companies like John Deere work with the ecosystem to create the best solutions for its customers. In return, John Deere offers insight and experience and works with other companies make the ecosystem stronger.

EdgeX Foundry is a prime example of a community approach to open source value. Hosted by The Linux Foundation, EdgeX is an open source project building software that enables and facilitates an ecosystem for Internet of Things (IoT) edge computing by enabling interoperability across tools and solutions. More than 60 vendors have come together in an open forum to create this ecosystem in a way that delivers shared value across the participants rather than large rents to a single company. The underlying hope is that this will accelerate the entry of participants into the ecosystem through equal access, and increase the market size by assuring customers that solutions built with EdgeX a safe, performant, and vendor neutral choice in a confusing and emergent marketplace.

Summary; The imperative for gaining competitive advantage via (these) ecosystems is for firms to create sustainable ecosystems and for the lead firm how to capture the value created by the ecosystem. Quote https://www.jbs.cam.ac.uk/fileadmin/user_upload/research/workingpapers/wp1006.pdf

The question is whether your Enterprise will seize the lead or through a failure to realize the implications by taking the obvious route via a vendor / provider help them to become the market disruptor and new industry sector leader.