IBM DataFirst: how it impacts Salesforce and Microsoft

Analytics and big data

IBM held a half-day event on Sept. 27 in New York City to unveil its DataFirst methodology to capitalize on the decision support market, which IBM forecasts as a $2 trillion market opportunity. IBM is removing the barriers between data and how people can use it.

Data synthesis underlies much of the power of digital transformation and cognitive computing as modern applications, analytics and machine learning rely on a steady, reliable and high-volume of data from disparate sources. Consumerized applications that run anywhere, on any device, require ready access to the right data at the right time. Data synthesis platforms and the data flows they manage are the building blocks of an emerging data economy IBM intends to lead and dominate. This market is not about the container or the database, but about managing and readying data for analysis and applications.

Senior vice president of IBM Analytics Bob Picciano kicked off the event, stressing IBM’s focus on synthesizing data for commercial enterprises to facilitate unlocking business value through the analytics-driven, cognitive insights IBM technologies can provide. While there were few mentions of other specific products, IBM Watson DataWorks, a cloud-based data and analytics platform targeted at cognitive business, was discussed. The DataWorks platform rests on the pillars of open-source technologies, most notably Apache Spark, Hadoop, R and Python, which IBM claimed it was giving more prominence within its product ecosystem alongside Apache Spark.

IBM vice president of Data and Analytics Ritika Gunnar outlined the transformative way in which IBM has packaged its cognitive assets to sell them solely as services rather than as traditional software licenses. Specifically, IBM packages DataWorks access by four discrete personas that all revolve around the fifth persona of the chief data officer.

TBR is unclear if the majority of enterprises have chief data officers within their organization. IBM executives explained this role could be shared, it could be assumed by the CIO or the CMO, and the function will evolve over time. The function behind the title is clear, however. Business commerce in the next several decades will increasingly rely on a chief curator of the information from both internal and external sources the IBM DataWorks platform can ingest, cleanse, synthesize and manipulate to generate customer business value.

With an entry point of $50 per month for access to one persona service and 20GB of storage that IBM calls Digital Self Service, IBM has pushed the commercialization and monetization out to simple self-service, “add to cart” selling to encourage interest and experimentation. At the other end of the spectrum, IBM’s DataWorks Plan aimed at large enterprises costs $25,000 per month with 32TB of storage, and is unlimited in the experiences/persona services and data services available to the customer organization.

Implications to IBM

Many of the technologies and capabilities IBM demonstrated at the event have been commercially available as disparate components of the IBM portfolio for at least several quarters. The marketing rollout of the DataWorks platform coupled with the shift in monetization strategy into personas represents a significant pivot in IBM’s go-tomarket activities. In essence, IBM has wrapped its cognitive assets into a cloud-based, consumerized shell and lowered the entry point to decrease financial barriers to adoption. This truly pivots the IBM selling model for its cognitive assets from blue-suit selling to add-to-cart selling, particularly for the midmarket and developer community. In the past 12 months IBM made a concerted effort to capitalize on opportunities from the “long tail of customers” outside its core large enterprise customer base, increasingly catering to SMEs, SMBs and even startups.

IBM has been showcasing its new focus through customer and partner panels at events including InterConnect in February and DataFirst. IBM will face challenges from reskilling and rebalancing its sales force to create a more services-led selling organization that can upsell to entry point subscribers while maintaining direct sales coverage to target enterprise-level DataWorks customers for a true digital enterprise.

Though IBM continues to grow its inside sales team, the rates at which organizations are adopting Bluemix online and lines of business (LOBs) are buying unsanctioned cloud services will test even an organization as large as IBM. Given these circumstances, it comes as no surprise to TBR that IBM hired its first CMO, Michelle Peluso, formerly CEO of web retailer Gilt. IBM recognizes it has to improve its retail marketing presence as the consumerization of www.tbri.com pg. 3 TBR IT that has been prevalent in the device side of the IT market begins to rapidly move up the stack into data center and mission-critical application selling dynamics.

Implications to partners

IBM invests heavily in the partner community, seeking to make engaging with the company as simple and easy as possible. IBM regularly stresses its commitment to open-source technologies as the enabling layer to allow any developer to build solutions on the IBM DataWorks platform. IBM views the DataWorks ecosystem as being expanded through three rings of participants.

Closest to the platform sits the ring of open-standards technologies such as R and Apache, surrounded by the community accepted ring where Docker, Mesos, Openstack, Python, Hadoop and Spark reside, among others. The last ring, defined as trusted partners, consists of large and small IBM partners such as Galvanize, Keen IO, Databricks and Confluent, which bring their niche IP and services capabilities into the ecosystem and build out the accretive network integral to accelerating the revenue and profit performance of the cognitive initiative. IBM also invests heavily in providing technical and business services to the growing number of smaller developer business entities as financial barriers to starting a business drop and the cost of compute access decreases due to the cloud. IBM Bluemix Garages place technical experts close to the key developer communities where IBM assists with technical training and provides much-needed business guidance and networking opportunities for those innovating around the DataWorks platform.

Implications to customers

IBM affords customers simple access to the DataWorks platform, which can enable incubator initiatives with low up-front investment. Additionally, IBM has a full array of professional services capabilities necessary to assist enterprises as they make the technological, cultural and business process shifts required to pivot into the DataFirst economy.

IBM parsed the current market landscape into four discrete parts, placing the majority of the market firmly in the midpoint of the overall adoption road map IBM envisions for cognitive enablement of business commerce.

The hurdles confronting the market revolve around the skills necessary to pivot LOB workers into data scientists and in risk mitigation around the financial investments to pivot to the Data in Action Track. Education, training and continued consumerization of the underlying cognitive assets through digital design will accelerate the data science capabilities. Moving into new business models will require business customers to find concrete use cases justifying different ROI forecasting models. The more IBM simplifies the last mile of any digital transformation initiative for customers, the lower the revenue lift that will be required to justify the investment.

Implications to competitors

The question is not if enterprises will infuse their business processes with analytics insights, but when. IBM has not slowed its rate and pace of investment in building cognitive assets on top of open standards, making participation by other technology providers a very simple and compelling process. Competitors wedded to traditional product sales of their software assets will be hard-pressed to compete against $50 per month trials of a suite of services composed from different IP assets across the entire spectrum of IBM products.

Simple, repeatable frameworks with clear insights into specific business use cases may be able to disrupt its dominant lead in the analytics and insights space. Competitors with closed architectures and an unwillingness to embrace a multivendor hosting environment as the underpinning to their base-level compute offerings will find it extremely difficult to sell against IBM’s increasingly open and composable suite of services that will expand as market adoption accelerates.

Competitors are not standing still. At its Dreamforce event, Salesforce announced Einstein, an artificial intelligence platform for its flagship SaaS CRM product. Similarly, Microsoft invests heavily in stitching PowerBI across its legacy product portfolios as it accelerates portfolio consumption on the cloud.

Geoff Woollacott, principal analyst; Stuart Williams, vice president of Research; Jennifer Hamel, senior analyst Cassandra Mooshian, senior analyst Meaghan McGrath, analyst at TBR