Predictive Analytics Landscape - Version 1.0

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Background

At Work-Bench Ventures, our investment thesis focuses on the disruption of legacy enterprise IT stacks. One area in particular which we've been studying is the need to derive business value from all of the data being captured by Big Data tools in today's enterprise environments. Our thesis is that the way to do this is through empowering business and IT users within their own silos with predictive analytics solutions.

This is difficult to do at scale, and the only way business people can leverage predictive analytics is if you give them applications tailored to their specific functions. For these applications to be effective, a certain 'special sauce' is necessary behind the scenes with the proper models and customizations for each unique use case and context.

The Landscape

This landscape represents a first pass at understanding the range of vertical-specific predictive analytics solutions available on the market, with emphasis on startups and newer incumbents (rather than legacy providers such as SAS, FICO, and IBM's SPSS and Watson products). The goal in compiling this landscape is to understand which verticals are supersaturated with new predictive solutions (e.g. predictive sales and marketing applications), versus which have yet to see many new, disruptive solutions.

The key areas of focus included HR, Purchasing, Finance, Sales & Marketing, Security, IT, and Facilities.

For each area that is sparser when it comes to vertical-specific predictive modeling tools, we ask ourselves: is this because the vertical represents a market that is too small; or is it a sector that involves so much proprietary information that all solutions are built in house? Or does it represent an enormous market undersupplied with new, efficiency-adding and revenue-driving solutions?

Community Collaboration

By "open-sourcing" this list to the public, we hope to gain insight beyond what we've been able to initially compile, and to create a dialogue with our enterprise tech community. Did we miss a great company? Is your company not on the list? Are there verticals that are much busier than we've captured here? Please let us know in the comments.

To see a list of all of the companies listed in the landscape and their respective descriptions, check out this Google Doc. It also has areas we researched but couldn't find any companies, so please let us know what we missed in the comments!

Many thanks to my former colleague Rachel Shannon-Solomon for her significant research and contribution to this landscape. Disclosure: Context Relevant is a Work-Bench Ventures portfolio company, and Pymetrics is a Work-Bench member company.

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