It wasn’t so long ago that the universe of data analytics companies was much easier to describe. In the year 2000 there were some clearly defined categories of companies that were all engaged in some part of the data and analytics world, although data analytics was not really recognized as a discrete sector at the time. Companies typically fit into a specific industry category, such as software (Oracle, Siebel, Epiphany), consulting (Accenture, Bain), data (credit bureaus, IMS, IRI); or a particular technology such as data management (Teradata, Informatica) or business intelligence (Business Objects, Cognos). A number of those companies were acquired along the way. The number of analytics solutions companies was largely dominated by the likes of IBM, SAS, SPSS and FICO although there was also a smaller group of emerging solutions providers, notably in the profit (and yield) optimization field and the still nascent area of web based analytics. Big data, mobile commerce, subscription based pricing and the cloud were still largely on the horizon. Software was typically installed on premise and data analysis was provided as large scale consulting assignments.
The world has certainly changed over the last 10 to 15 years! The era of data based decisioning has arrived and predictive analytics projects that were once the province only of companies able to afford expensive and time consuming consulting engagements can now be performed internally by business users. The internet and ecommerce has forced businesses to better understand and meet the needs of their customer base. Subscription based pricing leveraging the cloud has democratized analytics and enabled smaller companies to perform their own analytics projects. Business intelligence applications and analytics are converging while, at the same time, analytics is evolving from predicting future events to prescribing the best course of action. The balance of power is shifting from the IT department to those who are data competent - wherever it resides in the organization.
In response there has been an explosion in the number of big data and predictive analytics companies being founded. We are still in the land grab phase of this market evolution, and needless to say, there will be winners and losers. The market for predictive data is forecast to grow at a compound annual growth rate of 34% from 2012 to 2017 reaching $48 billion, according to Gartner, so there is room for a number of winners. The global leaders have largely staked out their ground in recent years and have completed acquisitions to reinforce their competitive strengths across multiple industries.
How will the industry evolve in the coming five years or so? There is currently no clear industry structure or taxonomy; business intelligence and business analytics functionalities are converging, analytic solutions may be as much consulting driven as software based etc. In addition, there is a growing number of consumer oriented companies for whom the aggregation and analysis of data is a key strategic asset and a core competency. Capital One led the way with this business approach and now companies such as Amazon, Google, Facebook, Netflix and others use data analytics as a key driver of their competitive advantage.
The industry has now reached a level of maturity where the major sectors have settled and the segments within each sector have emerged. The global leaders will continue to have the resources and expertise to provide a comprehensive range of capabilities and serve companies across all industries and to make such acquisitions as they see fit. They will be complemented by companies that have deep expertise in specific industries and have a collaborative relationship with their key clients. They will need to innovate and acquire capabilities to defend their entrenched position and preserve their client relationships.
Much innovation is likely to occur with start-ups that are focused on either developing analytic software tools or solutions to address specific business problems (such as risk, marketing, operational or compliance areas) or leveraging new technologies. New data analytics businesses are starting every day. The chart below sets out a structure of the data analytics industry including some representative companies in each segment.
Industry Structure Overview
While the Global Leader and Industry Leader segments are fairly well defined, the pace of change in the Tools & Apps and Solutions segments as well as emerging companies in other industries is torrid. Many companies have established strong positions in their sector but must continue to innovate to remain relevant. Consequently, the universe of analytics companies is large and growing. How many analytics companies are there? I will look at this separately in my next blog.
Arguably, a number of trends and events are likely to emerge in the next few years:
The rapid growth environment of the industry will likely result in some companies going public. The existing universe of public data analytics companies includes:
These companies vary widely in size and valuation reflecting the scope of their business activities (not all of which are analytics related) and operating models. Tableau, Splunk and Guidewire all went public fairly recently (May 2013, April 2012 and January 2012 respectively) and each will need to continue growing rapidly to justify their valuations.
How ever the industry evolves, analytics is now in the mainstream – it is no longer a question of whether you are using data analytics but rather how extensively they are being used and managed. In the marketing space, self service, mobile analytics and other features will continue to drive usage down the enterprise and analytic tools will become more of a decision support appliance. Increasing regulatory and compliance burdens along with cyber crime and fraud will underpin analytic solutions in these areas complemented by growth in decision support applications as companies seek to operationalize those decisions.
For more insights, visit my website at www.marinanalytic.com