DISRUPT.SYDNEY™ has led the conversation on digital disruption to a point now that virtually all industry sectors can expect to face at least some degree of digital disruption in the not too distant future. Interestingly, there is one digital business sector, that consumes a significant proportion of corporate IT spend, that to date has experienced little change since first established in the 1970s. This sector is called “Business Intelligence” (BI), but should more accurately called “Business Reporting”. With a catch cry of “one version of the truth”, the major part of the investment has been on trying to build reporting data warehouses across increasingly diverse sources of business operational data. The downside of adopting an aspiration term like “Business Intelligence” is that it provides a false impression that real intelligence gathering of the predictive type is happening, when mostly it is not.
Current Status Quo
We now know that the most prospective targets for digital disruption are areas where processes and technologies have been locked into a mature business and technical infrastructure. While incremental improvements are being made it is too little too late for the demands of a rapidly changing business environment. Gartner has recently flagged this emerging opportunity by differentiating a required “Modern BI and Analytics Platform” from the existing “IT Centric Reporting and Analysis Platform” as:
Table 1: High-Level Comparison of Traditional and Modern BI and Analytics Platforms
|Analytics Workflow Component||IT-Centric Reporting and Analysis Platform||Modern BI and Analytics Platform|
|Data Source||Upfront dimensional modeling required (IT-built star schemas)||Upfront modeling not required (flat files/flat tables)|
|Data Ingestion and Preparation||IT-produced||IT-enabled|
|Content Authoring||Primarily IT staff, but also some power users||Business users|
|Analysis||Structured ad hoc reporting and analysis based on a predefined model||Free-form exploration|
|Insight Delivery||Distribution and notifications via scheduled reports or a portal||Delivery via sharing and collaboration, storytelling, and open APIs|
Source: Gartner (February 2016)
Gartner’s characterization of Modern BI promotes a simpler business created intelligence gathering and use. Gartner speaks of democratizing analytics away from specialist IT departments and to the “owning” business units themselves. This is an admirable development, with IT specialists likely being replaced by specialist data analysts working in, rather than for the business. However, we believe the ‘real disruption’ needs to go beyond this. While moving the responsibility for BI closer to the consuming business is a positive change, it does not remove the need to employ specialist data analysts, especially if predictive analytics is desired. The proposed changes are unlikely to match the sorts of digital disruptive changes we have seen elsewhere and now become accustomed to.
The Digital Disruption Opportunity
We think that the fundamental opportunity for disrupting BI is not just simply moving the responsibilities from IT to the business. The current models for BI were established in an industrial age when manufacturing businesses and operational hierarchies dictated a like BI process of data capture, data cleansing, data filtering, data reporting and finally recommendations and actions. With the more dynamic and human-centered business structures of today, each stage of the current BI process potentially requires collaboration and shared judgement. With the explosion of data availability (big data), questions like which data should we aim to capture? how should we filter it? what can we infer from our analyses? and finally how can we execute the agreed actions?, can no longer be left to the ‘selected few’. We present here two potential disruption opportunities as a lead into workshopping what a disrupted BI marketplace might look like.
Disruptive Social Analytics Opportunity
One proposed model for a disruptive change to BI is to move the focus from the process to the people. Today the focus is on operational data with a secondary acknowledgement that exploiting insights will require sharing and collaboration (Gartner’s Insight Delivery stage). A people focus places conversations at the centre, with operational data simply an input. As data sources explode, it will be left to humans to collectively decide on what data and data quality is sufficient. Business outcomes are predicted more by the quality of the conversations, rather than the quality of the operational data they draw from. Importantly, insight delivery is not simply the last step in a linear BI process, but a continuous occurrence, as staff embed themselves in business and data centred conversations, on a day to day basis. Actions flow incrementally and continuously from such conversations. Learning and improvement is achieved through analyzing conversational data i.e. social analytics and resultant business outcomes.
‘Platform’ Business Disruptive Opportunity
A second and more common approach to digital disruption is the use of the ‘Platform Business’ model, commonly associated with businesses like Amazon, Uber and Airbnb. In a BI context, the Enterprise opens its data sources to an open community of potential data consumers. In essence we would not only be democratizing the consumers of data but also providers. The BI ‘Budget’ would initially be distributed to Enterprise consumers who would be free to use these funds to ‘pay’ for both internal or external data providers. Over time BI purchases would be absorbed into operational budgets, with data providers being able to earn their funds by servicing potential data/intelligence consumers. To do this they would have to market their data services on the platform. The platform itself would be configured to optimize the matching of data owners to data consumers. Providers would have the opportunity to provide value added services like data cleansing/filtering as demand dictates.
The platform would not only facilitate connections between providers and consumers, but also facilitate collaboration and co-operation between data providers themselves and data consumers themselves. In this way economies of re-use and sharing can effectively be achieved.
Other Ideas and Opportunities?
BI systems are arguably one of the last bastions for legacy industrial style thinking in IT. The explosion in data availability (Big Data) will ensure that the pressure for change can only accelerate. This is a $17 Billion market opportunity. Join this workshop to help shape the BI of the future.
If you are interested in discussing the future of BI in a world of social data come and join our workshop at DISRUPT.SYDNEY.