I am sitting on a train to Düsseldorf on my way back from Paris, where I presented an update of what we are doing at arcplan to a mixed audience of customers and prospects. Part of my presentation included the usual content of company and product development updates. The outlook included a preview of our next release, code named Xenon, in the context of what is happening in businesses these days. One of the key topics was the explosive appearance of mobile devices and the challenges this poses to organizations – different form factors and operating systems, security issues, and expectations from a user community that is educated by the private consumption of applications on these devices (bringing an expectation of usability to the business environment). Of course, I introduced our first-ever approach in the business intelligence world to solve the dilemma of catering to this ever-increasing diversity of different device types and form factors as DORA: Develop Once, Run Anywhere. This is accomplished by responsive design for business intelligence and analytics applications. The audience was clearly impressed as was our customer advisory board in a similar session last week.
This year we were positioned by Gartner in their annual Magic Quadrant for Business Intelligence Platforms. Although the Gartner analysts expressed strong appreciation for our capabilities (and commented accordingly in the strengths and cautions section of the report), we are positioned at the lower end of the niche vendor section. We were told this is partially due to self-service analytics and data discovery playing a strong role in this year's Quadrant as this represents advanced BI. Really?
I am a firm believer that every individual in an organization will benefit from having relevant analytic content at hand when making decisions. And we all make decisions, permanently, big and small, quick and well thought-out decisions, every day. In fact, it is the holy grail for all BI vendors and organizations alike to create and provide an infrastructure in which decision-relevant, supporting information is available at any time, anywhere. But all studies and analyst opinions I am aware of estimate that penetration of BI is still below 30% of its potential user base within organizations. This used to be credited to complex user interfaces and difficult tools. I don't think this is true anymore. There are virtually hundreds and thousands of easy to use solutions out there these days.
One of the presentations I saw today was from Diana Group, a company that develops ways to make food and pet products more palatable using natural ingredients. Their arcplan solution includes sophisticated business logic that is relevant to the user community as well as the ability to enter data and commentary and churn out budgets and rolling forecasts for all its business divisions. I was wondering how data discovery could ever serve this type of user community. In fact, accessing a data set without the context of what is relevant, what is good or bad, is not helpful for the majority of this user audience. They would be overwhelmed with the options being presented and may even draw improper conclusions. The analyst type of user can add the context, but frequently the average business user cannot. This type of analysis requires an understanding of the business framework and the data set to draw the right conclusions, which is it not necessarily a given for most users.
On top of that, imagine you have heterogeneous data sources for a given decision process – your transactional data from an ERP system and interaction data from a CRM system (like web activity, store visits, etc). How does an average business user match those and makes sense out of this?
I came to the conclusion only a platform that combines many different types of analysis, including data discovery and exploration, ad-hoc analysis, and guided analytics with embedded business logic will serve the purpose of user enlightenment and empowerment. In addition, the various data sources that exist inside and outside an organization need to be accessible and combined in a meaningful fashion.
But this is still not enough. As a human being in an organization you are not alone; you work with peers, you can benefit from the knowledge of colleagues, and you can provide your competence to others. And more frequently than not there are teams collaborating on decision processes. Feedback is important and often improves the quality of the work product or decision.
At the end of my presentation I presented an outlook of our next release, arcplan Xenon, and went through our vision of how these usage scenarios work hand-in-hand. A supply chain manager may start with a dashboard monitoring back-locked orders, identify an issue, jump into arcplan Spotlight (our web-based solution for data exploration), create a view from within the selected dimensionality and pinpoint the cause and implications, pull unstructured data like customer contracts, mark an issue and share with a colleague to request a comment or ask for action. The colleague may take this new report, enhance the content with the new findings and save it for public consumption for similar situations in the future.
There are certainly more dimensions to value creation from BI solutions than data discovery and self-service analytics as it is understood from the BI industry at large. We at arcplan may not be perfect, but we are getting there with an integrated approach of various use cases within a unified platform that leverages a company's variety of existing data sources. At the end of my presentation I was approached by a young Frenchman, a long-term arcplan customer. He gave me the inspiration for this blog article and the headline. He was sincerely impressed and described the vision of Xenon as a "new way of thinking." I wouldn't disagree.