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I quickly scanned the BI trends for 2023 and what struck me is that the top trend – increasing user adoption – has been the same for the past 20 years. According to this year’s BARC and Eckerson Group international survey the adoption rates of analytics tools are stagnating at around 20%. But if you look at past Gartner, Forrester, and other analysts’ research the adoption rate has always been around 20%. Adoption has been stagnant because the industry has been stuck in the same gear for quite a while. The industry has not addressed the big discrepancy between how the BI tools work and what skills and needs the information consumers have. The promised ease-of-use has not materialized and information consumers feel frustrated with the time and effort it takes to learn tools and to analyze the data for their daily work decisions.

The stagnant 20% adoption rate is a clear sign that doing more of the same will not produce a different result. It is time for the industry analysts to acknowledge that the traditional BI vendors have misunderstood the needs of the information workers and have given the wrong tools to the wrong people.

If we look at the history of BI technology, it becomes clear that the approach has remained the same over the years which has resulted in small functional improvements of basically the same tools. Some tools made charting, pivoting data, and other functions easier, but these improvements did not solve the main problem that information consumers have with the self-service tools. Business Intelligence started with the invention of 4GL languages that made query writing easier. The adoption of these tools was between 2% and 5%. The real breakthrough in adoption was the invention of ad hoc analytics tools by companies like Business Objects and Cognos with drag-and-drop GUIs to generate SQL. But users still needed to understand the underlying data and the logic of combining and aggregating data sets. These ad hoc tools drove adoption to 15% to 20%.

The adoption rate remained the same for the next 20 years despite the introduction of new self-service tools by companies like Tableau, Qlikview and Power BI. The new tools promised to increase adoption because users did not have to know how to join data or make charts. The software magically blended the data and chose the best charts for the users. That magic wore off quickly as it worked only in the simplest cases. Thus, business professionals and other information workers were stuck at the same barrier – they had to know the data and they had to learn complex tools to apply even simple filters and calculations. This is not how information consumers imagined BI. Hence, they did not adopt these tools as the BI companies and the industry experts envisioned.

The problem with the ad hoc and self-service tools approach is that the vision and the expected user needs are formulated by professional analysts and industry experts who model the information consumer expected behavior based on their own knowledge and experiences. What they miss is that less than 3% of Excel users know how to pivot data in Excel, while the BI tools require much deeper knowledge. The information consumers do not see pivoting, chart and tables creation, and other data manipulations as necessary to derive insights. They see DIY analysis as a waste of time and distraction from more important tasks. It is not that they do not understand the value and importance of data insights; they do not understand why they have to learn tools to manipulate the data instead of having easy and direct access just to the analytical results. To most of them, DIY analytics is like asking senior execs to find and book their own flights and hotels. Professionals are expected to spend their time in the most efficient way, and they loathe anything that makes them less efficient. The problem with self-service BI is that while it increases the efficiency of the professional business analysts, it does the opposite for the line of business managers and other business professionals.

If adoption is to grow, reports and dashboards must be designed and implemented as data products tailored to the specific needs of the targeted users. Today most mobile apps are designed as data products, i.e. they allow users to effortlessly interact with data to get the right information to achieve specific tasks. In retail apps users search for items, retrieve lists of items, and do price and other comparisons with just one click. Users do not have to learn how to pivot the lists to make proper comparisons. The ideal data product gives the end-user the right insight without asking them to manipulate data in order to get to the insight.

So why are reports and dashboards not implemented as data products tailored specifically to the needs of their users? The reason is simple – the sheer variety and number of reports and dashboards does not make it cost effective to build and maintain them as apps. Hence, the industry settled on the self-service tools approach and pushed users to DIY analytics.

It doesn’t have to be this way. Storied Data’s innovative interactive documents allow you to develop, package, and distribute reports and dashboards with an app-like functionality without requiring any tools for the end-users to get to the insights. End-users don’t need to learn how to do pivots, charts or tables as the entire experience is packaged in the interactive documents so that end-users can get to all insights with a few clicks. The tailored BI approach allows business professionals to focus on the insights instead of on data manipulation functions. It gives end-users an analytical data product that delivers insights effortlessly and without a possibility for user error. It minimizes the time spent to manipulate data and maximizes the time spent to understand the insights. It delivers the insights that business professionals need without taxing them to learn tools and perform tasks that they do not consider part of their job duties. The tailored approach eliminates the misconception that information workers will become data analysts. Information workers are simply professionals who use insights to do their job better. And we have to deliver these insights to them with a tailored experience in an interactive document accessible on any device, online or offline.

To learn more about how to create tailored BI documents, contact us.

Dr. Rado

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