Let’s say a hypothetical executive is curious one day and decides to conduct a web search on self-service BI. What does he or she find? Chances are good the web browser will hit on some good articles and blogs on the subject—with the majority of opinions pushing the software perspective—that promise magical self-service powers upon installation of their solution. At least that’s what the market wants you to believe. We want to believe it too, because it’s a quick fix. So the executive buys and installs this magical mystery tool on his or her desktop, connects to all sorts of data, and creates the most visually appealing reports anyone has ever seen. The executive is now the envy of all his friends.
What is Self-Service?
As the old adage goes, if it sounds too good to be true, it is. Although this tool can provide limited data access for end users, it’s only one part of a functional BI framework. Self-service doesn’t come in a box and can’t solve larger BI issues on its own, which is one reason this subject has been kicked around a bit over the years. It’s time to pick it up, dust it off, and re-evaluate its value within the larger context of BI solutions today.
First, self-service BI is not something you purchase, plug in or hire. It’s a discipline. A discipline that gets developed in concert with many activities with the goal of bringing together people, process and technology. It requires time, budget, resources and work. It certainly isn’t magical; self-service modules require us to roll up our sleeves to make it work. Oddly enough, this is the same set of activities that drive a high performing business intelligence program.
It’s Important to Stop and Ask for Directions
Throughout the last several years, I’ve worked with many excellent organizations all over the globe that initially went looking for a self-service BI solution. When these tools didn’t perform as advertised, I was brought in to develop BI strategies and programs that actually did realize benefits previously promised by BI software vendors. While software vendors certainly don’t intend to leave their customers in a difficult situation, it’s important to engage expert guidance to ensure the product truly pays off. It is human nature to look for shortcuts, but the reality of BI Self-Service is that it requires a concerted effort and expert planning.
The bottom line is that executive stakeholders need a proven roadmap and clear directions that can assimilate self-service into the larger BI picture. Maybe your organization has users wanting more capability to access, query and report on data as they see fit. Maybe there’s a backlog within the BI support team and that backlog is leaving users frustrated with long waits for responses that don’t meet their real-time needs. While there are still concerns on self-service BI in the market in general, it’s worth discussing tangible benefits—both simple and actionable—that can move your organization forward towards higher-functioning BI self-service.
The Three C’s of Self-Service BI
The three C’s of Self-Service include three key tenets that must be in place for end-users to access their data: Connectivity, Context, and Controls.
How do these three C’s work together to complete the proverbial three-legged stool? Let’s take a look.
Connectivity refers to the right mix of tools and technologies that give your users access to the data assets within. Connectivity is just one leg of the stool; it’s co-dependent on the other two C’s to keep that stool upright. Self-Service BI tools without the other two C’s can, in fact, exacerbate the issue they were supposed to solve, leaving users out on a limb as they try to figure out how to use them. In many cases, identical queries can generate multiple answers, bringing down databases and systems with unplanned intensive or “runaway” queries. In any case, depending on user needs, your Information Management delivery portfolio can and should have a breadth of tools to empower discovery, operational reporting, ad-hoc queries, visualizations, data-mining, and true analytics.
When we apply context to data, we provide a common understanding of what that connected data means. A functional, efficient organization would develop properly designed data models for end-user and BI Tool consumption. This enterprise would also want to provide data dictionaries, metadata, and common business definitions. For example, do your users know where the source data comes from, or how often it’s updated? It’s very easy to get excited by shiny new visualization tools, because they can quickly enable users to connect to any data set and work with it. But are users roaming freely around complex transaction data sets with metadata that is only relevant to the application running against it? In order for data to be truly “intelligent,” it must be put into the appropriate context, especially with regard to how it relates to informing day-to-day decisions.
Without digging too deeply into the many different types of self-service BI consumers, it’s important to recognize that there’s a full spectrum of users who have consequent knowledge of the underlying data to which they are connecting. Some businesses may require highly aggregated and modeled data to ensure that however they select their data, the processes will create syntactically proper queries and precise results. On the other end of the spectrum, tech- and data-savvy power users will only need a little context as they attack the schema on the real world of NoSQL and Hadoop data platforms. Regardless, data must be put into Context to be understood, ingested, and analyzed.
Having provided Connectivity, or access to the data, and subsequently put it into Context so that it’s consumable and relevant to its users, it’s time to attach the third leg, Controls. The idea of Controls may upset the power users and the true data brokers within a given organization, but without it, the remaining users are at the mercy of what could be called the Wild West of Analytics. No organization wants to end up there. This is the land where the same question can generate 419 different answers or quite possibly no answer at all. In this scenario, users looking for self-service will inevitably end up disgruntled, lost and sorely tempted to give up. How can the third C involving Control help? Under the umbrella of Control, one of the key things to empowering self-service involves education and training programs, as well as the development of proper BI Governance and Data Governance.
When rolling out any new tool or capability, it’s essential that training programs be developed for all affected users. Self-service users also need accessible resources and support for questions, and opportunities for collaboration with others within the organization. In addition, self-service users need to have confidence in data quality and be informed when new data sets are available, with additional education as needed. A proper BI Governance program will also provide the conduit and planning to accommodate additional datasets and newer, more advanced tools when available. Controls gather these key disciplines under one umbrella—aligning business units with IT and enabling users to do what they want when they want—by providing a strategy and infrastructure to support the bigger business picture.
The three C’s of Self-Service BI offer a simplified explanation of what, in essence, is hard work. It’s the type of hard work that brings value in terms of efficiency, better decision-making, and empowered users who are all aligned to your organization’s vision. The next time Self-Service is discussed in your organization, keep in mind the three C’s—Connection, Context and Control—and you’ll achieve the necessary framework for a high-performing business intelligence program and an extremely successful Self-Service BI initiative.
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