The term self-service BI (SSBI) is common, but it is also commonly misunderstood. The first things I ask clients who want to discuss an SSBI project are: “What do you mean by SSBI? Who do you expect to use it, and what are their analytical and data skills? What data will it access? What are the source systems?” And most importantly: what are the business expectations?
SSBI certainly meets several important needs, particularly by helping business users access data without having to wait in a queue for IT support. In 2016, Gartner made a major change to its Magic Quadrant for BI and Analytics Platforms to include only data discovery tools, highlighting a shift in the industry towards agile, accessible analytics.
But the initial success of a new SSBI tool is often followed by frustration. Let’s look at how that can happen. A company acquires a highly rated data discovery tool. It is a genuinely good tool. Suppose the first rollout is with a limited set of data, such as Salesforce only.
Power users start to use it. They are the people who know the business group’s data inside and out. They know the schema: tables, columns and all the relationships. They know what data is available and its quality. They are the experts who built the sophisticated spreadsheets that other business users have historically relied on (often referred to as data shadow systems). These people are really good with the tool, and the tool makes it easy for them to do all the work they used to do with spreadsheets.
After the successful rollout, a couple of things tend to happen:
- One, other business users start to use the tool. They are experts in their business area, but not in data analysis. They need things like pre-built visualisations and reports they can choose from. They would like to be able to filter the data, drill into the details, change the visualisations and export them to spreadsheets. They cannot waste time worrying about where the data comes from and what state it is in.
- Two, the tool ramps up to full speed. It now accesses data from more sources, which means many more data relationships and much more complexity. All the data integration comes into play, since not all data adheres to the “5 Cs”: clean, consistent, conformed, current and complete.
Non-power users do not understand data integration, nor should they have to. The self-service solution, which started out so promisingly, no longer delivers the results everyone needs and is not saving anyone time. None of this is unusual: it happens in companies all the time.
The key, before implementing SSBI, is to think about these questions:
- What do you mean by SSBI?
- Are you thinking of pre-built reports and dashboards or the ability to create reports? Who do you expect to use it?
- Your data experts or your average business person? What data will it access, and where?
- A single data source or multiple sources and types that will need to be integrated?
- What are the business expectations? Will that tool meet everyone’s needs?
SSBI is a great tool in the BI arsenal, but you need to know what you are up against. Set the right expectations and make sure you understand all the nuances.
At Digital Fox Data we help implement self-service BI with the right foundation —data model and governance— through our Business Intelligence consultancy in Qlik, Tableau and Power BI. And if you want to see where self-service is heading, read about agentic analytics. Shall we talk about your project? Get in touch.