General definitions of business intelligence and analytics tend to apply to enterprise organisations, but we want to tailor them to small and midsize businesses (SMBs) such as banks and financial institutions that typically have fewer than 1,000 employees.
According to Gartner business intelligence (BI) is:
An umbrella term that includes the applications, infrastructure and tools, and best practices that enable access to and analysis of information to improve and optimize decisions and performance.
In the same vein, analytics: "has emerged as a catch-all term for a variety of different business intelligence (BI) - and application-related initiatives.”
Defining BI and Analytics for SMBs
Now we’re not about to question the guys at Gartner, and wouldn’t want to get into a debate about semantics, but for SMBs and financial institutions such as credit unions, microfinance and challenger banks, a more practical definition of the value and what can be achieved with business intelligence and analytics may be more relevant.
When talking to our customers and colleagues about banking BI, we tend to look at it as follows:
- Business Intelligence enables you to discover WHAT happened
- Analytics enables you to discover WHY it happened
- Combining the two provides insight which shows you how to ACT on any problems or opportunities
Self-Service Analytics is Key to Success
Our friends at Gartner define self-service analytics as: “A form of business intelligence (BI) in which line-of-business professionals are enabled and encouraged to perform queries and generate reports on their own, with minimal IT support.
Self-service analytics is often characterized by simple-to-use BI tools with basic analytic capabilities and an underlying data model that has been simplified or scaled down for ease of understanding and straightforward data access.”
As it happens, we completely agree with them. BI should not be the domain of IT. This doesn't diminish the importance of IT in the infrastructure and operation of a BI system, but it is the business users who have the context in which to judge the value of the ‘intelligence’ the system is providing.
IT users may be administrators and power users of BI, however, it is the upfront identification of the business problems or opportunities that will ultimately drive adoption.
Once these have been defined it becomes much easier to assess whether the investment needed to meet these requirements is worthwhile.
For example, your processes could be more efficient, your information could be more timely and more trustworthy, and you could have access to new intelligence to enable decision making.
When all of the possible benefits are combined, it starts to build the business case for the project.
Form Follows Function
To borrow an engineering design term, the ‘function’ of business intelligence and analytics should preclude spending too much time on its ‘form’ or definition. When combined effectively, business intelligence and analytics should enable business users to ACT.
To succeed in real terms, business intelligence projects must be driven by the value derived and by the business decisions they enable.
User adoption is critical, and the way to get there is through ever more self-service analytics. Provide users with the tools they need to answer the Why questions and forget about the semantics.
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