>>Written by Imran Siddiqi, Sr. Industry Value Advisor, Big Data and Analytics
As Analytics tools and platforms continue to proliferate, a central challenge for most practitioners is how to successfully compete for funding dollars for BI / Analytics. Compounding this challenge is that, rather than a core technology, Analytics is considered by many to be an enabling capability. So how do we go about building an Analytics business case?
What’s a Business Case?
First of all, we need to understand that the term “business case” connotes different things to different people. Taking a leaf from Clayton Christensen’s book, The Innovator’s Solution, there are two definitions of the “Job To Be Done” (JTBD) by a business case:
In an environment where there is always competition for resources, developing the right type of business case will determine what gets done versus what doesn’t. However that’s where the similarities end. We’ve seen business cases that are 2 sentences in a spreadsheet, all the way through to a multi-month strategy to convince decision makers, and everything in between
Types of Business Cases
While there is no single taxonomy for a business case, based on the thousands of business cases that we have built for SAP customers, here are 3 levels of business case to consider. Figuring out which of these you need to build should be your first step:
Level 1(Basic): Cost + Technical solution enablers / benefits + Business benefits (qualitative)
This is the simplest form of business case, and one that is suitable for items that are easy to understand and may or may not have a dollar cost. These business cases have relatively lower value and involve minimal change management. Pulling together this type of business case is fairly quick and easy – really the only challenging part is to identify the business benefits.
Level 2 (Intermediate): Level 1 + quantified business benefits + implementation roadmap
This type of business case involves going beyond the cost side to incorporate the dollarized impact of business benefits. In many cases the business benefits can be easily estimated, but the key is to run apples to apples analysis for 3-5 years
Level 3 (Advanced): Level 2 + benefits realization plan + Storyline
The key aspect of this type of business case is that it’s got a storyline. Ideally it starts with the strategic goals of the organization and show this investment will enable those. This used to be onerous to do, but now with tools like the Value Management Center (https://valuemanagement.sap.com) this is within reach of most organizations. SAP has made this a free capability, available to all organizations, so I encourage you to check it out.
5 years ago many of the Analytics business cases were about justifying spend on external software to ramp up a Analytics capability. Now that Analytics is ubiquitous , there’s a need to more precisely define what the strategic intent of the Analytics business case. This can include any one of the following:
In almost all these Analytics business cases, the crux of the case rests on identifying what the impact of Analytics will be on existing business processes. In other words, how much of a “lift” will the capability bring to the operating KPIs of the downstream processes that access to information enable.
In many instances, the need for an Analytics business case is actually being driven by the business, because they want to take advantage of capabilities such as end user visualization and predictive analytics without having to go through IT to have these delivered. In these situations, explaining the linkages between Analytics and core operating processes, information governance and big data is a valuable input that can be provided by IT.
While the above covers how business cases continue to be built for Analytics, two new vectors (mushrooming of new technologies and shift of tech spending to the business, particularly to Marketing), are driving an enhanced approach to building of Analytics business cases. We will cover these in more detail in a future blog post (or come to SAP’s “Getting Started with Big Data” workshops):
You must be a registered user to add a comment. If you've already registered, sign in. Otherwise, register and sign in.
User | Count |
---|---|
10 | |
9 | |
5 | |
4 | |
4 | |
3 | |
3 | |
3 | |
3 | |
3 |