There are several reasons why a BI-project might turn sour. Here are a few tips on why that might be -and how to make your project a successful one.
THE TECH GETS THE BETTER OF YOU
Your IT -department and business management most likely have a different point of view to what BI looks like, and how your new BI project should shape up. If the dialogue between tech -oriented consultants, and pragmatic business management is inadequate, the end result might not serve business purposes or end users as well as intended.
Problem solved: Don’t leave it up to your IT -department alone to plan and purchase BI. It is not strictly just an IT -project. Get your management involved, make sure your IT and business management understand each other’s needs. Plan an overall BI -process with clear goals and then choose the tech to suit it.
THE PROJECT DOESN’T HAVE A CLEAR GOAL OR FRAMEWORK TO START WITH
If everyone wants everything immediately, it most likely means no-one is going to get a thing. Trying to solve every problem in the very beginning will overflow the size of your project before you even get started. Whilst your project is stretching on every corner, you will be spending time in meaningless meetings with your targeted schedule, budget, and most of all goals, turning to dust. Without a clear game plan, phases of progression, and targets, you’ll end up with a bundle of useless data models to answer none of your questions.
Problem solved: Implement your BI -project in clear phases with individual goals to suit the overall targets. Consider for example, implementing each business area or organizational function individually -finance, operative, top management, HR etc.
YOU CAN’T PREDICT THE FUTURE – OBJECTIVES ARE NARROWED DOWN TOO MUCH
A BI -project is always agile. A sequence of iterations. An ongoing, revolving process.
Be careful while defining your needs and the answers you want from your business intelligence -solution. Narrowing down and restricting your current needs, might make your life difficult in the future. The answers your brand new solution is providing might raise brand new questions and prove your current solution inadequate as it is. You’ll face an unfortunate situation, where your finished solution hasn’t been designed to provide answers to these newly found enquiries and extending your solution means basically returning back to point A.
This kind of a project compares to a wave hitting a wide shoreline (everything for everyone) but eventually sliding back to the starting point.
Problem solved: When planning and executing the project gather as much data as you can, even though it might not seem relevant at the time. Try to see a few steps further. Maybe you should start tracking history or versioning data models already from the beginning. Who knows when you’ll want to see the past and future trends or snapshots of data? The execution should start with adding new elements instead of always starting from the beginning.
QUESTIONS, NEEDS, ANSWERS – SOLUTION ISN’T AT ALL DATA DRIVEN
The solution doesn’t scale itself well enough according to the changing needs. A solution that serves you today might become obsolete tomorrow. Not an ideal outcome, when dealing with resource greedy projects. You should be able to produce new content and modify the existing enquiries without outside help. Your solution should serve your business needs without every user having a degree in information technology. You should be empowered to answer your business related questions, not your IT department or some outside consultant.
IMPLEMENTING THE NEW PROCESS IS DIFFICULT
Implementing the solution throughout the organization has been incomplete and the new solution is left on the shelf.
Even if Artificial Intelligence and machine learning are hot topics, they are not going to subtract the human from the equation. The solution should involve your whole team and support discussion and communication. You can ditch unnecessary emails and increase awareness as people share discoveries instead of barricading behind individual job descriptions and numbers.
The organization should create a management culture where analytics isn’t just reports and lists, but instead discussion, decision making and follow-through based on correct information.
Author: Simo Vesterinen, CEO of Visionbay Solutions Oy