Analytics projects, especially ones involving prediction and optimization, can bring a ton of value to the organization. Better understanding, reduced costs, increased yields, less waste, higher rates and a plethora of benefits that can give very large returns on investment.
But, that hard work can be torpedoed easily. So, somewhat “tongue-in-cheek”, I give you 7 ways to destroy your analytics project:
- Create Excessive Expectations
You don’t even have to let your exuberance run like the wind. Just promise nearly perfect results. When your project comes to an end and even though you may have delivered very good results with good benefits, it won’t matter, you didn’t achieve the expectations and management pulls the plug.
- Don’t Listen to the User
Do the project just for the fun of playing with the technology. Skip talking to the persons who are actually going to use the results. When you have the best whiz-bang technical solution that nobody wants, watch the system wilt like an un-watered flower.
- Don’t Target a Business Objective
Don’t worry, your project will be great for the company, somehow, right? Just do it, show the results and wonder why no funding comes forth to continue on.
- Have a Central Group Think They Can Do Better or Cheaper
OK, you’ve done all the right things, you’ve targeted business objectives, have the full buy-in of the end users, you have a great team delivering a fantastic solution and have documented value to the organization. Everyone is happy. Then the phone rings. It’s the central analytics team at headquarters. They want to see what you’ve done! Great! They want to adopt it corporately! Not so fast. They want to see what you did so they can do it themselves, their way. They shut you down by talking to their senior management to tell your senior management to stop and implement THEIR “corporate” solution, which fails and no one ends up with anything.
- Reassign or Retire The Champion
New innovative solutions are almost always driven by a “champion”, someone who understands the business need and the technology, a true believer that drives the project home. During or at the end of the project, transfer them to Albania or Alaska or Angola, maybe have them retire, and then watch the project die.
- Don’t Plan for Exceptions
The world is perfect. There is no such thing as bad data, or situations you were unaware of. Don’t worry about it. When the first glitch comes along watch the system fail.
- Don’t Go After the Plum
In some cases prediction of something comes before being able to optimize it. Optimization is where the real money is. So, as a “safe” first step, do prediction, and do and do and do prediction. Let the prediction project become the primary focus and eventually optimization becomes a distant thought. When the prediction part does not deliver the optimization returns on investment, terminate the project. (Yes, this happens!)
This was in a bit of humor, but unfortunately these things happen, more than we think or want.
Over to You
Do you, or did you ever have a good project go bad? What was YOUR experience? I’d love to hear it.