Why Analytics Projects Fail – And It’s Not The Analytics!
Being in a highly technical, complex field it is easy to sometimes lose the ‘human aspect’ of the solutions we are developing. We focus on apply edge computing concepts, or whether a seasonality model works better for our predictive accuracy than some other approach. Don't get me wrong, these are all important activities.
However, in working with many firms in developing, deploying and supporting advanced analytics solutions, particularly in the domain of the Industrial IoT space, it’s often the people side that fails – not the technology.
How many times have you developed an amazing predictive analytics solution that your team is excited about, but it fails to get corporate funding? Or even worse, you develop a proof of concept, but the business unit responsible for deploying the solution never fully adopts or accepts the solution. What gives? The solution has been proven to work. It shows significant results. Why the hesitancy.
The reality is that most advanced analytics solutions have some impact on existing business processes. Whether it is replacing staff with an automated process, or gaining the trust in management that the decision making algorithms work – the bottom line is that it’s all about making sure the organization, the people, not only accept, but embrace the solution.
Here are some suggestions for helping to make this happen:
KISS-Keep It Simple Stupid. Yeah, it’s cool to be the ‘wizard in the room’, but the reality is, most people are pretty intimidated by the statistics and buzz words associated with advanced analytics. Keep it simple, they are already going to be impressed by your understanding of the subject area. Use as many examples as possible and try to avoid buzzwords or highly technical jargon.
Make It Relevant. Clearly articulate the reason why this has value. For the executive team, a clear use case with financial detail explain the value of the solution is critical. For the management team implementing this, before you ever pitch ‘the solution’, make sure you have spent time to really understand how this would impact them, what their needs are, and explaining how this will help them in their job or how the improvement in company performance will benefit them.
Get Buy In Early. Give everyone involved in implementing, using, or making decisions about the solution a chance to buy in by having a say on how it is designed, and how it will operate. If you wait until you have ‘completed’ the design, then you have to overcome resistance to change and inertia. No matter how good the solution is, folks typically don’t want to change. However, if you let them help you design the solution, they will buy-in to it as part of the process.
Clearly, there are a lot of things that can be done to help drive acceptance of your solution.
So my strong advice is – don’t think of just designing the solution and developing as the ‘project’. Half of the project is getting buy-in to the solution from your organization. Be prepared for this, plan for it, and embrace it!
Some opinions expressed in this article may be those of a guest author and not necessarily Analytikus. Staff authors are listed in https://www.analyticbridge.datasciencecentral.com/profiles/blogs/why-analytics-projects-fail-and-it-s-not-the-analytics