Three Pitfalls to Avoid When Starting Out in Predictive Analytics
After two years of developing Photizo’s Advanced Analytics business, I thought it would be good to share a few of the key learnings we have observed during our past engagements. Here are three key ways to avoid pitfalls during the development and deployment of advanced analytics solutions.
- Let the use case be your guide – the single biggest piece of advice I can give is to begin the process with identifying and quantifying a use case. Defining a use case involves identifying and clearly articulating the problem you are trying to solve and building a financial model for the expected impact of the solution. This is essential for several reasons. First, it guides the development team towards a clear goal as they are assessing the data and building the predictive models. Secondly, it helps to build consensus within an organization helping to ensure there is alignment on what is to be achieved. If the goal is not clear, there’s no telling where the path will lead.
- Start small scale fast – Often companies are looking for quick wins and evidence that advanced analytics can drive the intended business results. The best way we have found to do this is by focusing on a proof of concept. Once the use case is clearly defined, the next step is to clearly lay out the path to creating a small solution that proves the business case. This involves mapping out the data flow, identifying where sensors and/or edge computing is necessary, and building the predictive model and data visualization elements. This enables you to show a quick success case and begin building the path to a larger implementation.
- Change management is key – For advanced analytics solutions to reach their full potential, they must be used in business decision making. If advanced analytics solutions are built, but the business model doesn’t change to take advantage of the new solution, very little benefit will be realized. One example we have seen is training senior management to make decisions based on data. While this seems very straight forward, humans are not logical creatures and we inherently resist change. Fully realizing the benefits of advanced analytics requires more than just technology skills, and the consulting and change management skills must not be overlooked.
As you look at implementing advanced analytics in your business, make sure to plan ahead to ensure you don’t fall into the pitfalls above. If you are looking for assistance in designing, developing or deploying an advanced analytics solution in your business, feel free to contact us at email@example.com