Getting started with analytics can be a large undertaking for any organization. Adding to the marketing hype and confusing the rest of the business are an increasing number of buzzwords like big data, business intelligence, predictive analytics and the internet of things.
Additionally, the emerging technology is advancing at an unprecedented pace. It is no wonder organizations find it tough to comprehend what all of this means for their business. When organizations analyze the cost of the software, hardware and resources, an analytics project may appear too daunting.
According to a Gartner study, over 50% of analytics projects fail. When we truly break down all the components in an analytics project, it comes down to a risk-and-reward ratio.
The following five steps help lower the risk and raise the reward.
A new tool will immediately add cost before any value is achieved. Outgrow your current toolset as the program expands. Don’t ‘grow into’ a new toolset. Most analytics projects do not fail because of the technology, they fail due to a lack of vision, execution and talent. Many organizations will look immediately to a new technology to solve their analytical problems. If the data isn’t available or is inaccurate, you can’t analyze it. A new tool will not solve this problem.
Analytics projects fail because they are too big. Big projects lack a unified direction, suffer scope creep and have too many stakeholders. Think low cost and fast time to value.
Find an area in the organization that is suffering from a lack of insight. Focus on solving this one problem. Ideally, the data associated with the problem is accurate and complete. Solve the problem and show a positive return on investment.
When touting the quick win that the analytics resources accomplished, include a return on investment (ROI) calculation. If the ROI is positive, add this as a reporting metric for the group. Shift the organizational thought process from analytics being a cost to a revenue or profit center.
This can be a tough discussion to have.