Identify the Benefits of Data Mining
It's pretty easy to justify the mining efforts on the promise of benefits today because there are so many success stories floating out there. The typical benefits that keep repeating include improved decision making, improved risk mitigation, improved planning, competitive advantage, cost reduction, customer acquisition, customer loyalty, new revenue streams, and new product/service development. The crucial step here is to find the benefits that will resound in your organization and situation. These days organizations are dealing with a multitude of challenges from plagues to politics. It is always a win to save costs, but there has to be more to it to create a compound set of appropriate benefits needed to justify mining efforts.
Scoping Efforts Properly Delivers Better Results
While we all believe that data mining has the potential to improve and even transform organizations, the amount of data to mine is growing by the second and the number of advancements in making data smart is expanding. It's not difficult to understand that the majority of organizations are struggling to find the right strategy or solution. The first step is to discover where there is significant potential like miners do by drilling boreholes to discover the potential in the ground. That means organizations will have to sample areas of data that promise potential. To that end, many organizations start with process minging because it promises cost and time savings that often improve customer experiences leveraging smaller scopes. For those organizations that wanted an outside-in perspective, starting with customer journeys and large scoped processes that cross system boundaries have been quite successful.
Incremental Learning is Essential to Continued Success
Starting small and expanding as success allows seems to be the most common model for mining. What is really popular at the moment is to use mining to find opportunities for more automation. Savvy organizations will look at adjacent systems, organizational units, and contexts. Feedback loops and iteration will teach the best lessons for mining results. Alternative visualization techniques such as timelines, animation, and limits do also help the learning process. Some organizations will also combine the visualization with discrete simulation to test alternative outcomes.
If you are not practicing focused data mining and looking for productive patterns in your ever-growing data inventory, you are missing many opportunities. As successes emerge, the more savvy organizations are looking to widen their scopes and using approaches that cut through the jungle of their organization. Mining is here to stay and brings a valuable set of methods, techniques, and tools to leverage for organizations looking to thrive under all conditions.