Even the best of clients have all sorts of data issues. It is actually quite surprising how this issue runs across industries, company sizes and types of ownership. So, what should we do about it? Let’s talk through a client example and the successful path forward.
Although quite technical and successful in designing manual processes, this client had a plethora of data issues. Item attributes and customer data was inconsistent. Data anomalies were rampant. And the list goes on. Although not ideal, it wouldn’t matter if it didn’t negatively impact employee morale, the customer experience or profitability. However, they had hit the wall in terms of frustration, scalability and predictability.
It definitely isn’t as simple as saying “fix your data issues”. In fact, we started by actively not focusing on this gorilla in the room. Instead, we looked for improvement opportunities. We started by reviewing workflows, understanding processes and asking about desired outcomes while finding out what the experts of each process step thought the bottlenecks were and asked about ideas for improvement. After seeing how the process steps came together and taking ideas from multiple clients and process owners, we designed a path forward. This roadmap would take tangible steps forward to achieve immediate improvement while laying the groundwork for long-term transformation.
From a data point-of-view, we tackled a small subset of data related to an area of key importance. This enabled us to find small wins on the roadmap to a digital transformation. For example, we identified a small subset of products and customers to focus on for data integrity, forecasting and predictive analytics. More importantly, we could gain a series of incremental improvements along the way while building a solid infrastructure to support scalable, profitable growth.