I distinguish the traditional change management we use for new enterprise applications such as ERP from the type we use for new technologies, where how to use them in daily operations is far less clear. When we implement a new enterprise system, we take great care to document every single change — big or small— resulting from the new system: a gap analysis of the as-is and to-be business process for each end user. I am surprised by how many people overlook that step. Not all users are equal, so it makes no sense to stick them in a room with an instructor for a day when a simple laminated user guide would suffice (or vice versa). Understanding the extent and degree of change for each employee and tailoring our rollout plans accordingly is the whole ball game.
We take the opposite change-management approach for technology we are just beginning to explore. Recently, we gave all our store managers iPads and told them, essentially, to have fun: no usage restrictions. We paired them up with someone in IT to help them get comfortable with the hardware and later to catalog how the technology was being used. Our decision to start with store managers — as opposed to some back-office function — was a deliberate one. How these folks work and interact with our customers is critical to the success of each store.
The lessons learned and the value these devices provide have a direct link to the company’s bottom line, which creates buy-in for future IT investment.
Sell information as a problem solver
Our goal is to provide predictive analytics beyond traditional performance reporting, which provides real insight for end users —less data and more meaning. Getting the business comfortable using this kind of business intelligence has little to do with technology and everything to do with understanding how to use the underlying data. In other words, what is the business problem worth solving and what information do we need to solve it? The role of IT in this case is one of analytics evangelist. We hear a lot of analytics success stories from external sources, and we vet these ideas for business impact and technology feasibility. Our business liaisons have a deep understanding of the business’s strategic objectives and will often pitch relevant analytics projects — with the support of our data warehouse team — to specific business areas.