How can artificial intelligence help organizations solve digital transformation challenges? Consider these examples - from customer service to resource optimization.
Digital transformation: Moving too quickly can slow you down
When creating a minimum viable product, don't be shortsighted. Look at the edges of your digital transformation and see where it interfaces with other systems, processes, and engagements
CIOs everywhere are feeling validated for any and all digital projects they pushed through before this global pandemic struck. But the reality is, most of us still have plenty of work ahead of us to digitally transform our businesses. There’s nothing wrong with taking a moment to say “whew, glad we fixed that before this all happened.”
A couple of years ago, we prioritized a digital transformation project that would improve the software procurement experience of our customers. We’re grateful that we started work on this project when we did, and we’ve learned many lessons along the way. Perhaps, most importantly, we learned the true importance of taking an end-to-end process view of the improvement we were trying to make.
When we started on this journey, we approached it as an Minimally Viable Product (MVP) – we aimed to deliver a solution quickly and then we’d expand on it. Working on something with an immediate value-driven outcome made it easy to focus on one piece, but we’d soon learn that this was short-sighted.
The importance of an end-to-end view
Our first focus in this transformation was to improve an initial interaction that a sales rep had with a customer: Creating a quote. This was a long and tedious process for both the customer and the sales rep, taking up to a week from start to getting a final approved quote to present to the customer. That was a big pain point, and we knew we could improve that interaction. Our solution was to implement a Configure, Price Quote (CPQ). The end result was great, customers could now receive quotes very quickly. The MVP was complete – we improved delivery speed by fully digitizing the process.
But it wasn’t long before we realized we had not taken an end-to-end view of the customer experience during the entire buying process. Yes, we had a great digital quote system, but there were other pain points for the customer downstream from that process – invoicing and payment.
We realized we were delivering an enhancement that was only beneficial to one specific part of our digital journey. We needed to address the order flow through the entire system. The improvement that we made was proving to be detrimental to the rest of the interactions that we wanted to digitize. In this instance delivering quick work was harmful because we did not take a holistic view.
Look at the edges of your digital transformation
Just because we had revamped our quoting process didn’t mean that we improved the customer engagement through to the finish. We needed to retrace our steps.
To fix this, we went through a detailed customer journey mapping exercise to revisit the processes and determine the places where we did not have a full view of the customer journey. Now we are revisiting those places in order to truly improve our customer interactions – from end to end.
We learned a couple of other lessons throughout this transformation. One, that the end-to-end customer journey is actually longer than we thought it was going to be. Two, when you create an MVP or an immediate value-driven outcome, you can’t be shortsighted. You must look at the edges of your digital transformation and see where it interfaces with other systems, processes, and engagements. Make sure those edges are not sharp so they don’t hurt the other pieces.
Another critical lesson is that your digital transformation can no longer wait. We are grateful we took on this project well before the COVID-19 pandemic and learned these lessons along the way. Now that we’ve found our rhythm, we’ll be more efficient than ever before.
[ Want answers to key digital transformation questions and lessons from top CIOs? Get our Digital transformation cheat sheet. ]