Four Key Tips for AI and Digital Transformation Analysis

These are more than just digital buzzwords or technical keywords. They are essential to understanding as technology continues to transform. From the feedback I’ve been receiving from my members, it’s […]

These are more than just digital buzzwords or technical keywords. They are essential to understanding as technology continues to transform. From the feedback I’ve been receiving from my members, it’s exciting to hear that many of you are venturing into projects that include digital transformation, intelligent automation, machine learning, and other artificial intelligence capabilities. I share your passion for these quasi-futuristic topics and how these capabilities deliver value to our end users now and in the future.

If these topics are not already on your horizon, set your sights on them now. Below I’ve listed some relevant tips to help integrate intelligent automation and digital analysis. I would love to hear your tips too. What are you doing to evolve the digital horizon?

1) Analyze the Customer Journey. Remove touch-points; maximize their time and effort!

Research and understand your customers’ experiences within your organization! Map out their journey. Find out how they achieve their goals and understand their triggers. With AI and digital transformation projects, look to remove touch points; the ones that don’t add value of course, and make sure you are not adding touchpoints. Time is a cherished commodity and we have to leverage the time we have to analyze the customer journey. As a result, it will save everyone time in the end.

2) Experiment and hypothesize.

These new technologies are complex, and thankfully, however, they can be quick to implement. To make sure you are on track with your ideas, build in “spikes” that serve as experiments to test the team’s big assumptions and hypotheses. Learn from these spikes. Make sure the team is not trying to perfect every idea and feature before learning. There is an old saying, don’t let the perfect get in the way of the good. This is key when keeping the process moving in the right direction.

3) Elicit user stories that are innovative!

A user story needs to provide business value. If you can’t provide business value without a few implementation steps being taken, then you can create tasks that, in aggregate, will result in the story being achieved. Stories are for the business and users. Tasks are for the implementation of the story.

Are your backlog refinement sessions boring? Use creative facilitation techniques and collaborative games to liven up the backlog refinement items will challenge the team to bring more innovation to backlog items. In conclusion, your leadership team expects innovation and don’t be the team that blames the big backlog at the end of the year. Change your backlog! Sometimes presenting things from a different angle changes and informs the user story.

4) Be agile and split stories from a user point of view.

Digital transformations and AI capabilities are definitely candidates for an agile approach. To make sure you are getting the most from agile, your team needs to know how to effectively split and slice user stories into small enough pieces that can be estimated and understood by the team. As a result this maintains user continuity and value focus for everyone. Each story has high-level acceptance criteria, which you can bring to a team, designers, and engineers to lead conversations and come up with a solution together. Bringing everyone that closer to implementation.