Support Insights
For once “Have Watson do it” didn’t doom the project
“If I had an hour to solve a problem I'd spend 55 minutes thinking about the problem and 5 minutes thinking about solutions.”
- Albert Einstein
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The competition to provide low-cost break-fix support for large companies’ IT infrastructure has caused IT support outsourcing to become increasingly commoditized. To find a competitive advantage, IBM was willing to invest in machine learning that would allow it to stop competing on price and speed, and instead make the unique promise that outages would be predicted and prevented, not just restored.
In order to make sure they didn’t make the same mistakes as many other Watson-enabled solutions, they asked me and another design leader, to lead the team through its initial release. -
Having facilitated over 100 envisioning workshops, I knew that “Watson does it” is the single least productive big idea to come out of an ideation session. Could we get the business and engineering teams to focus on real user needs, not expensive tech-first solutions?
Key systems that our clients used were being sunset within the year. We would need to replace those systems with something groundbreaking in less than a year?
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We created a robust research program that allowed us to learn how to best serve our users. After doing dozens of interviews and workshops with a range of IT roles at our client companies, we were able to quickly develop and test prototypes. In under nine months, a new digital support AIOps platform was providing over 1000 clients critical failure alerts, before they occurred.
As design educators and change agents, our first goal was to establish a new way of working that was user-centered, and restlessly reinventive. We would have an aggressive timeline, but we would invest a large portion of this time on generative user research and co-creation with our clients.
We established, through working with our on-the ground support teams and IBM’s own mature IT teams, a broad set of user personas for whom a preventative alert system might be beneficial. But we knew that getting direct access to the actual users of our products is sometimes a project in itself, and we treated it as such.
We designed every interaction to be bold but professional, so that our account teams and our clients understood that the project represents an important new way of working together.
Once we had strong relationships with people from each of our four main persona groups, we hosted virtual workshops that used traditional and novel design thinking activities to determine what specific needs our MVP would solve for.
Having an active sponsor user team allowed us to put concepts in front of our users, then story boards and low fidelity mockups in record time.
As the development team went to work on the MVP, we began to look at the supporting experiences, like discovery and first use, that we would have to design for.
Impact
IBM Support Insights has grown to over 1200 onboarded clients, and has become the centerpiece of IBM’s AIOps Strategy.
Bundling Support Insights with other premium IT support services helped increase their gross profit by 6%.
Support Insights has set a new standard for elegant design is the centerpiece of IBM's AIops strategy going forward.
