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Is the value of your enterprise analytics SAAS or AI product not obvious through it’s UI/UX? Got the data and ML models right...but user adoption of your dashboards and UI isn’t what you hoped it would be? While it is easier than ever to create AI and analytics solutions from a technology perspective, do you find as a founder or product leader that getting users to use and buyers to buy seems harder than it should be? If you lead an internal enterprise data team, have you heard that a ”data product” approach can help—but you’re concerned it’s all hype? My name is Brian T. O’Neill, and on Experiencing Data—one of the top 2% of podcasts in the world—I share the stories of leaders who are leveraging product and UX design to make SAAS analytics, AI applications, and internal data products indispensable to their customers. After all, you can’t create business value with data if the humans in the loop can’t or won’t use your solutions. Every 2 weeks, I release interviews with experts and impressive people I’ve met who are doing interesting work at the intersection of enterprise software product management, UX design, AI and analytics—work that you need to hear about and from whom I hope you can borrow strategies. I also occasionally record solo episodes on applying UI/UX design strategies to data products—so you and your team can unlock financial value by making your users’ and customers’ lives better. Hashtag: #ExperiencingData. JOIN MY INSIGHTS LIST FOR 1-PAGE EPISODE SUMMARIES, TRANSCRIPTS, AND FREE UX STRATEGY TIPS https://designingforanalytics.com/ed ABOUT THE HOST, BRIAN T. O’NEILL: https://designingforanalytics.com/bio/
Episodes
Tuesday Jun 18, 2019
Tuesday Jun 18, 2019
Bill Bither, CEO and Co-Founder of MachineMetrics, is a serial software entrepreneur and a manufacturing technology leader. He founded and bootstrapped Atalasoft to image-enable web applications which led to a successful exit in 2011 to Kofax. In 2014, he co-founded MachineMetrics to bring visibility and predictability to the manufacturing floor with an Industrial IoT analytics platform that collects data from machines. This data is used to benchmark performance, drive efficiency, improve equipment uptime, and enable automation.
Today, join us as we discuss the various opportunities and challenges in the complex world of industrial IoT and manufacturing. Bill and I discuss the importance of visualizations and its relationship to improving efficiency in manufacturing, how talking to machine operators help add context to analytics data and even inform UI/UX decisions, as well as how MachineMetrics goes about making the telemetry from these machines useful to the operators.
We also covered:
- How improving a customer’s visibility into CNC machines helped reveal accurate utilization rates and improved efficiency
- How simple visualizations make a tangible difference in operational performance
- Bill’s model for the 4 different phases of analytics
- Descriptive
- Diagnostic
- Predictive
- Prescriptive
- Mistakes Bill learned early on about product dev in the IIoT analytics space
- What Bill learned from talking to customers that ended up identifying a major design flaw his team wasn’t aware of
- The value you can glean from talking to customers
- MachineWorks’ challenges with finding their market fit and aligning their product around customer’s needs
- How MachineMetrics has learned to simplify the customer’s analytics experience
Resources and Links
Quotes from Today’s Episode
“We have so much data, but the piece that really adds enormous value is human feedback.” — Bill
“Simplicity is really hard. It takes time because it requires empathy and it requires going in and really getting into the head or the life of the person that’s gonna use your tool. You have to understand what’s it like being on a shop floor running eight different CNC machines. If you’ve never talked to someone, it’s really hard to empathize with them.” — Brian
“In all the work that we do, in adding more intelligence to the product, it’s just making the experience simpler and simpler.” — Bill
“You don’t have to go in and do great research; you can go in and just start doing research and learn on the way. It’s like going to the gym. They always tell you, ‘It doesn’t matter what exercise you do, just go and start.’ …then you can always get better at making your workout optimal.” — Brian
“It’s really valuable to have routine visits with customers, because you just don’t know what else might be going on.” — Brian
“The real value of the research is asking ‘why’ and ‘how,’ and getting to the root problem. That’s the insight you want. Customers may have some good design ideas, but most customers aren’t designers. … Our job is to give people what they need.” — Brian
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