Wait, I’m talking to a head of data management at a tech company? Why!? Well, today I'm joined by Malcolm Hawker to get his perspective around data products and what he’s seeing out in the wild as Head of Data Management at Profisee. Why Malcolm? Malcolm was a former head of product in prior roles, and for several years, I’ve enjoyed Malcolm’s musings on LinkedIn about the value of a product-oriented approach to ML and analytics. We had a chance to meet at CDOIQ in 2023 as well and he went on my “need to do an episode” list!

According to Malcom, empathy is the secret to addressing key UX questions that ensure adoption and business value. He also emphasizes the need for data experts to develop business skills so that they're seen as equals by their customers. During our chat, Malcolm stresses the benefits of a product- and customer-centric approach to data products and what data professionals can learn approaching problem solving with a product orientation.

• Malcolm’s definition of a data product (2:10)
• Understanding your customers’ needs is the first step toward quantifying the benefits of your data product (6:34)
• How product makers can gain access to users to build more successful products (11:36)
• Answering the UX question to get past the adoption stage and provide business value (16:03)
• Data experts must develop business expertise if they want to be seen as equals by potential customers (20:07)
• What people really mean by “data culture" (23:02)
• Malcolm’s data product journey and his changing perspective (32:05)
• Using empathy to provide a better UX in design and data (39:24)
• Avoiding the death of data science by becoming more product-driven (46:23)
• Where the majority of data professionals currently land on their view of product management for data products (48:15)

• “My definition of a data product is something that is built by a data and analytics team that solves a specific customer problem that the customer would otherwise be willing to pay for. That’s it.” - Malcolm Hawker (3:42)
• “You need to observe how your customer uses data to make better decisions, optimize a business process, or to mitigate business risk. You need to know how your customers operate at a very, very intimate level, arguably, as well as they know how their business processes operate.” - Malcolm Hawker (7:36)

• “So, be a problem solver. Be collaborative. Be somebody who is eager to help make your customers’ lives easier. You hear "no" when people think that you’re a burden. You start to hear more “yeses” when people think that you are actually invested in helping make their lives easier.” - Malcolm Hawker (12:42)

• “We [data professionals] put data on a pedestal. We develop this mindset that the data matters more—as much or maybe even more than the business processes, and that is not true. We would not exist if it were not for the business. Hard stop.” - Malcolm Hawker (17:07)

• “I hate to say it, I think a lot of this data stuff should kind of feel invisible in that way, too. It’s like this invisible ally that you’re not thinking about the dashboard; you just access the information as part of your natural workflow when you need insights on making a decision, or a status check that you’re on track with whatever your goal was. You’re not really going out of mode.” - Brian O’Neill (24:59)

• “But you know, data people are basically librarians. We want to put things into classifications that are logical and work forwards and backwards, right? And in the product world, sometimes they just don’t, where you can have something be a product and be a material to a subsequent product.” - Malcolm Hawker (37:57)

• “So, the broader point here is just more of a mindset shift. And you know, maybe these things aren’t necessarily a bad thing, but how do we become a little more product- and customer-driven so that we avoid situations where everybody thinks what we’re doing is a time waster?” - Malcolm Hawker (48:00)

• Profisee: https://profisee.com/
• LinkedIn: https://www.linkedin.com/in/malhawker/
• CDO Matters: https://profisee.com/cdo-matters-live-with-malcolm-hawker/

Welcome back! In today's solo episode, I share the top five struggles that enterprise SAAS leaders have in the analytics/insight/decision support space that most frequently leads them to think they have a UI/UX design problem that has to be addressed. A lot of today's episode will talk about "slow creep," unaddressed design problems that gradually build up over time and begin to impact both UX and your revenue negatively. I will also share 20 UI and UX design problems I often see (even if clients do not!) that, when left unaddressed, may create sales friction, adoption problems, churn, or unhappy end users. If you work at a software company or are directly monetizing an ML or analytical data product, this episode is for you!

Highlights/ Skip to

• I discuss how specific UI/UX design problems can significantly impact business performance (02:51)
• I discuss five common reasons why enterprise software leaders typically reach out for help (04:39)
• The 20 common symptoms I've observed in client engagements that indicate the need for professional UI/UX intervention or training (13:22)
• The dangers of adding too many features or customization and how it can overwhelm users (16:00)
• The issues of integrating AI into user interfaces and UXs without proper design thinking (30:08)
• I encourage listeners to apply the insights shared to improve their data products (48:02)

• “One of the problems with bad design is that some of it we can see and some of it we can't — unless you know what you're looking for." - Brian O’Neill (02:23)
• “Design is usually not top of mind for an enterprise software product, especially one in the machine learning and analytics space. However, if you have human users, even enterprise ones, their tolerance for bad software is much lower today than in the past.” Brian O’Neill - (13:04)
• “Early on when you're trying to get product market fit, you can't be everything for everyone. You need to be an A+ experience for the person you're trying to satisfy.” -Brian O’Neill (15:39)
• “Often when I see customization, it is mostly used as a crutch for not making real product strategy and design decisions.” - Brian O’Neill (16:04)
• "Customization of data and dashboard products may be more of a tax than a benefit. In the marketing copy, customization sounds like a benefit...until you actually go in and try to do it. It puts the mental effort to design a good solution on the user." - Brian O’Neill (16:26)
• “We need to think strategically when implementing Gen AI or just AI in general into the product UX because it won’t automatically help drive sales or increase business value.” - Brian O’Neill (20:50)
• “A lot of times our analytics and machine learning tools… are insight decision support products. They're supposed to be rooted in facts and data, but when it comes to designing these products, there's not a whole lot of data and facts that are actually informing the product design choices.” Brian O’Neill - (30:37)
• “If your IP is that special, but also complex, it needs the proper UI/UX design treatment so that the value can be surfaced in such a way someone is willing to pay for it if not also find it indispensable and delightful.” - Brian O’Neill (45:02)

• The (5) big reasons AI/ML and analytics product leaders invest in UI/UX design help: https://designingforanalytics.com/resources/the-5-big-reasons-ai-ml-and-analytics-product-leaders-invest-in-ui-ux-design-help/
• Subscribe for free insights on designing useful, high-value enterprise ML and analytical data products: https://designingforanalytics.com/list
• Access my free frameworks, guides, and additional reading for SAAS leaders on designing high-value ML and analytical data products: https://designingforanalytics.com/resources
• Need help getting your product’s design/UX on track—so you can see more sales, less churn, and higher user adoption? Schedule a free 60-minute Discovery Call with me and I’ll give you my read on your situation and my recommendations to get ahead:https://designingforanalytics.com/services/