152 - 10 Reasons Not to Get Professional UX Design Help for Your Enterprise AI or SAAS Analytics Product
Sep 17, 2024
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Exploring the potential downsides of hiring professional UX design services for enterprise AI and SaaS analytics products, the discussion reframes misconceptions around design needs. It delves into the complexities of crafting user experiences without oversimplifying intricate functionalities. Concerns about the impact of GenAI and the value of emotional responses in design are also addressed. Ultimately, the conversation emphasizes the necessity of genuine user insights and the importance of building trust in AI solutions.
Investing in comprehensive UX design is crucial for long-term benefits, as opposed to merely focusing on short-term gains and quick tweaks.
Overconfidence in internal design capabilities often leads to missed user needs, necessitating the involvement of professional designers for effective and intuitive solutions.
Despite advancements in AI, thoughtful design remains essential for creating user-friendly interfaces that align with complex analytics demands and build user trust.
Deep dives
The Importance of User Experience Design
Investing in user experience (UX) and user interface (UI) design is critical for analytics and AI products, despite some misconceptions about its value. Many companies prioritize short-term wins with small tweaks rather than investing in comprehensive design work that can yield substantial benefits in the long run. While quick adjustments might satisfy immediate needs, the sunk costs of doing it right the first time can often lead to greater product debt and complexities. Thus, organizations focusing solely on low-hanging fruit should reconsider their strategy and investment in robust UX design.
Skepticism Toward Self-Perceived Design Skills
A common pitfall for teams is overestimating their own design capabilities and underappreciating the complexities of UX work. Even experienced product managers may feel confident in their design taste, but achieving effective and intuitive design often requires a deeper understanding of user needs and behaviors. This overconfidence can lead to misguided assumptions about what simple solutions can achieve, ultimately resulting in user experiences that may fall flat. Engaging professional designers can bring expertise and empathy to the design process that is challenging to replicate internally.
The Misconception of AI Solving UX Issues
Many believe that advancements in generative AI and large language models (LLMs) can alleviate design challenges, leading to the assumption that design expertise is unnecessary. However, the reality is that even with sophisticated AI capabilities, creating a user-friendly interface and building trust requires thoughtful design. Simply relying on AI to generate answers can miss the mark if users cannot easily interpret or feel confident in the feedback received. Therefore, investing in design is crucial to ensure that the user experience aligns with the complex demands of analytics solutions.
Complex Tools Require Thoughtful Design
Technical users may demand raw data access and view simplification as a threat to their complex tools. This perspective underlines the idea that good UX should meet users' sophisticated needs without dumbing down functionalities. Effective design is about aligning the product with user tasks rather than merely reducing complexity. Recognizing that users have unmet needs allows for opportunities to enhance the user experience, making thoughtful design even more vital.
The Agile Process and Design Investment
Organizations following agile methodologies often believe that iterations suffice for achieving optimal user experience, which can lead to neglecting the importance of initial design investment. Agile processes can become output-driven, prioritizing feature delivery over meaningful user experience enhancements that contribute to business outcomes. Unless teams have robust mechanisms to gather user feedback and measure the impact of design changes, relying solely on iterative processes may not yield the desired results. Hence, investing in design expertise remains essential for ensuring that user needs are accurately addressed throughout the development cycle.
In today’s episode, I’m going to perhaps work myself out of some consulting engagements, but hey, that’s ok! True consulting is about service—not PPT decks with strategies and tiers of people attached to rate cards. Specifically today, I decided to reframe a topic and approach it from the opposite/negative side. So, instead of telling you when the right time is to get UX design help for your enterprise SAAS analytics or AI product(s), today I’m going to tell you when you should NOT get help!
Reframing this was really fun and made me think a lot as I recorded the episode. Some of these reasons aren’t necessarily representative of what I believe, but rather what I’ve heard from clients and prospects over 25 years—what they believe. For each of these, I’m also giving a counterargument, so hopefully, you get both sides of the coin.
Finally, analytical thinkers, especially data product managers it seems, often want to quantify all forms of value they produce in hard monetary units—and so in this episode, I’m also going to talk about other forms of value that products can create that are worth paying for—and how mushy things like “feelings” might just come into play ;-) Ready?
Highlights/ Skip to:
(1:52) Going for short, easy wins
(4:29) When you think you have good design sense/taste
(7:09) The impending changes coming with GenAI
(11:27) Concerns about "dumbing down" or oversimplifying technical analytics solutions that need to be powerful and flexible
(15:36) Agile and process FTW?
(18:59) UX design for and with platform products
(21:14) The risk of involving designers who don’t understand data, analytics, AI, or your complex domain considerations
(30:09) Designing after the ML models have been trained—and it’s too late to go back
(34:59) Not tapping professional design help when your user base is small , and you have routine access and exposure to them
(40:01) Explaining the value of UX design investments to your stakeholders when you don’t 100% control the budget or decisions
Quotes from Today’s Episode
“It is true that most impactful design often creates more product and engineering work because humans are messy. While there sometimes are these magic, small GUI-type changes that have big impact downstream, the big picture value of UX can be lost if you’re simply assigning low-level GUI improvement tasks and hoping to see a big product win. It always comes back to the game you’re playing inside your team: are you working to produce UX and business outcomes or shipping outputs on time? ” (3:18)
“If you’re building something that needs to generate revenue, there has to be a sense of trust and belief in the solution. We’ve all seen the challenges of this with LLMs. [when] you’re unable to get it to respond in a way that makes you feel confident that it understood the query to begin with. And then you start to have all these questions about, ‘Is the answer not in there,’ or ‘Am I not prompting it correctly?’ If you think that most of this is just an technical data science problem, then don’t bother to invest in UX design work… ” (9:52)
“Design is about, at a minimum, making it useful and usable, if not delightful. In order to do that, we need to understand the people that are going to use it. What would an improvement to this person’s life look like? Simplifying and dumbing things down is not always the answer. There are tools and solutions that need to be complex, flexible, and/or provide a lot of power – especially in an enterprise context. Working with a designer who solely insists on simplifying everything at all costs regardless of your stated business outcome goals is a red flag—and a reason not to invest in UX design—at least with them!“ (12:28)“I think what an analytics product manager [or] an AI product manager needs to accept is there are other ways to measure the value of UX design’s contribution to your product and to your organization. Let’s say that you have a mission-critical internal data product, it’s used by the most senior executives in the organization, and you and your team made their day, or their month, or their quarter. You saved their job. You made them feel like a hero. What is the value of giving them that experience and making them feel like those things… What is that worth when a key customer or colleague feels like you have their back with this solution you created? Ideas that spread, win, and if these people are spreading your idea, your product, or your solution… there’s a lot of value in that.” (43:33)
“Let’s think about value in non-financial terms. Terms like feelings. We buy insurance all the time. We’re spending money on something that most likely will have zero economic value this year because we’re actually trying not to have to file claims. Yet this industry does very well because the feeling of security matters. That feeling is worth something to a lot of people. The value of feeling secure is something greater than whatever the cost of the insurance plan. If your solution can build feelings of confidence and security, what is that worth? Does “hard to measure precisely” necessarily mean “low value?” (47:26)
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