UI/UX Articles and Interesting Tidbits of the Week
July//28//2023
Here are some interesting finds on UI/UX of the week!
1.
Upskilling Opportunities. Very pertinent and relevant article published on The Next Web, and authored by Dara Flynn, on the topic of upskilling that is needed by most professionals in order to maintain their relevance in the job market. This article highlights this pressing issue not only as a result of the progressive automation of certain roles, but also as a result of what AI is bringing to most industries. And while the extent of what AI can deliver is still undetermined, the article does provide some recommendations on where to focus in terms of upskilling (though it is highly focused on development roles). Worth reading and reflecting on. Highlight of the article includes:
“Upskilling is a core practice in a dynamic jobs market, and many employers are advertising in-house skills programmes as part of their employee incentive packages. The penny has dropped: keeping the best talent in the age of AI means helping them to self-improve. Employee training to increase retention is preferable in the long term to worker turnover and costly recruitment drives. Getting paid to be better at your job, while on the job, is now up there with share options, remote working, and diversity policies, as far as talent is concerned.”
2.
Why Analytics are Relevant in Challenging Economic Times. Interesting article hailing from the Pendo Blog, and author Pippa Barnes on the value brought forth by analytics, particularly when the macro-economic context in which everyone operates isn’t as robust as expected. While the article of course is a push for Pendo’s product, it nonetheless brings noteworthy attention to a few aspects, namely: analytics and metrics allow for business strategists on various levels of hierarchy within an organization, to better understand performance, adoption and troublesome aspects of a solution. Secondly it also enables for iterative cycles to be put into motion based on demonstrable evidence, and thirdly, there’s a layer of competitive advantage that is unlocked as a result of this type of data (what is the data telling informing teams, what are customers revealing). Worth reading through if anything for the data statements that it makes. Highlight of the article includes:
“With product analytics, product teams can better communicate with the company’s finance team (hello, CFO!) and understand the business the same way they do. Finance teams love product data because it allows them to identify areas of inefficiency and opportunities for cost consolidation. By analyzing data on product usage, customer behavior, and resource utilization, finance teams can pinpoint areas where costs could be recouped. For example, they can identify features that aren’t generating sufficient value, and pivot the human and monetary capital going into them to other areas of the product that do. Product data can also inform finance teams’ budgeting and forecasting processes — which is invaluable when it comes to planning investments and managing financial expectations (especially when a board or shareholders are involved).”
3.
UserTesting and AI. Interesting reflection on AI and its relationship with UX Teams and Research hailing from UserTesting’s blog, authored by Andy MacMillan and Ranjitha Kumar. Both authors emphasize how AI can become a powerful tool which enables storytelling and solutioning centered activities developed by UX Teams to further progress and become a resource which will even potentiate better solutions in the long run. They also emphasize time efficiencies, larger data sets become available, and generally speaking, providing more sources and materials with which to develop better solutions. The article also emphasizes UserTesting’s focus on data security and privacy, and how they’ll continue to evolve while integrating these developments. It’s an interesting perspective and statement from a market leader in the field of research. Highlight of the article includes:
“We envision AI empowering teams, expanding the scope of what they can accomplish by providing them with the tools to scale and mature their research practice, the time to focus on strategic work they enjoy, and the evidence-backed insights to make a stronger case for customer-centric decision-making. Through thoughtful AI implementation, we see AI elevating the role of UX teams — making them an even more integral, strategic partner within their organizations. We see AI-human collaboration where AI evolves from automating functions behind the scenes to a trusted assistant with which resource-strapped UX teams can interact through a natural language dialogue to facilitate every stage of the research lifecycle and generate higher-level customer insights. AI will accelerate and scale research by suggesting what to test, when to test, how to test, and who to test with. It holds the ability to process large volumes of data across videos, audio, written, design, and behavioral data — data that would have otherwise gone unused — at an unprecedented speed. Processing data beyond human capacity will identify patterns, correlations, and anomalies to help teams make discoveries and access a new breed of high-value insights generated from multiple data streams.”
