The myth of the “low hanging fruit”

TL;DR — Teams rush to build ‘low hanging fruit’, features they think will benefit users but also make them feel their achieving things. However, this is a mistaken belief that outputs equate to outcomes. But its almost as fast if you focus on the areas of highest value to your users and start by immediately delivering a small slice of that. You’ll end up delivering software just as quickly, which is a first step in making something truly great.

Photo by 44 Degrees North on Unsplash

This was originally a presentation I made to several design teams, describing the benefit of moving away from delivering product features and towards addressing the most impactful user issues that we were finding in our research. It was a reaction to managing several design teams that often had their goal post’s moved during the year. I felt there were growing frustrations from teams that were struggling to make things they felt were valuable.

In this changeable environment, they looked for ways they could quickly feel the glow of satisfaction when progress is being achieved. Combined with a changeable company strategy, teams looked for ‘quick wins’ to help prove efficacy (to both themselves and others in the organisation) in the new space they were told to operate in. This post was a response to delivering on the ‘low hanging [feature] fruit’. My point was that to be ‘Quick’ doesn’t mean you just start with the easy, obvious things, that are plucked with no strategic value.

This was never meant as a “this is the only way to do it” polemic. I was a design manager working across several multi-disciplinary product teams and wanted to communicate a supportive message that doing high-value work is what we’re here to do. That I was here to help move towards identifying areas of greatest opportunity and then do work to address that.

Note: Names here are changed to protect the innocent. By that, I mean companies and teams I have worked with.

Features over value

Designing features is a common way that many software teams think about what they need to make. In many cases, features appear like a 1:1 match for an identified user need. In some cases it’s a literal response: User says this, we build this. However, this approach is hit and miss and also is in opposition to a systematic way that consistently produces solid products over a long period. Yes, it can work, but will the team produce and deliver value that builds on or creates sustained changes in user behaviour? Over time?

Feature focus tends to produce software products that are poorly conceived (doesn’t match users needs well), lack continuity (poor experience) and most importantly, don’t address fundamental behaviours that make our product and services useful and valuable to our users.

It often reflects organisations that are racing to deliver, that prioritises ‘shipping’ over ‘shipping value’ and measures their output through metrics that reflect activity (burn downs) rather than outcomes that reflect changes in user behaviour (behavioural metrics). I am not saying there is not a space for any of that, but for the maturity of the organisation we were in, I felt that this was not the place.

So….another way to look at this is to reframe the issue from the product perspective and ask the question: how will we know we’re doing a good job?

This is how we framed it:

Our products are loved when they continually and consistently fulfil the high-value need(s) of our users. We will know when we’re succeeding at this when we see a corresponding change in user behaviour.

Value and Outcomes

At this point, it’s worth talking about what I mean by value and outcome. These key terms describe not only the benefit of what you’re making but the change in user behaviour that occurs. Firstly, value, in this sense, is the scale of a (potentially unmet) behavioural need in our users. At my last company, Babylon Health, we knew that reducing the time that clinicians spent entering data into the EHR took time and attention away from their patients. It effectively reduced their effectiveness as clinicians and reducing that clerical burden is high-value for both clinicians and patients.

An Outcome is a change in user behaviour that we know drives business results. This definition is taken from ‘Outcomes over Outputs’, and stresses the symbiotic relationship between the organisational benefit that comes from changes in user behaviour that the products or service creates that change. An outcome, using the Babylon example, would be a reduction in time spent entering clinical notes into the electronic health record. The hypothesis here is that reduced time spent entering data meant more time spent engaging and understanding their patients.

At Babylon, we spent a lot of time mapping out these outcomes as a way of understanding what are the behaviours we want to change and what behaviours will we see that will help us know we’re on the right path. We looked to reduce time spent at the keyboard, to improve data entry tools and use AI and NLP to take over the clerical burden of a consultation.

Mapping areas of value

So instead of just continually adding features to our product or service, we should try and reframe the problem so we’re focused on areas of opportunity. The question is not ‘let’s add this feature’ (to a product rammed with features) it’s more ‘let’s find areas where we think we can add value/change behaviour’.

This is a reframing of the question, from ‘what should we build next?’ to ‘what problem should we try to solve?’. It’s a subtle difference in approach and in a world of making software, its easy to get them mixed up as you’re still delivering software. The difference is really an area of opportunity could have many solutions, often delivered in combination, that addresses a behavioural need…and sometimes could also not be software and located anywhere along the value chain. Whereas a feature tends to be viewed as a chunk of code that drives an isolated benefit.

So…What we define as ‘areas of opportunity’ typically emerge through our generative research and are formed as a result of deep understanding of our users, user behaviour and the problem space we are working in.

We tend to identify areas of opportunity or value within the problem space we are working. Sometimes they are so large, that can fill the entire problem space.

Often within a problem space, teams may identify many areas of opportunity and these areas even over-lap.

This is where continuous generative research identifies many of these areas of opportunity. Part of a team’s research activity is to constantly define, refine and add colour to these areas. This upward curve of understanding also highlights the behaviours around this opportunity we want to change. Teresa Torres refers to this as continuous discovery, an approach that looks to consistently identify areas of high value for users and fold that knowledge back into the product design process.

I can’t stress enough how important the nuanced view that emerges through continual research, helps create sublime products. I also can’t stress how important it is for design management/leadership to help give the space for teams to do this.

A bit about mapping and low hanging fruit

As hinted at earlier, The thing is mapping features and mapping areas of opportunity, is that they can look pretty similar.

When looking at features, a filter of effort and impact can be used to rank each one. Especially in high delivery pressure environments, teams are often asking themselves ‘what can do straight away that we think will deliver value’ and in a feature-focus world, it’s easy to understand why low effort tasks tend to get higher priority. It’s probably the easiest way teams can show efficacy and impact.

Low hanging fruit — the name describes features that exist in the bottom half of the diagram, occupying both of the ‘low effort’ quadrants

The diagram describes the situation of the low-hanging fruit. Effectively, this is the bottom half of the diagram. These are features that are low-to-high value that take the least amount of effort to deliver. The misconception is that picking the features in the bottom half of this map is what teams should prioritise. It makes sense, on some levels you’re delivering immediate value to users. It’s just that often, this value is often too small to make a wholescale and enduring behavioural change. Furthermore, it is likely to be poorly orchestrated, creating a fragment product experience. Worst of all, its equates outputs with outcomes and is usually done to assuage the needs of stakeholders in other parts of the organisation.

Secondly, this is hit and miss. There is no strategic approach here as there is no identification of value or of any user behaviour(s) you’re looking to change. We’re making stuff blindly hoping that things improve. Ironically teams could deliver all of these features but still not make zero substantial improvements for their users.

Why do teams do this? Lots of reasons..a few that sprang to mind include Tight deadlines, specific ‘deliverables’ have been promised upfront, KPI’s that reframed to deliver a feature, not an outcome, and often someone in the org has sold something and the teams need to fulfil that promise.

Mapping Opportunities

So what happens if you map areas of opportunity across the same two-axis? It yields similar results.

However, unlike the areas dominated by ‘low hanging fruit,’ we should aim to build what we think are the areas of the highest value. It is in these areas that are most likely to yield remarkable products, products that exist in a different space and solve real user problems.

Ideally, this would be the top-right corner, areas that we believe are high value and high effort. As a friend said to me “If it was easy, everyone would be doing it!” @KarlBunyan

So we still ask the question: How can we deliver value to our users as fast as possible? And also, how can make sure we’re making the biggest impact? Remember the Agile manifesto has as a key principle that “Our highest priority is to satisfy the customer through early and continuous delivery of valuable software”.

But as I mentioned earlier, opportunities are sometimes too large in themselves. In this case, I pushed for teams to break these down (often through hypothesis generation) into more granular parts that they can deliver. Alongside this, they should cultivate a diligent focus on the outcomes you want to drive, so you know you are adding value (metrics).

Build the smallest slice of your biggest opportunities

This approach advocates building the smallest version of that first…and then keep going. So whereas ‘low hanging fruit’ represents a feature that’s easiest to deliver, looking towards outcomes and breaking them down, we seek to deliver the easiest part of what we think is the highest value. Ironically, we can almost do this at the same speed as delivering a feature classified as ‘low hanging fruit’

— —

There is always a cost in choosing to do work. By choosing one thing, you are making a choice not to do all the others. Teams can’t do everything and there is always the inverse to any action you take. That inverse is usually, what has the team chosen not to do?

Feature factories are such high-risk ventures, you can fluke success, even semi-sustained success, but if those features don’t work out, then you’ve invested time, usually at the expense of other things, like continuous discovery research.

This presentation aimed to show teams that speed of delivery does not sit in opposition to the delivery of value. Quickly choosing to deliver a feature is a product guess. And almost as quickly, one can find areas of value and look to break these down into smaller units that can be incrementally delivered. In product teams, out aim to deliver a change in outcomes (behaviours). By focusing on those and tackling these in a small, iterative way, we can deliver value as fast as tackling the ‘low hanging fruit’.

The UX Collective donates US$1 for each article published on our platform. This story contributed to Bay Area Black Designers: a professional development community for Black people who are digital designers and researchers in the San Francisco Bay Area. By joining together in community, members share inspiration, connection, peer mentorship, professional development, resources, feedback, support, and resilience. Silence against systemic racism is not an option. Build the design community you believe in.


The myth of the “low hanging fruit” was originally published in UX Collective on Medium, where people are continuing the conversation by highlighting and responding to this story.

from UX Collective – Medium https://uxdesign.cc/the-myth-of-the-low-hanging-fruit-5d5d8e6aa472?source=rss—-138adf9c44c—4

4 Ways to Apply Progressive Disclosure for Better Task Focus

Too many interfaces are guilty of displaying too much information at once. Not all that’s displayed is immediately relevant. Some information is temporarily irrelevant until users meet certain conditions. As such, you should conceal irrelevant info so users can focus on what’s relevant. Focusing on relevant info first allows them to complete tasks with fewer […]

The post 4 Ways to Apply Progressive Disclosure for Better Task Focus first appeared on UX Movement.

from UX Movement https://uxmovement.com/mobile/4-ways-to-apply-progressive-disclosure-for-better-task-focus/

Why car design education is broken

And how it could be fixed.

Matteo Licata Design
An old, not very good sketch from Yours Truly (picture from the Author)

Have you tried to Google “Behance Car Design Sketch” lately?

If you do, I bet your eyeballs will be assaulted by a barrage of out-of-proportion, often even out of perspective “vehicles” whose massive wheels and impossibly tiny glass fight for your attention, yet they all look the same. We have been fetishizing sketching to a point where we have lost sight of what matters, especially in the design academy’s world.

Over the past forty years, many automobile design courses have popped up in various locations worldwide, all seemingly with the same goal: to separate wealthy kids’ families from an atrociously large chunk of their cash in exchange for the “high education” needed to enter the field.

Except that’s not what they deliver, in most cases.

The proliferation of for-profit design schools flooded what has always been a small job market with bright, resourceful, and creative young professionals that sketch like demi-gods and make ace renders but know nothing of designing a vehicle. The result are hundreds of portfolios full of shiny eye-candy whose wheels don’t turn, suspensions have no travel, zero outward visibility.

As a former Pininfarina studio chief wisely stated in this brilliant Form Trends article

“You don’t pretend to beat Federer by simply hitting the ball hardest.”

Any game’s rules are there to be challenged, bent, or changed, but refusing to learn them in the first place gets you nowhere. Small wonder that “junior designers” ‘ market value has been driven below zero, as the supply of “sketch monkeys” vastly exceeds the little market demand for them.

I’ve seen things you wouldn’t believe…

…like plenty of talented young designers and supposedly “senior” ones, blissfully ignoring the most fundamental manufacturing realities because they’ve been issued a vehicle design diploma without ever see a technical drawing and a typical section.

I’ve seen 1:1 scale “epowood” (rigid resinous material used to make life-size vehicle mock-ups) models milled with bonnets whose shape could not be stamped, with shut-lines placed regardless of manufacturing technology,
Once, and this is one I’ll never forget, I’ve “taught” a smooth-talking, supposedly experienced colleague how to calculate the total diameter of a tire in millimeters from the sizes written on its sidewall. Enough said.

While the world certainly has worse problems than this, I feel for the families who get tricked into spending large sums on courses and masters whose titles sound impressive but offer little actual value in exchange.

Is there a solution?

Of course, there is. The formation of future automobile designers should be taken over by the automobile industry itself. Each year, according to their actual necessities, each manufacturer’s design studio should train a small number of thoroughly vetted candidates for free in exchange for a few years of a contractual commitment to the company once tuition will end.

I’m under no illusion it’ll ever be put into practice, but I believe it’s high time to have this discussion within the automobile design business.


Why car design education is broken was originally published in UX Collective on Medium, where people are continuing the conversation by highlighting and responding to this story.

from UX Collective – Medium https://uxdesign.cc/why-car-design-education-is-broken-7f27ca0216a8?source=rss—-138adf9c44c—4

Supernormal brings AI-powered asynchronous video messaging to remote teams


Zoom became one of this year’s big success stories for real-time video communications, as the rapid shift to remote work forced businesses to rethink their operations. Now a new startup is setting out to become the go-to platform for asynchronous video communications.

There is no shortage of non-real-time communication tools that allow globally distributed teams to check in with each other — email and Slack, for starters. But Supernormal is meshing video messaging with some nifty AI smarts to bring more engagement and utility to “async” interactions, where nuance and meaning isn’t lost amid a barrage of emojis. At a time when companies are increasingly committing to a distributed workforce spread across multiple time zones, Supernormal could carve itself a niche in a space awash with real-time video and voice tools.

“Supernormal is focused on helping teams communicate async and enabling key personas — engineers, designers, managers — to have creative time and choose when they want to consume or create team communication,” cofounder and CEO Colin Treseler told VentureBeat.

To aid its mission, the company today announced it has raised $2 million in a seed round of funding led by EQT Ventures, with support from several angel investors.

Supernormal (in the new normal)

Available via the web or through a desktop Mac app, Supernormal allows users to record company (or personal) announcements, presentations, greetings, or just about anything else. A separate function lets users record their screen in order to give presentations or product walkthroughs, with a little video avatar of the speaker embedded inside the screencast.

The app uses natural language processing (NLP) to instantly transcribe content and provide it as text beside the video while also extracting what it thinks are the three most interesting sentences from a transcript to suggest as caption summaries.

According to Treseler, the company develops its AI system “mostly” in-house. “We’ve built our own machine learning for detecting the most interesting sentences and have trained it on a massive corpus,” Treseler said.

Above: Supernormal: Screen recording with video message overlay

For businesses that sign up using their Slack or Google account credentials, Supernormal also automatically tags specific users in a company if their name is mentioned in the video, alerting the individual via Slack or Gmail. Presenters are notified whenever their team or intended audience has viewed the video, enabling them to follow up with any relevant communications.

Above: Supernormal: Text extraction and automatic alerts

Videos can also be embedded into digital properties such as websites, and dedicated links can be manually shared through any app. If they’re shared on Twitter, Slack, Facebook, or Microsoft Teams, they can be viewed inline directly on those platforms. Anywhere else, the user will have to click to view the video on the Supernormal platform itself.

There are other notable players in the space. San Francisco-based Loom is perhaps the most obvious example, having raised nearly $75 million in funding — including a $29 million tranche in the midst of the pandemic — from notable investors that include Sequoia Capital, Coatue, Kleiner Perkins, and Instagram’s founders. Founded in 2016, Loom has a bit of a head start and an impressive roster of clients, including Atlassian, Intercom, and HubSpot. It also offers additional smarts, such as a drawing tool, allowing presenters to illustrate or highlight specific items on their screen.

Prezi is doing some interesting things in the video presentation realm, though it’s aimed at a different market. Elsewhere, Slack is gearing up to launch a new Stories feature, which are essentially video-based status updates along the lines of Snapchat and Instagram’s consumer versions. Don’t be surprised if Microsoft follows suit with something similar for Teams.

Although it’s still early days for Supernormal, the startup’s use of AI to generate transcriptions, summaries, and smart alerts makes it worth keeping tabs on.

There are also potential use cases far beyond the enterprise, as Loom has demonstrated. For example, teachers struggling to get their entire class online for a live demo could simply record a short video-based presentation and send it by email for the students to view on their own time.

“Right now, we are seeing a lot of use by ‘prosumers,’ and we are open to education/nonprofits,” Treseler said. “Our core focus, however, will be on teams at the enterprise level.”

The story so far

As is increasingly the case with companies these days, Supernormal can’t be pinned to one location, with a workforce spanning the Americas and Europe. Treseler is currently based in Stockholm, Sweden, though he has served in various technical roles on both sides of the Atlantic over the past decade, including a two-year stint as a Facebook product manager in Menlo Park, California.

Treseler and his team started work on Supernormal in January, fortuitous timing given how global events would unfold in the months that followed. “When we started to create our solution, we didn’t expect every business to be relying on virtual communication this heavily,” Treseler said.

Supernormal was initially trying to be more of a catch-all video communication tool, but the company ultimately decided to go all-in on recorded video.

“We had live video in the initial product but felt that it wasn’t additive to the team experience and was not helping our core focus — shifting teams to becoming more asynchronous,” Treseler said.

Since its official launch in August, Supernormal claims it has been picked up by more than 400 teams, with workers at companies like Spotify and GitHub, and has seen “heavy engagement” across the spectrum, from SMBs to Fortune 500 companies.

The company is now working on native apps for Windows desktop and smartphones, along with one-click editing tools that enable users to remove pauses or specific words or sentences from transcripts. Treseler said the team is also exploring additional data reporting and analytics tools for customer-facing roles, such as sales and customer support.

In terms of pricing, it is entirely free for now, as the product is developed and iterated. But Supernormal will eventually adopt a SaaS model, with pricing to be determined. “We’ll eventually get to pricing that is considerably cheaper than the competitors in the space,” Treseler said.

With an extra $2 million in the bank, Treseler said the company will now double down on product development and expand its “fully remote team” around the world.

from VentureBeat https://venturebeat.com/2020/12/01/supernormal-brings-ai-powered-asynchronous-video-messaging-to-remote-teams/