Data, Design and Uncertainty

Balance 99/365 by Rafiq Sarlie

Originally published on github: Data, Design and Uncertainty

Something that’s been nagging at me is how much materials I’m reading (on data and design or data and storytelling) focus on working in an environment of certainty: goals are clear, missions are understood, time pressures seem nonexistent.

Data should serve, support and enable, so how do you navigate that minefield of uncertainty?

Let’s take a look at some approaches from people working in uncertain environments.

Understand the obstacles, yours and theirs

“Your competition is any and every obstacle your customers encounter along their journeys to solving the human, high-level problems your company exists to solve” says Tara-Nicholle Nelson in Obsess Over Your Customers, Not Your Rivals.

Nelson, who has a background in marketing, is reflecting on lessons learned from their approach at MyFitnessPal. The article is about rethinking competitor analysis but resonates for data people working with organisations where uncertainty is the main certainty.

Tara-Nicholle recommends using information (and data!) to discover roadblocks including:

  • user data
  • surveys
  • ethnographic research
  • online listening
  • subject matter experts
  • third-party data

Handily, the article includes some examples from MyFitnessPal to give some context on how to successful discover and remove roadblocks.

In my role as a consultant, I have some preliminary (but untested thoughts) on roadblock. The competition here for my customers is that they know my services (data + storytelling + design) are important but they can’t always articulate:

  • their goals for the project
  • how they’ll know the project has been successful
  • how the project supports their mission
  • their own data ecosystem and lack the means and framework for doing so (thanks to Ade for highlighting this)

Time (I believe) is another obstacle my customers face. Getting the right people in the room and giving the project enough resources and support to thrive can be a challenge. These are assumptions to test to help me understand my customers better and better help them get what they want out of our relationship.

It’s been useful to learn about obstacles, but I think there are more tricks of the trade, so let’s move on.

Ask the right questions to frame the problem

Asking the right questions to frame the problem is Ben Holliday’s recommendation. As a Chief Design Officer, the focus of this article is on designers, however, “framing the problem is something that teams really struggle with” resonates for anyone working with uncertainty.

Ben Holliday’s is to ask the questions:

  • Why are we doing this work? or What is our motivation for building this product or service?
  • Who are our users? or Who do we think would need to use this product or service?
  • What outcome will users get from this service? or What problem will it solve for people?
  • What outcome are we looking for? or What problem will it solve for our organisation?
  • What are our key metrics? or What do we need to measure against these outcomes?

Ben also covers how to ask the questions, starting from motivations then digging deeper into alignment and finally measuring success.

The questions could be even more useful with some examples and context: why am I asking this and what can we do once we know? I think of these situations like having a giant puzzle — answering each question gives you a piece to build up the picture so you can solve the puzzle. The questions are variations on those found in books on agile, design and user experience (UX), which may be why they are summarised.

The client is the expert, put them front and centre

“It’s not as sexy because it now places the client as the expert instead of the consultant” says Zeroth Labs. The Singapore-based start-up blends anthropology, data, and design with experimentation as a new approach to development consulting.

Like Tara-Nicholle Nelson, research is high on the agenda. Zeroth Labs’s describe their approach in Using anthropology, data and design thinking to disrupt development consulting as:

  • Conducting their own ethnographic research
  • Applying behavioral science
  • Testing, testing, testing

Essentially Zeroth Labs is understanding their customer’s customer using these methods to “build the capability for developing countries to make life better for citizens”. Another approach that could be useful for people working with developing companies.

Help your customers help themselves, by giving you advice

“Teach a man to fish and he’ll know how to fish — but get him to teach others how to fish, and he might actually get on with some damned fishing.” is Oliver Burkeman’s analysis of psychology research, Advice versus choice.

In Why it’s wise to give people advice, Oliver reflects that “giving advice reacquaints us with the knowledge we possess, which instills confidence, which motivates action”. Unfortunately, as the original research is behind a paywall, I can’t be certain if the interpretation is justified, but let’s go with it.

If it’s the case that asking our customers for advice about their areas of expertise will make them more bought into the project, build confidence and skills, then this sounds a lot like co-creation. One thing I can tentatively acknowledge is that as a specialists in data, my customers have the expertise, or can at least point me to the people who do.

In my projects, like the CRM and digital transformation project for Freedom Studios, I’ve encouraged a collaborative approach. We started with me leading the way, transitioned to me facilitating, then ended with my customers telling me what they needed. By the end of the project, we had clarity about the goals and capabilities of the CRM, new skills in the organisation and confidence in the system.

Co-creation works when customers are willing to put the time in and use the outputs outside the project. If whatever lessons you’ve learned are put aside after the project, it’s unlikely any changes will stick.

And in conclusion

Here’s what I learned today about approaches to getting clarity as a data professional working in uncertain environments:

  1. Understand the obstacles, yours and theirs
  2. Ask the right questions to frame the problem
  3. The customer is the expert, put them front and centre
  4. Facilitate them to advise you
  5. Collaborate and experiment to find the right approach

How do you deal with uncertainty? Comment below or tweet me.

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