At Plot + Scatter, we’ve seen our clients make the same three mistakes across all industries — big and small, corporate and non-profit. These errors cost time and money. In some cases, they lead to the realization that the entire project needs to be re-imagined. Not ideal.
These common mistakes are:
- Setting unrealistic goals because the project team has misunderstood their target user / audience / market.
- Underestimating the extent to which local conditions and environments determine how, where, and why their target audiences behave in certain ways.
- Ignoring how these can change across regions / organizations / departments / industries / socio-demographics.
People tend to only look at basic or traditional indicators in their data projects. As a result, they miss great opportunities that would allow them to dive deeper into their data. Sometimes they totally miss the boat.
To help our clients avoid making these mistakes, we’ve adopted some useful Agile and Lean User Experience (UX) Design methodologies. In this series, we’ll show you how they can apply to any data project.
Smart methodologies for working with data
The terms “Lean UX” and “Agile” are often heard in the tech world these days. More than buzzwords, they are processes and methodologies that have allowed the tech industry to evolve and innovate at a fast pace. Luckily, they can be adapted and applied to industries and domains that go beyond the tech sector.
While Agile stems from the development side of tech, Lean UX stems from design. Both embrace similar values and principles that focus on:
- people (instead of tools and processes)
- iterative work (to minimize overall risk and adapt quickly to necessary changes)
- collaboration throughout teams and different roles (breaking down silos)
- shorter feedback loops (test or get feedback often, sooner rather than later).
(To fully understand the difference between Agile UX and Lean UX, check out this link.)
So how does this apply to understanding and communicating data?
According to Don Norman, “guru of workable technology” and co-founder of the Nielsen Norman Group, user experience in general is defined as “…everything. The way you experience the world, the way you experience your life.”
Data is exactly this: tidbits of numbers and information that show us on how people experience their lives and the world.
Lean UX and Agile techniques are all about setting your assumptions aside and listening for multi-dimension answers instead of jumping to conclusions. It all starts with peering beyond the computer screen and into the world.
Get outside of the building (GOOB)
GOOB is a UX and product design exercise that should confirm assumptions that product teams in tech make about their projects . It works exactly as it sounds: you leave your desk to go collect relevant information. Then you confirm (or refute) your assumptions.
This can be done in different ways with:
- Stakeholder interviews
- Ethnographic research
The perils of tunnel vision when working with data
One of the worst mistakes people who work with data make is focusing only on the data immediately in front of them. Step away from your spreadsheets and computers. You will discover information you hadn’t considered before.
A recent article in the Harvard Business Review explains how multinational corporations (MNCs) failed to understand their targeted markets in Africa. In their example, MNCs only relied on GDP and demographic growth data to build their business strategies.
Their approach to data didn’t capture how wealth trickles down through society. This led MNCs to overlook the informal economy. More than 50% of working adults in Africa earn income from activities not reflected in official statistics.
Organizations tend to jump-start their data projects without building a foundation. They’re eager to gain insights without thinking about what they might do with them. They don’t consider how they will take action afterwards. And most importantly, why they want to do the project in the first place.
Sometimes project leaders already have an idea of a desired outcome. But if they don’t question their biases and remain curious about what the data is not saying, they will miss big opportunities.
In the Harvard Business Review study, the author and her team talked to people ranging from hairdressers to public relation executives on the ground. This allowed them to rebuke several myths and assumptions about middle class African consumers. They discovered that many Africans valued durability over flashiness when buying higher-cost items.
The team found that MNCs also overlooked an important fact. In Africa, traditional ties between individuals and large family networks remain important. As a result, they may have ignored opportunities in regions that would appear as poor in the data.
In short, start those data projects right
These examples may appear anecdotal at first. But collecting these stories on the ground will help identify gaps in your data and your approach to it. It will also save you time and resources in the long run.
Adopting Agile and Lean UX strategies to the way you approach data will lead to better results for your projects. So start GOOBing with data today.