Decisions are based on fact, emotions and guaranty a business success or failure.
Among people knocking at your desk, emails, chat, phone calls, meetings, social networks… sollicitations are numerous and it’s tough to find the right set of information, digest and understand complex issues. Those noises don’t help to focus and decide.
A decision contains a part of fact and a part of feelings. Always.
Data design is here to reduce the noise and find the best way to display your data, facilitate your comprehension and get the information you need to make your decision. At least on the factual part.
Let’s see how data design can help you to decide and how to integrate it in your company.
Data design definition
For a detailed data design definition, I would recommend to read my article about data design and data art definition
Data design ensures you to have all the necessary data in the right form to understand complex situations. This is crucial to make choices impacting the future.
Data visualization is about data accessibility in charts and graphs. No matter if those data products help or not. Before making your decision, you may have to crunch several dashboards – usually not centralised – compelling tons of KPI without being sure that this is actually useful. Sometimes it’s even confusing as same KPI may have different definition and calculation rules.
In the end, this is precious time lost to build your own dashboard aggregating several dashboards in emergency.
Data design offers a curation by design : select the best KPI displayed in the right format that accelerate your comprehension.
The ability to decide is mandatory and data design is a strong asset for that.
Data design to facilitate decision making
Data design helps to decrease the data noise and display the information in the right way. Here is why :
Prevalence of the visual sense
We get information from our five senses but the sight is the major one by centralising 70% of the visual receptors and our brain dedicates 50% of its activity in visual treatment.
In addition, we treat images and graphs faster and memorised better (2/3 of people learn by visual).
But it would be too simple to multiply visuals : based on the theme and the purpose of the information, they need to respect some rules. The human brain filters information if they don’t respect them and produce the opposite effect despite all your efforts.
This is rules about design – right form with harmonious colors, relevant text and typography – but also about curation in a period of time where data is everywhere.
Data abundance
Some years ago, data wasn’t so abundant. If some companies had it in massively, the challenge was to access and treat this data. Tools weren’t as developed as today.
Today, we have everything : a lot of data, accessible and the tools to manage it.
We have too much data and a part of the data design process is to select just what is needed to make your decision.
Complexity reduced and mind opened
Perfect visual and data curation decrease the complexity and accelerate decision making.
It also bring a new angle in the thinking : going beyond the design in some use cases to approach data art level inspire and open the mind to a new way of thinking.
Traditional data visualisation process won’t generate that.
Data design is a strong lever to accelerate decision making process but there are some guidelines to integrate it in a company.
How to implement data design in a company
It’s not about decoration
That’s something I hear quite often from both manager and data analyst : it’s not just adding fancy colors, graphs and typographies. It’s not decoration. Data design must serve your comprehension !
Master your data
As seen previously, we have too much data.
Abundance brings some issues and the biggest one is the lack of governance.
Data governance helps to manage mass of data preventing dashboards abundance and quality issues.
This is far more dangerous to have bad data to decide conducing to bad decisions that not having data at all.
When you master the data you own, you need to take care of your data quality which is a part of the governance process.
Data governance is not sexy and most of the companies don’t invest in it. But it’s fundamental to avoid the equation: bad data = bad decision.
If data is curated and passed the quality check. Let’s go for the data treatment step.
Data and design modern stack
Solutions exist to store and transform the data: from the data mart to a data mesh approach, depending on the size of your company.
Then data modelling appears to transform the data before the visualisation step. It will optimise the dashboard performance execution.
Tools are important depending on the mass of the data and the outcome you need: a fixed infographic, a dashboard or an animated data story. Design tools must be considered too, in addition to data tools.
The whole process could be complex as several type of experts collaborate. That’s why organisation is key.
Data design organization
It’s important to identify all the people implied in this program that will allow you to effectively use your data as a strong business asset.
A mistake I see very often is the step where data designers are contacted: lately in the process.
They have to be in the discussion from the beginning: the brief that describes the needs or even at the strategy definition step.
As I mentioned : it’s not just making a dashboard looks good. It’s about using your data as a business asset and a way to accelerate your decision process.
A data designer will help to define your need but also the way to treat and model your data to make an efficient dashboard from a technical point of view.
Bias prevention
Bias may be added on purpose but most of the time, people are not aware that the dashboard they create could lead into misinterpretation. Data designer is here to prevent design bias but as always, it’s mandatory to work in a close collaboration with the business team. They are the business experts and final users.
Speaking about the final users, it’s crucial to adapt the information format to the audience.
Audience centric
A data design product will basically serve 3 purposes concerned by different levels in the company: strategic, tactic and operational.
A CEO or C-Level won’t have time to dig into a table or a large dashboard. Main strategic KPI must be displayed and sometimes accessible quickly via a smartphone. But this is not enough for a marketing specialist who needs more details to prepare a marketing campaign for example. Even this tactical level is not enough for an analyst who needs raw data to define a customer target and be more than happy to use a self BI solution.
Conclusion about data design in business decision process
Our brain focus on visual : we get information faster and are more willing to memorise them.
In a world drowned by data, data design helps to reduce the noise and expose data in a way that facilitates comprehension before making a decision. It reduces complexity and including data art could even bring new analysis angles and inspire new ideas.
To implement data design, it’s fundamental to check the first steps of the data journey: data governance, data quality, data infrastructure. From an organisation point of view, a data designer must be in the team from the beginning to ensure that in the end, it’s possible to create an outcome able to use data design principles.
Basic project delivery best practice should be there too: focus on the audience and collaborate with business team.
Data design helps in the decision making process by bringing the factual part and a slice of the emotional part that is often underestimate.
But it’s just the beginning. A decision implies actions and to guarantee their success, you need to sell it.
Sell it to your boss, to your investor and, of course, to your project team members if you want them to work motivated in the right direction. Story telling is a solid way to sell a vision, a necessity to act. Data design and probably data art will help to create an impactful (data)story telling.
Do you want to revive your data ? Just let me know