• Digital Workplace
  • Performance Management
  • Predictive Analytics
  • March 26, 2019

Data Science and Design – Why Combine Them?

Data science can be defined as analyzing and explaining phenomena from data with the help of various advanced calculation methods. It means trying to identify repetitive patterns from large masses of data using mathematical, statistical and machine learning models. The goal is to identify substantial information and to present it in a format that is easy to comprehend. A billion rows of data could, for example, tell us that whiskey drinking, body-building motorcyclists that mainly watch Bruce Willis action movies, put their life on hold the minute a new episode of Tidying up with Marie Kondo is available.

Design can be seen as a concrete plan that helps us to reach the desired outcome, whether that outcome be a product, service, process or strategy. Good design is goal-oriented and based on insight, not guesswork.

Designers make use of all available information when trying to form an accurate understanding of the situation in order to identify the challenges that need to be solved so that the desired outcome can be reached. Designers specialize in using qualitative research methods to understand the human needs and behavior.

Data Science Without Design Is Wasted Potential

In general terms, we could say that data science provides information on what is happening and design methods help us to understand why those things happen, and what we should do about it. When numerical data and qualitative customer understanding are combined, we are able to prove customer behavior hypotheses right or wrong.

After thousands of hypotheses, tests and improvement measures, we know an astonishing amount of information about the desires, habits and behavior of customers. A customer-oriented science project helps companies to optimize their services – even in real time.

Customer Knowledge Is the Key to Success

In today’s world, technology makes it possible to predict future events more precisely than ever before. With this information at our disposal, we are able to affect the future, be it presidential elections, the Brexit referendum or predicting consumers’ purchasing behavior.

Data science is a goldmine of insight for design work. Why do Amazon, Netflix and Facebook dominate the markets? It is not a lucky coincidence. They have made their consumer research an exact science that predicts the future behavior of their users.

My family is going for a holiday in Tenerife. The tickets have been paid and we are waiting for the holiday. While the travel agency could be sending tips for activities in the destination, instead I receive an email advertisement about a cheap vacation in Tenerife. I’m not joking. To avoid unnecessary annoyance, I probably should not check if the newsletter ad offers the same trip for cheaper. Non-personalized advertising can be like a bull in a china shop. For someone else, the ad might have been just the right one. But in my case, the travel agency ended up being the center of a joke.

In companies that don’t ask their customers to take their families to the same abroad holiday destination twice a week, content personalization determines what to send. The content selection is based on manually set rules (for example, do not send an advertisement for a product that the customer has just purchased), algorithms that choose the content based on data. Machine learning is used to make sure content recommendations keep getting better.

While earlier newsletters used to be identical for each and every customer, a modern online retailer might send millions of partially or fully personalized newsletters in a day. Each customer receives the best possible, personalized version of the content. This is likely to lead to more purchases and the concentration of consumption.

If you mention to your friend that you would need something, a circular saw for instance, the next time you log on to Facebook, you might see an advertisement for that exact circular saw which is now 30% off – and even the last piece in the store! Wow, what a lucky coincidence! Or was it?

In the new world, a company that knows its customers well and predicts the near future with precision is always several steps ahead of its competitors. This is how tiny Netflix brought down big Blockbuster and eventually grew into a market-dominating mega-firm.

The Rise of Netflix, and the Fall of Blockbuster

Yet, data alone is not enough to explain the whole world. We also need design research to provide us with deeper understanding about the future. Design research is particularly good at uncovering the unknown which feeds hypotheses and data insights. For instance, Frog Design received a mission from Disney to figure out ‘what is the future of entertainment in the context of amusement parks?’. This led to the creation of MagicBand, the new smart wearable that’s the centerpiece of the Disney experience.

Numbers can “lie” to us. If we ask the wrong questions, we can end up drawing the wrong conclusions. Unfortunately, this is all too easy for us. For example Nokia found this out the hard way. We are good at coming up with rational explanations to phenomena but without qualitative research our conclusions might be totally wrong.

Netflix talks about customer obsession, an obsessive need to understand the customer. When corporate culture and decision-making is based on understanding the customer, the company is difficult to beat. In a customer-oriented company, all employees make decisions that aim to bring value to the customers.

In a tech project, JIRA tickets and project schedules are secondary. The most important thing is to create value and take the right steps forward, even if they are small ones. Developing features is expensive so it pays to know what you’re doing and do things right rather than producing a sub-par result. If all employees in Company A concentrate on bringing value to customers and Company B’s operations are based on following the competitors, it is just a question of time before B is left biting the dust. It is like a race between a Formula 1 driver and a turtle. Spoiler alert: The turtle doesn’t win. Unless the F1 driver messes up. It is possible to “move too fast and break things”.

Tech Giants Rule the Game, Others Try to Hang on

For traditional companies, all of this has been very difficult. Consumer research has of course affected, for example, the food industry’s recipes already for many decades. Yet many companies have failed to see how digital media reaches customers everywhere, not just at the store. While a traditional company optimizes the packaging of potato chips to encourage impulse buying, a digitally aware company influences the consumer behavior already before the customer has even entered a store. Behind understanding and influencing customer behavior are super teams of customer innovation that have high-level expertise in design and data science.

Some companies have reacted to the situation by buying entire design firms to ease their path to future success – or just to keep up with the increasing competition.

It seems that in the future a growing number of markets is dominated by young technology companies, and this trend is accelerating. For instance, the advertising business is already pretty much controlled by Google and Facebook. Who would have guessed just a decade or two ago? Similarly, banks and credit card companies have not been able to stop Apple and Google from entering the mobile payment market like a bull showing up to a tea party.

Amazon has expanded its Prime loyalty program and pushes Americans to concentrate their consumption. Audio and video streaming, online stores, e-books, groceries and so much more. Everything made easy and personalized just for you. So practical. When something just works, why would you consider anything else?

It should come as no surprise to anyone that companies that have a design-led corporate culture and understand their customers beat their competitors and take more than their fair share of the market in each and every sector. If the word design-led doesn’t resonate with you, let’s clarify: being design-led doesn’t necessarily mean being designer-led. Or, that designers should be new corporate overlords. Everybody affects the user experience and designers can’t or shouldn’t do everybody’s job. Being design-led means everybody puts the user experience first, not only designers. When this happens, customers stay with you and business flourishes.

If design-orientation, data and customer science sound like a strange foundation for business management, then you should get used to the new reality as soon as possible. It is not just a few tech pioneers but a revolution of the whole working life and a redistribution of the market shares. Living in denial and sticking to the old ways of thinking is the surest way to lose your market share. The signs have been there for a long time and if you have not changed the course by now, it will soon be too late to save the ship from sinking.

Our design team has had a proven impact on revenue, cost savings, time to market, valuation.

InVision has conducted a survey that classifies companies based on their design maturity. The companies that are best at design-oriented business leadership and culture have better business performance. Source: https://www.invisionapp.com/design-better/design-maturity-model/

Why Do Big, Well-Known Companies Fail to Dominate on Their Home Turf?

You would imagine that traditional big companies with their big resources and market shares put up a bigger fight. But it is not that simple. Reforming a large organization takes time. People do not want to change their decision-making models, bureaucracy slows down innovation, and managers and employees alike prefer sticking to the old safe ways. Companies fail to attract the most competent employees, the performance indicators encourage to concentrate on the wrong things, the technology is outdated, etc. Usually, the critical decision-making models are changed only when it is almost too late: only when everyone can see the signs.

In the end, everything comes at a high price of change. The old beliefs and ways of thinking need to be abandoned but a large organization is not as agile to change course as a small start-up. The organization has been developed over the years to be good at removing disturbances, that is to say, to slow down changes.

Although a small tech firm has limited resources, it is able to test its hypothesis with customers before a traditional company has time to organize even the first internal meeting. As a management consultant and author Peter Drucker put it aptly, culture eats strategy for breakfast and even the best ideas are abandoned if one sufficiently important manager says “no”. A company with great resources might be completely unable to cope with change despite everyone doing their best.

Design Thinking Can Support a Cultural Change

The organization’s design competence can be increased with recruiting but that is not enough. Tim Brown of the design firm IDEO has cleverly stated that design is too important to be left to designers. The design is collaboration-based and belongs to everyone. Different points of view and diverse understanding are needed. No one is an expert in everything. Many organizations have converted into a customer-oriented thinking model with the help of design thinking.

Design thinking is a systematic approach to business operations and decision-making that combines empathy, creativity and rationality. Design thinking brings the designer’s way of thinking and design methods at everyone’s disposal, helping them to have a stronger customer orientation.

Design thinking does not remove the need for actual design work, quite the opposite. It increases the need for design work as people realize how much better everything could be done. Design thinking helps organizations to grow more mature, have a stronger customer orientation and identify simple, and often painful, changes that the company needs to make in order to develop.

Data science and design are often seen as completely separate competences but when you combine them, you gain an opportunity to build unique services that anticipate the needs of the users.

The Game Is Not Over

The world-leading companies have successfully used design and data science to expand their market shares immensely in a very short time. But this is not rocket science. If you study, test, assess and improve continuously, you cannot avoid developing your business.

In the old world of technology, teams were set up around product features while nowadays there are also growth teams whose task is to test, explore and develop models that encourage the use of services by increasing the customer value. The more value, the more committed customers. If you use a service every day, you will also use it tomorrow. And the next month. And a year after. The competition for people’s time is tough and everyone wants a slice of your daily life.

Do you know your customers? Do you have growth teams? Do you personalize your services on an individual level? Which are your customers’ top 5 pain points at the moment? Are you able to predict customer behavior? Do you know how to scale up the number of loyal customers? What are the most significant factors leading to customer churn?

Many companies know the answers and develop their services and operations based on customer orientation and data. They are the winners of the future because the Internet and digital technology bring the opportunities at everyone’s reach and knowledge always wins over guesswork. If your company’s customer understanding is dragging behind and you do not know what to expect from the future, it is high time to roll up your sleeves.

Customer Knowledge Toolkit


  • Customer and user understanding through qualitative methods in particular (e.g. user research, usability testing)
  • Design thinking – customer-oriented design methods for everyone
  • Designing new solutions, prototyping

Data Science

  • Analytical and artificial intelligence tools, e.g. IBM Watson
  • Data analysis and modeling
  • Verification of hypotheses, patterns and phenomena on a larger scale
  • Fact-based prediction models

Growth Teams

  • A range of experts in data science, design, marketing, software engineering and others
  • Hypotheses, experiments and measuring of success
  • Developing the customer understanding
  • A systematic way to promote growth

About The Author

Jarmo Valmari, Head of Design at Valamis

Jarmo Valmari

Head of Design

Jarmo has been leading and managing the design of products and services at Valamis since 2014. Jarmo’s design-driven strategy work has helped organisations from private and public sector for the past 15 years.