From Data To Value: Businesses Need Insights, Not Data
If data is the new oil, then insights are the new gasoline. Data needs to be refined to drive business. How can businesses ensure to get the most value out of all the data they collect?
by MING Labs
In a previous post on the topic, we reflected on the potential of turning data into commercial value and the importance of having a customer-focused data strategy. The kind of data you have is an essential factor in what you can do with it. And as most businesses are looking to drive results further, focusing on the customer is critical. At MING Labs, our interdisciplinary teams focus on the end customer, and design and develop digital products that solve their problems, based on data collected from user research. All this builds an important part of our work.
Data, however, is just the raw material in the process of value creation. To turn data into value, it has to be refined into information, which in turn is translated into knowledge and eventually into insights (to learn more on these four stages of evolution, it is worth reading about the DIKW pyramid). Insights are what businesses can really leverage.
The ability to turn data into information, knowledge, and ultimately insights is a crucial factor in the ability to use it as a commercial lever.
In our work at MING Labs, we help our clients do exactly that — go beyond their observations and derive insights about their customers that can serve as springboards for innovation.
To understand the importance of translating data into insights, one should remember that ‘data’ is simply a collection of signals. Information, while it adds a narrative to data by putting it into context, is still merely an observation that requires further investigation. Knowledge is then the combination of different pieces of information.
An insight, on the other hand, is the derivation of something entirely novel from knowledge. Insights are the springboard of innovation, as we gain a deep understanding of a situation that allows for new approaches. Insights launch whole new industry categories — such as mobility or cloud computing.
How might businesses leap from data to insights?
Drilling Into The Details
Take, for example, Theodor Levitt’s famous quote: ‘People don’t want ¼ inch drills, they want ¼ inch holes.’
A collection of ¼ inch holes is data. It also tells us nothing more than that there are X holes at the diameter of ¼ inch. Putting that in the context of a wall, perhaps even in a living room, and that these holes were made by man gives us the required understanding that it was a human that created these holes in their domiciles.
That, however, is still information with limited commercial implications. Add to this the understanding that people drill such holes to hang pictures, and you have enriched your ability to act upon this data. Perhaps by deducing that there is a market for ¼ inch semi-professional drills or that there is room to innovate in the way people can hang pictures. Now the business can take action with real commercial implications.
This analysis (at least as widely quoted) still falls one step short as it does not seek to discover people’s motivation to hang pictures in their living rooms. An understanding that people hang pictures to preserve and present their memories could lead to innovation on the topic of memory display. An understanding that people hang pictures to show off their good taste in front of guests could lead to a whole new area of innovation.
A Well Of Refreshing Insights
Let’s take another example: Many people use refreshing mouthwash. This fact, on its own, is data.
Many 20–40 year-old people living in urban surroundings use mouthwash, which adds context to this data and thus increases its commercial usefulness (by enabling the ability to forecast demand and sales, for example).
Add to this the understanding that these people use mouthwash because they want to feel good about themselves, and you can refine your marketing efforts or develop additional products that make people feel good about themselves.
But understanding that people do so because they need to feel good about themselves on specific occasions, such as dates or business meetings, and you get a powerful insight that can open the door to multiple related innovations (such as social interaction enablers).
When we work on generating insights, we try to achieve at least one, if not two things — Understand the Why behind the What, and incite more questions that would not have been asked otherwise.
Case Study: Turning Telco Data Into Valuable Insights
Working with a Telco provider on a recent project, we leveraged data to gain both insights as well as incite more questions.
A Telco company that sells both mobile and broadband has high visibility of the number of smart devices used by people. It knows the number of smart devices that are connected to a household’s router, and it can identify the type of smart devices used, based on the apps that that household’s residents download and use.
As such, it can know various things: It can know which areas are more populated with smart devices than other regions, and it knows which smart devices are frequently used jointly. This information on its own has commercial value to brands that manufacture and market smart devices. For example, they can assume sales potential in various areas and offer bundled products based on purchase habits.
What this information does not explain is the Why.
Why are some areas more populated with smart devices than others? Why do people who buy one specific product frequently buy another one?
Answering those questions requires further investigation and has far greater commercial potential: Understanding why specific areas have more smart products than others may suggest that better infrastructure, such as broadband or smart switches, is required in undersold areas.
Understanding why people buy specific products in conjunction with others can lead to developing features that connect between these products. It can have a direct impact on marketing decisions, as product bundles are revised, pricing can be updated, and messaging can be refined. For campaigns, the insights also help target the right consumers in the right areas with the right story.
How To Get Started
Businesses need to refine data into information, knowledge, and, finally, insights to drive commercial value from it. This is a task for a cross-functional team. At MING Labs, our cross-disciplinary teams of skilled business designers and user researchers put refined data into context by conducting user tests, digging into motivations, and enriching it with additional data and information sources. This task has to be driven by a business-relevant inquiry.
More and more companies turn to us with the question — How can we make better use of our data and turn it into commercial value? Often the question comes out of the blue because data is all everyone hears about. Whether in logistics, machine building, banking, or any other industry — everyone is thinking and talking about data. Yet we rarely find any companies that are driving commercial value from their data operations.
Should you come up with a similar focus, here are a set of preliminary questions we would challenge you to ask yourself:
1 What data do you have? In what quality and quantity?
2 In what context did you collect this data?
3 What do you believe this data tells you about your customers, employees, operations, …?
4 Why do you think this data shows what it shows?
5 Who do you think can make use of this data, if contextualized and properly story-told?
MING Labs is a leading digital business builder located in Berlin, Munich, New York City, Shanghai, Suzhou, and Singapore. We guide clients in designing their businesses for the future, ensuring they are leaders in the field of innovation. For more information, visit us at minglabs.com
Liked this story, and curious to know more? Start a conversation with us on Twitter, check our latest updates on LinkedIn, or drop us a note at hello@minglabs.com.
Related Reading: Is Your Data Strategy Customer-Focused?
