Data is valuable only if you know how to make decisions
 

By Ari and Mona Riabacke, lecturers and business strategy consultants on decision making and how human nature and technology interact in the process.  

Too often we look for answers to questions without realizing what is truly important for us to know. Ari and Mona Riabacke are helping companies determine why they are looking before they sift through the data.

With an abundance of information and data available to help steer strategy in companies, combined with the advantages of data analysis, how come so many companies still struggle with making the right decisions?

Ari and Mona Riabacke are business strategy consultants, authors of the book Freestyle Decision Making and frequently featured in different business magazines. Both hold PhDs in risk and decision analysis. According to the Riabackes, most of us forget to look at the actual process of decision-making and the human element steering our actions. We amass more and more data hoping to gain more insight – but often fail, simply because it is not fully clear to us what we are looking for or why we are doing it.

“We are trying to tell people that in most cases, they do not need more information. Instead, they need to be clear on what they are trying to decide. We are so keen to be super rational and make the very best decisions that we tend to forget to ask ourselves: What are the most important ones?” says Ari Riabacke.

He tells the story about how in workshops, he asks business leaders to answer the simple question: ’What are the 3-5 most important decisions your company needs to make – short and long term?’ “So far, not a single one has come back with a clear answer on this,” he points out.

Backing up this assessment, the Riabackes asked almost 800 decision-makers to explain how decisions were made in their companies. They received some startling feedback:

• 50 percent of the respondents could not point to documented processes for decision making – only 7 percent could fully confirm that these processes were in place.
• Just 4 percent of respondents felt that new approaches to decision making were valued in their company, while almost half felt new approaches were not appreciated or absolutely not appreciated.
• Only 6 percent of the respondents completely agreed that decisions were followed up to ensure that they were carried out. 55 percent did not agree that this was the case in their companies.
• A mere 2 percent fully agreed that the majority of available data in decision support systems were utilized.

Lack of structured processes in decision making

To the Riabackes, these answers and many more studies of how companies go about their decision making confirmed that far too many simply do not know how or why they arrive at crucial decisions.

“If there is not a structured method, which is written down, there is a risk that decision makers do not have the same understanding of how to go about the job. It can be a simple process, perhaps a check list. But it needs to include information on basics such as: Who should be part of the decision, what roles do people have, what are the important criteria, which time-frame are we operating in, and so on,” says Mona Riabacke.

Just as culture eats strategy for breakfast, culture frames the decision making process and determines whether outcomes are based on real knowledge or just gut feelings.

“The most complex decisions made at the top of companies often include much more than only information. We see that another, much stronger, system kicks in, one called intuition. Analysis is often done at lower levels of the organizations and does not always filter up into the really important strategic discussions,” says Ari Riabacke.

But does this mean that analytical decision making tools are irrelevant? Absolutely not, the scientists are quick to stress. For example, Mona Riabacke points to the healthcare field as an area in which data analysis can greatly improve a doctor’s ability to quickly gain access to the newest information about treatments for rare diseases as a good example.

Large data quantities create false sense of security

However, many companies risk taking false comfort in the fact that they have made an investment in a data analysis system if they do not look very closely at how it is best utilized.

“We call it The Cookbook Syndrome: People buy cookbooks because they dream about a different life. In many cases, companies buy decision making support systems because they think they will use them – but they end up not using the systems to the extent that they thought they would,” says Ari Riabacke and continues:

“We have yet to meet a company that has been able to make progress just by buying a new system. There’s a lot of work that needs to be done in parallel, work that isn’t tangible like the decision support system itself, yet essential for its success. How the system fits into the “bigger picture” of the domain in which it will be used. We too often forget to provide the right resources for the things that steer decision making more than anything else: people and culture.
Once this is clear, data analysis systems will become much more valuable tools in sifting through the massive amounts of information available to all of us today.

IoT: The future of unburdening our busy brains?

The data explosion is only intensified by the rapid development of the Internet of Things, which adds terabyte upon terabyte of additional information to our already brimming data warehouses. But perhaps surprisingly, the Riabackes see great potential in this development. Pointing to their matching Fitbit armbands, they look forward to a future in which technology helps us in the right direction based on the data of our daily actions and our health status - especially when technology develops to the point at which our decision burden is actually lowered. For example, when our IoT-connected fridge is able to determine how much milk our family drinks in a week and automatically orders for us.

According to scientists, humans use mental short cuts, so-called heuristics, to simplify the complexity of decision-making. Although often helpful, heuristics can lead to errors of judgment in the form of biases. In general, people still know very little about how to avoid being biased when making decisions. However, the Riabackes are emphatic that it is possible to design a decision process that aims to uncover these biases before they become errors in judgment.

“So much of our time and energy is taken up with decision making, often rather unimportant decisions. We need to be able to focus on the important ones and find ways to automate the simple ones, so we don’t waste a lot of time on them. The ‘smart’ part of our brain has very limited capacity,” Mona Riabacke points out.

Framing and communication are essential for success

Another important human factor besides our limited capacity for complex information is our need to understand not just what but why change is occurring. The Riabackes point to the example of an insurance company. A brand new IT system was partly implemented but the predicted success did not occur: It turned out that many members of the organization did not truly understand the value of the system and thus, did not make the effort of learning to use a new system and changing their way of making decisions.

“The system was good, so we helped them with the communications, which was essentially a change management task. There’s clearly a difference between user-friendly, useful systems and systems that are actually used. To ensure the system is used, we often need to invest more in the “people part”, Mona Riabacke concludes.