How to Implement Data-Driven Decision Making in Your Organization

One of the most powerful choices a company can make is to focus on data and develop a strategy of data-driven decision making. Experience and inference are powerful leadership tools, but data can guide CEOs and other executives to the best decisions possible. 

While many companies want to be data-driven, it’s not always easy to change a pattern of leadership and thinking that has lasted for years. To make the transition easier, follow these seven steps to help your managers, staff and analytics team utilize data-driven choices. 

Encourage Senior Leadership to Embrace Data

The first step toward using data as a decision-driving tool is to get complete buy-in from the executive team. Jonathan Milne, director of marketing at data analytics cloud app Klipfolio, says data-driven decision making needs to come from the top if it is going to be embraced throughout the organization. 

Executive leadership teams need to show that they trust data and make choices because of it. Otherwise, low-level managers and employees won’t be as motivated to base their arguments on data and facts. If the CEO doesn’t care, then why should anyone else? 

Milne says that in the absence of data, the HiPPO (“highest paid person’s opinion”) reigns supreme. Whoever is highest in status or rank has the final say, no matter how compelling the data is in the other direction. In business today, this pay-rate power grab is not sustainable.


Make Data Seem Approachable and Valuable

Another way to make a case for data-driven decision-making is to prove that any company, regardless of size or budget, can use it. 

Even the smallest companies create data, emphasizes Graham Church, founder and managing director at software company CodeFirst. Small businesses can look at their social media engagement, website traffic, customer transactions, reviews and inventory to learn about their organization. They can track what is effective and what isn’t as a way to test the success of various ideas. Essentially, saying a company is too small or doesn’t have the funds for data isn’t an excuse. All companies generate data, it’s just a matter of utilizing it.    

Of course, it’s easier said than done. The team at data company Grow note that 85 percent of companies want to be data driven, but only 37 percent feel like they have been successful. 

“From our experience, managing data often overwhelms companies, especially startups with small teams who are wearing a multitude of hats,” they write. “Trying to keep up with the endless reports across various departments is enough work to be a full-time job, forcing many organizations to have to choose between data insights or actual production.” 

Too often, data driven decision-making turns into just more reports from employees, where management glances at the data without taking a second thought about the information. This is a matter of executive training and buy-in. 

Offer Training for Different Levels of Data Comfort

As a company becomes more data-focused, employees outside the world of data analysis will need training to learn how to use analytics tools and how to approach new sets of data. It’s important to note these are skills that can benefit your whole organization.

Data analytics isn’t a niche career field where only one or two people within the company benefit, says Naren Madan at training solutions provider Simplilearn. “Nearly every industry today is improved with the implementation of Big Data, and similarly, every career field is significantly improved when the ability to collect and analyze Big Data is added to the mix,” he explains. 

As more employees embrace data rather than fear it, they can become more involved in the company’s data investments, governance, and bias prevention.

Despite the perceived value of data, not everyone feels comfortable manipulating, presenting or questioning it. Arithmophobia, the fear of numbers of math, is very real in the workplace. This doesn’t mean that your coworker can’t handle an excel spreadsheet, but rather that they feel confused or overwhelmed when confronted with data. 

To limit arithmophobia, the team at 7wdata encourages analysts to use colors and images when possible to make data seem more inviting. They also suggest using metaphors and stories to connect the data to qualitative experiences. This can take a page of insights and turn them into something meaningful, making data more approachable.  

In some cases, embracing data-driven decision making might involve rebranding it or proving that the process of collecting and analyzing information is actually part of being human. 

“Any CEO understands statistics at a gut level, because that's what they do every day,” says computer scientist Paco Nathan. “They may not know the math behind it, but the idea of collecting evidence, iterating on it and basing decisions on this is intuitive for executives." 

The challenge is making CEOs, managers and other employees less numbers-phobic and convincing them to give more weight to the data insights presented to them.


Teach Employees to Identify and Avoid Bias

If people are going to use the data that is available to them, they need to know it is accurate and trustworthy. This starts with your team members. People must be aware of their own biases and learn when their personal feelings are clouding the numbers.

Many people are guilty of seeing the data they want rather than the big picture, writes Sandra Durcevic at business intelligence software provider Datapine. They cherry pick their top insights and ignore or hide information that won’t help them. In this way, they only present a positive picture to management, who has to trust the source and interpretation of the information.

Bias is so prevalent in data analysis that Naveen Joshi, founder and CEO of software solutions provider Allerin, created a guide to identify and prevent it. He looks at factors like confirmation bias (looking for data specifically to confirm a hypothesis) and interpretation bias (where certain words or insights cause analysts to come to different conclusions). Joshi demonstrates how people are swayed by reports and that, while data itself is objective and concrete, there are certainly opportunities for emotion and manipulation.

Companies that want employees to use data need to provide the right training and resources to limit biases that paint incorrect pictures.

Implement a Data Governance Process

Another way companies can overcome employee wariness of data is by implementing a data governance strategy within the organization. 

The team at BI-Survey found that 41 percent of companies have the IT department in charge of data governance and 10 percent state that the IT department alone governs the data. They say that this 10 percent is as high as that number should go. Data is the responsibility of everyone who uses it, and it’s up to the whole company to make sure the information collected is accurate and useful. 

Investing in data governance prevents data breakdowns while proving to leaders that the information can be trusted.

Good data governance will become more valuable as teams within a company use the same data sources. Instead of siloed teams using their own data, information will likely be shared across departments, which means that one set of bad data can result in several bad decisions. 

“Remember that when different departments use separate systems, it can lead to inaccurate data reporting,” writes business strategy consultant Orlando Trott. “The best systems can cross-analyze data from different sources.”

Having a policy, strategy or team in place to maintain the health of the data means that no one will need to question the source or collection model used in a particular report. 


Understanding the Value of Gut Decisions

Many executives ignore data at first or believe that their gut is more reliable than the data presented to them. Interestingly, this reliance on gut instinct is somewhat cultural. 

According to a study by KPMG and shared by the World Economic Forum, executives in some countries are more likely to go with their gut over cold, hard data. Americans at 78 percent have the highest rate of “decisions by gut feeling,” followed by Japan, the UK and Australia. Meanwhile, just over half of French and Dutch CEOs say they have overlooked data in favor of their gut instinct. 

That said, many CEOs rely on intuition because they question the data they receive. More than half prefer historic data to predictive analytics, so going with the gut actually means overriding data that they know is overblown or incomplete. 

This means that there is a time and place for relying on intuition. Companies that want to rely on data can actually increase adoption if their managers realize that there is some flexibility involved — they won’t be expected to follow the data all of the time. 

“Not all the decisions we make...are driven by cold, hard numbers,” explains Karl Sun, cofounder and CEO of visual productivity solutions providers Lucid. “The numbers can be a good jumping-off point, but at the end of the day, we’re dealing with people. And when you’re dealing with people, you will need to include the necessary element of learning to trust your gut—even when the data says otherwise.” 

When asked the secret to balancing gut instinct over data-driven decision making, Sun says his company is still figuring it out. While they create a culture of experimentation and trust, not all gut instinct-based calls pay off and not all data-driven ideas lead to perfect results. For the most part, CEOs can learn when to use the data and when to use their own experience to make a call that is similar or counter to what the data says. 

“The more experience you get, the more you can rely on your gut,” writes communication specialist Alexander Maasik. “When you have more experience, you can make more informed decisions by default.” 

In a way, experience develops your backlog of qualitative data that you pull from and apply when faced with new information. This is no different from an AI tool that is shown 100 pictures of giraffes and then is expected to identify a giraffe. Your mind provides you with its own set of data.

Prove That Data Investments Pay Off

Business analysts who want to move their companies toward more data-driven decision making need to prove the value in it. They have to show that business success is directly correlated to implementing new data processes, and that the investment in these new processes is paying off.

Research is on their side. “Studies show that data driven organizations not only make better strategic decisions, but also enjoy high operational efficiency, improved customer satisfaction, and robust profit and revenue levels,” says Harshdeep Singh, research associate at Queen’s University in Toronto. 

He reports that data-centric organizations are 23 times more likely to acquire new customers and 19 times as likely to be profitable. 

Remember, the data you collect is only as valuable as the insights derived from it, notes Elana Katzor at business intelligence software provider Sisense. She cautions businesses from collecting hoards of data without using it. After all, if you keep going to your leadership team and asking for more investments in data and analytics tools without proving their value, the purse strings will eventually close. 

Getting a company to buy into data-driven decision making means identifying the top barriers to adoption. Does the CEO prefer his gut to analytics? Are people afraid of numbers? Does the data seem biased or inaccurate? Conquering these fears can help employees move to a more data-driven environment that they can feel comfortable in. 

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