Good data doesn’t necessarily guarantee good decision making

Making the right business decision has never been more critical than it is today. Many industries are still in a state of uncertainty as they continue to bounce back from the past 18 months. Data and our data gathering abilities drive intelligent decisions, and the amount of data that we can collect has increased enormously over the past decade. Now we’re seeing businesses dedicating huge budgets to managing the information and using it to make informed decisions. 

However, certain investments in data management can be futile, unless employees can incorporate that information into good decision-making - taking raw data and turning it into workable information. Research shows that data that companies have invested heavily in collecting is not being used correctly and poor decisions are being made. By making sure the correct  data is collected and understood by employees, businesses can save money and make the right decisions for the future of their business and their clients. Having the right data is one thing, but being able to use it successfully is a step beyond.

Why your data needs to be good

Having good data is the bedrock to almost all business decisions. In the modern era, so very few decisions are now based solely on instinct or intuition, but require data and evidence to back up exactly why it’s the right next step to take. Ultimately, any wrong decision could have catastrophic consequences for a business. Therefore, having excellent data quality aids your business decisions, and gives you the right backing to make those all important calls. 

Understanding specifically the impact that bad data can have on your business really will drive home the full scale importance of having strong data, and the catastrophic impact that weak or unhealthy data can have. According to research conducted by Gartner, ‘the average financial impact of poor data quality on organisations is $9.7 million per year’. This statistic highlights the true financial impact that poor data quality can have on your organisation if not maintained well. Ultimately, having good data is vital, and is the real bedrock to decision making. 
However, what’s the point of having good data if you can’t read and interpret it?

The importance of data analysis in decision makers

Having good data is great - we’ve already established that it gives you the foundation to make the right decisions, and provides the safety net that the right call is truly in the business’ best interest. However, what use is good data if those decision makers can’t actually read or interpret what they’re seeing?

There’s a real culture still in businesses of those top decision makers not being ‘data literate’, and being passed the information from those embedded deeper into the data systems across a company. However, it’s a very precarious line. Often, a decision maker is going to be requesting the data analysis from those lower down the chain, and it could lead to inaccurate decision making, or a narrow-minded approach to reading data. Someone who is simply ‘data literate’ and not a decision maker might not have the foresight to look laterally across the data, seeing the bigger picture and the broader  impact. When decision makers are able to read data for themselves, they can not only read the data they’re looking for, but also spot potential weak points in their decisions, or even potentially uncover hidden gems in a business that are previously untapped. 

What’s worst in businesses though is that many businesses still aren’t taking this seriously. Even though spending on big data and analytics products is supposed to surpass $215 billion in 2021 according to the International Data Corporation (IDC), 50% of organisations will still lack the data literacy and AI skills to achieve business value. Essentially, businesses are spending more than $215 billion dollars on a solution where they can’t see or feel the full potential - all because those decision makers might not be able to read what they’re seeing, and perhaps don’t have the ability to interpret the data. Those businesses who do take data literacy seriously are ultimately making the best decisions, the most validated decisions, and are making the most out of the treasure trove that truly is data collection. 

How businesses can turn raw data into usable decision making

Realistically, the biggest challenge as we’ve established is the reading of data and having staff with the right levels of data literacy to be able to take that raw data, and turn it into an actionable and usable decision-making tool. However, there are ways that businesses can build upon their data literacy skills, and ensure everyone is up to the required standard to make the most of the data. 

Implementing a full-scale data literacy program is key. It’s not something that can be self-taught to a high enough standard, and a business can’t rely on individual staff members to all be at the same level. Implementing a company-wide program also begins the process of embedding data literacy into the business culture, ensuring that it’s ultimately going to be around for generations to come. 

It’s also vital that businesses identify areas where data literacy is lacking, and target those areas most in need of improvement. Whilst implementing a business-wide culture of data literacy is important, it’s equally important to remember that not everybody will be at the same stage, and therefore some areas will require more work. Getting everybody onto one level playing field will ensure that data literacy, and the analysis of data across a business is up to the highest, uniform standard, and everybody in a business can be relied upon to make the best decisions based on the data collected.