Today, 90% of business professionals state that data analytics are key to their organisation’s success, with many believing that without the use of data to drive decision making, achieving the firm's potential would be near impossible. However, with much stock still put in the power of gut feeling, the question arises, is data driven decision making truly as advantageous as marketed, or is it simply a trend that has gained traction in our increasingly digital world?
Data driven decision making, sometimes abbreviated as DDDM, is the process of utilising data to help inform an individual or group decision making process. This is done through a provision of information that validates a course of action prior to committing to it. In modern day business, this can take many forms, such as; a collection of survey responses, user testing, market research, or trend analyses, all of which help to determine an organisation's strengths, weaknesses, opportunities, and threats. However, exactly how data is incorporated into the decision making process will of course depend on numerous factors, like the types of data you utilise, the quality of data available, and the organisation's goals and aspirations.
Once firms commence the process of both collecting and analysing data, they often discover that data can actually performs multiple roles. Whereby, it not only serves to benchmark what currently exists within the business, which allows better understanding of the impact that any decision will make, but it should also instil confidence. This confidence should be with both the decision maker, as well as the firm as a whole, due to the logical and concrete nature of the information. This in turn, provides a platform from with to fully commit to a particular vision or strategy without being overly concerned that the wrong decision has been made.
As a result of this, today’s largest and most successful organisations have integrated data into their strategic focus, in order to justify high-impact business decisions, with success stories being published on the work done by Google, Starbucks and Amazon. When you delve into the statistics, it's understandable why many organisations have followed in the footsteps of these giant firms, with research by BARC stating that, businesses using big data saw an 8% increase in profit, as well as a 10% reduction in costs. In addition to this, companies surveyed also listed other benefits from their transition to monitoring data, through which 69% cited better strategic decisions, 54% boasted an improvement in control of operational processes, and 52% stated that they had a better understanding of their customers as a result.
These findings are further supported by the Mckinsey Global Institute, who in their studies saw that data driven organisations were not only 23 times more likely to acquire customers, but they are also 6 times as likely to retain customers, and 19 times more likely to be profitable. The organisation concluded that their research had shown that leveraging this data enables enterprises to make more informed decisions, in addition to improving their customer experience, which resulted in satisfied customers who continue to return again and again.
However, just because a decision is based on data does not necessarily mean that it is guaranteed to be correct. This is as, while the data might illustrate a particular pattern, or suggested outcome, if the the data collection process or interpretation of said data is flawed, then consequently, any decision based on the data would be inaccurate. Therefore, to combat this every business decision should be regularly measured and monitored in order to ascertain the impact. If done correctly, it will become increasingly easier to reach a confident decision about virtually any business challenge, whether you’re deciding to launch or discontinue a product, adjust your marketing message, branch into a new market, or something else entirely.
Therefore, if you have the goal of becoming increasingly data driven in your business approach, there are several steps that you can follow, which will allow you to reach that goal. These are as follows;
Search for patterns and correlations - to put it simply, data analysis is the continuous search to identify patterns within, or correlations between, different data points. It's from these patterns and correlations that insights and conclusions can be drawn. Therefore, to become increasingly data driven, make a conscious decision to be more analytical in your approach to business practices, through the search of trends in the information available to you.
Link every decision to data - whenever you're presented with a decision, ensure you avoid gut instinct when determining a course of action by instead applying an analytical mindset. Do this by identifying what data you have available to you which can be utilised to inform your decision, analyse it, and use the insights gained to guide your choices. If for instance you find that there is no data available, you could consider gathering your own.
Visualise the purpose of the data - whilst it's practically impossible to derive meaning from a table of numbers, by transforming the data into engaging visuals in the form of charts and graphs, you will be able to promptly identify trends and draw conclusions, from which decisions can be made.
To conclude, though intuition can be a helpful tool, it would be a mistake to base all decisions around a mere gut feeling. This is because, whilst intuition can provide a hunch or spark that starts you down a particular path, it's through data that you verify, understand, and quantify the best course of action. In a report by PWC which surveyed in excess of 1,000 senior executives, the firm identified that highly data driven organisations are 3 times more likely to report significant improvements in decision making compared to those who rely less on data. This along with the other statistics quoted throughout this MiBlog is exactly why data driven decision making is here to stay, and why for us at MiGrowth, we see it as the future of recruitment. To the extent whereby, we've built our model around utilising scientifically proven recruitment methods, centred on data, to help businesses source and assess talent. Through this approach, we utilise our MiAssessment software to provide hiring managers with data on candidates' cognitive ability, integrity, and workplace preferences before they even meet them, thus facilitating justifiable decisions that not only save time, but money too.
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