I calculated that during one week I made more than a 100 decisions. I started to wonder would my decisions have been different if I had had more time and better analyzed and good quality information available.
Everyone makes multiple decisions daily or weekly. Decisions can be big or small and can relate to business, private life or even politics. I calculated that during one week I made more than a 100 decisions. Decision making can be fast and intuitive, but also fact-based and analytical or any combination of these. My decision making process varies a lot depending on the possible impact. When I decide what I will eat for dinner, I hardly collect any facts or do a deeper analysis on menu alternatives, because I know that my decision will only affect the atmosphere and feeling of one evening. But if the decision will affect the whole family or a large group I might do little deeper analysis on people’s taste, diets, allergies and preferences as well as the costs.
In business, decisions impact the company, the employees, the customers and other stakeholders and should be based on facts and data, but I believe that they are still too often based on intuition and a ‘gut feeling’. You need to decide within a very short timeframe with limited data or nowadays more often with too much data. A typical decision making situation is when a colleague or an employee asks for advice or a decision on a topic where the deadline was days ago, and you haven’t had time to read the background material i.e. a 50-page long summary of the situation. Then you quickly ask a few key facts and maybe ask the opinion of the questioner and make a decision. Your decision is based mainly on intuition and a few facts that you collected during the discussion. I find myself in this situation often.
I started to wonder would my decisions have been different if I had had more time and better analyzed and good quality information available. And what if analytics would not have only been based on history but could have also taken into account future scenarios? And what if I could have combined this analyzed data with my intuition and done some simulations? I realized that even if I had had all the data and technology available I still might not have had the time or skills to do the analytics myself. That is another challenge to solve.
I began to look for scientific articles and studies about this topic – decision making with and without analytics and whether there were any differences between the results if the decision was based on analytics or only intuition. Unfortunately, I could not find that many studies from public sources and for someone like me, that is not a specialist in brains or physics. I wanted to find neutral and independent studies with hard economic facts and figures about the (business) outcome of decision making with and without analytics.
I found one study by McKinsey (source: McKinsey & Company, “Using customer analytics to boost corporate performance: Key insights from McKinsey’s DataMatics 2013 survey.” January 2014) in which companies in the area of customer analytics were studied. Some findings from that study are that the companies that use analytics in marketing and sales have a 50% better likelihood to increase sales, they have a 23 times better outcome in customer acquisition, 9 times better customer loyalty and a 2,6 times better return on investments in customer management. So, decisions with the help of analytics improve your company’s results. I believe in this, but it would be interesting to have more independent studies to demonstrate this.
Another interesting study was conducted by PwC, where they studied strategic decision making (Source:http://www.pwc.com/gx/en/issues/data-and-analytics/big-decisions-survey/industry.jhtml?WT.mc_id=cs_gx-hero-home_Data-analytics). 94% of the managers and directors are ready to make decisions on strategy and ‘big issues’ related to the company’s future, but only a third of the directors had relied on data and analytics when making the latest big decision for the company. Mostly the decisions were based on their own experience, intuition and advice from colleagues and advisors. The main reasons for this situation were poor data quality, insufficient data and the fact that relevant data is hard to find.
So I belong to the majority of managers in my decision making process. And I share the feeling of not trusting the figures and the reports. I definitely would like to base my decisions on better analyzed data, but the main issue and challenges are exactly what the PwC study says: data quality and data relevance. Too often my intuition says that this report cannot be right, so am I wrong or is the report or data incorrect or is the data in the report irrelevant?
In my opinion the real issue is not technology, because today, new technology and tools bring analytics and report generators to everyman’s desktop. Self BI-tools are here to stay, but if you cannot trust the figures, or read the relevant data into your graphs, the ‘self BI’ analyses and reports are useless.
Then I started to think about how to solve this dilemma. I need better analyzed data and even though good tools are available but I cannot trust nor have I enough time to interpret the figures. If I had a personal analyst as a service, a person that has time to work with the data, a person I could trust and who is a professional in reading and analyzing large amounts of my data, this analyst could find the relevance in the data and see if the data is correct and what conclusions could be drawn from the data. And even better if this analytical person could be available as an outsourced service for companies and people like me. Like a doctoral service, you use the service and then pay for what you use. There must be many managers with similar decision making challenges. That’s why we at Avarea introduced MyAnalyst service to the market. A manager needs more than tools and data, he needs a person who can do analyses and with whom he can discuss the outcome of the analytics. A team that is passionate about better decisions!
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