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Decisions, decisions

It is imperative to understand the decision-making process and how this can impact a company.

Nicholas Bell
By Nicholas Bell, CEO of Decision Inc.
Johannesburg, 22 Jan 2015

Gartner predicts 70% of all business intelligence (BI) solutions implemented are considered a failure, yet investment in BI/analytics in 2015 remains the number one focus of CIOs. This statistic should give any CIO pause for thought given the increasingly tightening wallet with regards to IT spend.

A top priority for CIOs should be not only on spending more on analytics, but making sure the spend on analytics makes a positive impact on the business, and that projects are considered a success.

Why do so many BI implementations fail? More than half of those are due to technical failures or projects not being completed. The remaining failure is often due to the fact that the analytics provided do not give the business the capability it needs, or the process of linking information with the decisions users need to make on a daily basis is not clarified.

Successful implementation of an analytics solution is not just about the technical delivery of the project and the completion of the scope of work, but also about the way users interact with the solution and drive improvement into the company. While the solution developed may provide the users with the correct information, little work is often done on understanding if the user has the ability to understand the questions they need to be asking of the information, and how they should take that information and use it to drive performance within their function.

A successful analytics implementation, therefore, depends on understanding users, how they make decisions and how those decisions impact the company's performance. This Industry Insight is the first in a series entitled: "Linking analytics to decision-making", where I will explore how to make decisions and how linking decision-making with analytics implementations can improve organisational performance. This first Industry Insight explores how people make decisions, and how this process impacts a company.

Brain power

In the Harvard Business Review article: "Why good leaders make bad decisions", written by Andrew Campbell, Jo Whitehead, and Sydney Finkelstein, the authors found that humans depend on two processes for decision-making. In making decisions, people's brains assess information using pattern recognition and they react to that information, or ignore it - because of emotion tags that are stored in memories. Both of these are normally reliable and they are part of the human's evolutionary advantage. However, they can both let people down.

Pattern recognition is a complex process that integrates information from across the brain. Assumptions are made based on prior experiences and judgments. When dealing with familiar situations, the brain can cause people to think they understand these situations when they actually don't. The speed at which people use pattern recognition also means they may not potentially review and assess if all of the variables are consistent or the same as the prior experiences.

The challenge that companies face with pattern recognition is that decision-making is very often based on experience. In "Gut and gigabytes: capitalising on the art & science in decision-making", a new survey report by the Economic Intelligence Unit (EIU), sponsored by PwC, interviews were carried out with 1 135 executives, 54% of whom were C-level executives or board members across Europe, North America, Asia-Pacific, Africa, the Middle East, and Latin America. According to the survey, executives' intuition or experience and the advice or experience of others in their company was the decision-making mode of choice for 58% of executives.

Mode of concern

This decision-making mode presents two key challenges. The first one is that in order for the experiences to be accurate, the variables often need to be similar or identical. The second is the reality that as companies hire and people move around or out of the company, the new incumbents do not necessarily have the experience or pattern recognition required to make effective decisions. This can be further exacerbated in companies that are growing rapidly and companies that do not necessarily invest in sufficient user training.

Emotional tagging is the process by which emotional information attaches itself to the thoughts and experiences stored in people's memories. The information tells them whether to pay attention to something or not.

The concern with emotional tagging is the reality that those past experiences result in people attaching something to the memory. This can be positive or negative, and can therefore also result in a person making the wrong decision. They can make people ignore certain variables that could be important in the decision.

Emotional tagging is the process by which emotional information attaches itself to the thoughts and experiences stored in people's memories.

These variables include the bias of emotional importance people place on information, which makes them readier to perceive the patterns they want to see. In addition, they can have the presence of distorting attachments which affect the judgments they form about the situation and the appropriate action to take. Lastly, the presence of misleading memories means people place more relevance on certain memories and compare them to the current situation, which could lead their thinking down the wrong path. They can cause decision-makers to overlook or undervalue important differentiating factors.

The challenge that pattern recognition and emotional tagging places on companies trying to drive performance improvement is how do they minimise the impact of these two human traits on how people interpret information; and how can the organisation then improve decision-making across a diverse group of people spread across multiple geographies?

In my next Industry Insight: "How to manage decision-making to perform better", I will outline how it is possible, through understanding how decisions are made, to link decision-making to individual and company performance, and how this can drive improvement.

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