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Connecting the data dots

Linking analytics to decision-making is imperative in order to drive performance.

Nicholas Bell
By Nicholas Bell, CEO of Decision Inc.
Johannesburg, 24 Mar 2015

In my previous Industry Insight, I outlined what affects the decisions that people make. Referencing a Harvard Business Review article: "Why good leaders make bad decisions", by Andrew Campbell, Jo Whitehead, and Sydney Finkelstein, I discussed how humans depend on two processes for decision-making: pattern recognition and emotional tagging.

In making decisions, the brain assesses information using pattern recognition, and the person reacts to that information - or ignores it - because of emotional tags that are stored in the memory. Both of these are normally reliable and they are part of the human evolutionary advantage, but they can cause issues in the decision-making processes of companies.

Companies trying to drive performance improvement need to harness pattern recognition in order to build repeatedly, and minimise the impact of emotional tagging on information processing. In order to that, it is important to understand the process of decision-making.

Decision-making begins with defining the problem to be solved, specifying the goals, gathering information, generating and analysing options, identifying trade-offs, predicting the possible outcomes with regard to risk and uncertainty, and, in the end, an act of deliberate choice.

In general, people make decisions to try to move towards a better future. The challenge for companies is that in many leadership situations, there may be too many or too few people with authority to decide; resources may be dispersed; and a lack of clarity in people's goals can also impact on how decisions are executed. Incomplete information, and the inability to source the required information in an accurate format, as well as social and group influences and many other factors, stands in the way of reasoned and rational choice.

Brain power

Humans, however, do have one powerful trait, through conscious deliberate examination of past experiences and imagined futures: they can learn, adapt and advance. In the article: "Advanced leadership and decision-making: An essential skill 3", Professor Daniel Gilbert stated the brain is an "experience-simulating machine". People do not have to experience all the bad things to know what is good. Yet, when imagining the future, people inevitably leave out many details that matter just as much as the things they include.

Furthermore, it is hard to escape the influence of how people feel in their present state, which colours what they want in the future. Therefore, their predictions are often incorrect or incomplete, which has important implications for decisions made by leaders.

In implementing effective decision-making, companies need to decide how they plan to enable staff to make better decisions. Companies must also understand how to leverage the benefits of the brain as an experience-simulating machine through pattern recognition, while minimising the impact of emotional tagging in decision-making.

With companies investing in technologies and storing large amounts of information around the history of how the organisation, its people and staff behave, there is the opportunity to learn from the patterns of prior behaviour. What this means is people can study their history in order to understand, based on certain variables, how all of these components react.

The process of systemising this information can be achieved through the implementation of an analytics solution. Analytics solutions provide users with the tools to assist in understanding their information, as well as providing a more rigorous framework in defining the type of decisions that users are required to make. The concept of guided analytics is defined as laying out the constituent parts of an analytics solution in such a way that a logical path is followed from the initial visualisation, until the realisation of the final answer.

These analytics solutions allow the company to understand how best to present information to users that will give them the ability to make the decisions required in their daily role, while minimising the negative impacts of human behaviour on decision-making.

The process of implementing analytic solutions should follow the process of decision-making and overcome as many of the identified shortfalls as possible. The process of implementing analytic solutions should start with problem definition, state what the intended organisational goals are, identify how the information is to be gathered, and whether the information is accurate and reliable, and then present the information in a way that will allow users to make an informed decision.

All about application

But, if analytic solutions are the answer, and Gartner continues to predict that the implementation of these solutions remains the primary agenda of CIOs in 2015, why does Gartner still predict 70% of these initiatives will fail? The answer lies in how companies implement analytic solutions.

In many leadership situations, there may be too many or too few people with authority to decide.

In conducting this study, I undertook an internal research project on the returns my clients were able to gain through their investment in analytics, and the impact the performance has had on their business. I was able to classify two distinct groups of companies and was able to identify the characteristics that existed with the successful companies versus the others. This is not to say only those were successful - all have been able to gain improvement; however, certain have gained an exceptional return and have experienced remarkable improvement within the business's performance.

I identified six key characteristics about these businesses that were common among them, and believe where these principles exist within the business, they have a higher propensity for success.

1. The business has a strong desire to improve, and this goal is shared across functional executive roles.

2. The executives understand the opportunity and competitive advantage that exists through analytics and wholly support analytic projects.

3. The IT department is supportive of the initiatives to drive improvement - both business and IT sponsorship is key to success.

4. Information is used throughout the company to make decisions.

5. Business leaders and executives value information and consider it a competitive advantage; they drive this culture through the company.

6. The company utilises best practice BI tools and methodologies, engaging with a focused partner that measures their success in terms of the extent to which they have improved the decision-making capabilities of their client.

Companies must understand the process of decision-making, and implement analytic solutions to guide users to making the decisions that will drive company behaviour. However, in order for analytic solution implementations to be successful, companies need to embrace a number of factors to ensure the solutions will be adopted and effect the required change.

In order for the company to drive greater performance, it needs to create a clear link between the decisions that people are being tasked to make and how those decisions drive performance.

Keep an eye out for my final Industry Insight, where I will discuss how to understand what decisions need to be made, and how to audit the company to assess its decision-making maturity.

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