Data Driven Decision Making | Sperto Consulting

In the modern world where business has more and more access to data than ever before, we must ask ourselves do we utilise the information we gain and if so, how we use this information effectively and use it to drive business growth.

Used correctly any business will benefit by using available data to assist making key decisions and increase profit margins.

Currently the world is being overrun with data. Very often digital behaviour is recorded, but for many companies this data sits in dashboards and databases never to be used. Often, we don’t consider the level and value of information we hold or are unsure how it can be used effectively.

In this edition of the Sperto Consulting newsletter we discuss how data driven decision making can be used, define data driven decision making in full and suggest steps that can assist in the implementation and how any organisation will benefit.

Making use of Data

Firstly, we need to clearly define what is decision making data. Too often we make decisions and strategy based on personal beliefs rather than real intelligence gained by analysing trends, historical information or detailed internal and external feedback. Very often we consider what worked in the past and replicate future decisions accordingly. By using data gained we can utilise real knowledge to optimise our decisions and methodology. There is always an element of risk in any business decision, however data driven decisions leave you much less vulnerable to making errors of judgement and a greater likelihood of a successful impact.

Data driven decision making relies on correctly analysing collected data using defined methods to answer questions, discover insights that can offer informed judgements as well as to determine a strategy and fully informed course of action.

In its simplest terms, when planning a go to market strategy, do we take time to look at past launches, consider what worked and why as well as what didn’t make the impact expected and understanding why.

In a recent business research, it found that whilst 91% of companies say decision driven data is important to their growth, just 57% said that they base decisions on their data. Those that did experienced a profit growth between 8 and 10% and a 10% reduction in costs.

Let us consider also some simple decisions data can assist us with:

In Finance - What’s the most cost-effective way to hire new staff or to promote a new product? What key activities prevent churn of existing clientele?
In Marketing and sales – Which marketing activities offer best results? Which sales activities generatemost leads?
In Customer Service – How can I improve response times; how can I best deploy resources?

Benefits of Data Driven Decision Making

Data driven decision making ensures any business will feel more confident in the decisions reached. Data allows a correct benchmarking of what currently exists, which in turn ensures a better understanding of the impact expected of future decisions on a business. Decisions made are logical and fully supported by information gained. This level of confidence allows any business to fully commit to a course of action or strategy.

Often the implementation of data driven is reactionary sometimes at variance with perceived ideas and company internal beliefs. If the data is accurate, it doesn’t lie and tells a story. Accept this and use the knowledge to drive change. Use it to consider proactivity in a changing world, is it identifying new opportunities or detecting a threat before it becomes too serious?

How to use Data Effectively

Firstly, define the decision needed to be made. No decision can be made until the goal and objective is clearly understood.

Next prepare a plan of action that defines what data you need, what is available and how you can gain the detail needed you do not currently have to hand.

Consider what are your objectives and then prioritise. All decisions need to focus on your business goals.

Having identified the goals targeted, identify, find and present relevant data. Relevant is key here, only collect the data that relates to your objective.

Analyse the data. Look to unearth patterns, trends and anomalies that may indicate opportunities or risk. Consider cause and effect and define any statistics to predict outcomes.

Finally evaluate the results. Did the data gained offer the insight needed. Use KPIs to measure impacts and use this information to consider other areas of the business where a similar action would apply.

Data and the individual

Make a conscious decision to be more analytical, while this may sound simple, it takes practice. Look for patterns, attempt to draw conclusions as to why they exist and occur. This soon becomes a training exercise to develop awareness whilst often allowing true insights.

The most common methods of data collection in business are:

Website analytics. Consider what information is available and how it can best be used.
CRM. Understand what data is being collected, what is its relevance and is it being used and discussed at management levels. Also, to be considered, what information is available but is not being utilised.
Business Intelligence. What decision making techniques have been used previously. Consider, customer feedback, testing, cost benefit.
Social Media Platforms. What social listening tools are available, what current key drivers do people consider when making a choice.
Feedback both external and internal. This is especially important as those companies who use customer feedback state that this has contributed to their most successful projects.
Review the historical data you have collected to identify patterns or trends.

Having identified the goal and analysed the data, now you can decide on the strategy to be used. Next what is needed is a plan of action to put your decision into practice.

At this stage, identify clearly defined goals on actions identified. Consider what needs to be done, when and by whom and what is the expected outcome.

Now measure success, with the decision being made and results identified now is the time for a review. Look at the original data and compare the historical data with the new data collected. Now consider, did your action have a positive impact on the business. What worked most and least effectively, what did we learn.

Thomas Edison said on the invention of the lightbulb, ‘I never failed, I just found 10,000 ways that didn’t work.’

Things to bear in mind

The economist states that Data is the Worlds most valuable resource, more so than oil. Owning that data reflects an enormous amount of power. An often-repeated line says, ‘With great power comes great responsibility’.

High profile data breaches have resulted in consumers being more and more concerned about how their personal data is used. It is always good practice to be clear how and when data is collected to comply with legal standards and in turn guarantee the safeguards used.

Examples of Data Analysis in Practice

Leadership development at Google.
Google focuses on people analytics. Data was mined from 10,000 performance reviews and compared the data with employee retention rates. The information was used to identify common behaviours in high performance areas and develop training to highlight these competencies. A 20% increase in scores resulted.
Real Estate Decisions Starbucks.
In 2008 hundreds of Starbuck locations were closed. A decision was taken to consider a more analytical approach to identifying future locations. Using demographics and traffic patterns as well as input from regional teams, this data is considered to determine the likelihood of success before a location is chosen.
Amazon Driving Sales.
Amazon identifies data to decide what products to recommend to customers based on prior purchases and search behaviour. It is accepted that 35% of Amazon consumer purchases can be referred to the recommendation system.

Conclusion

There can be little doubt that data used correctly and efficiently is a valuable, in a fact vital tool for all companies with the most successful using available data as the core of their decision making to reduce costs and increase profit. If data can be used to prove a course of action, then those actions are more likely to have a positive impact. Use your CRM, Customer feedback reports, sales dashboards etc. next time you need to make a decision. Now consider the tools needed to store and make available information going forward.