December 27, 2019

The importance of purpose when doing data analytics

Organisations can easily be overwhelmed when considering large projects involving digital transformation. The size of a project can hinder an organisation’s ability to execute efficiently.  

This is particularly true of integrating data analytics, which should be an integral part of any organisation’s data strategy. Coupling data analytics within a wider data strategy can give drive to your analytics programme. However, it is not enough to simply analyse raw data and hope to infer insight from it. 

It’s important for an organisation to ask why it’s employing data analytics. Without a clearly defined sense of purpose, organisations often end up putting their raw data in a data lake where they don’t do anything with it. In cases like this, insights and value will be lost forever. 

 

Capture, then analyse

capture-then-analyse

Data analytics has the potential to transform how organisations organise, operate, manage customers, and create value. And its potential is growing as data volumes grow exponentially. 

As we know, the proliferation of data is increasing. Data can now be acquired from a broad range of sources. In recent years, the explosion of social media, as well as the increased use of apps to assess and manage our personal finances, has further driven data growth. It’s vital that forward-thinking organisations capture as much of this data as possible. If it gets wasted, valuable learnings will be lost and competitors will take advantage. 

Capturing data is only the first part of the puzzle. Data needs analysing – and that’s where data analytics comes in. Advanced data analytics tools can help organisations to learn from data, make informed decisions, attract new customers and drive growth. 

 

The wrong way to start 

How to get to this outcome? First, you need to ask the right questions.

This isn’t easy. In fact, many organisations, in the face of lightning-quick change and widespread digital transformation taking place all around us, can feel overwhelmed by the need to participate. As a result, they begin a project, such as data analytics, for the sake of it. 

The desperation to employ data analytics is one of the reasons why organisations do end up putting their data in a data lake or cloud solution without understanding what to do with it. They know that they need to capture it. But they don’t know what to do it with it once captured. 

Organisations cannot just say, “give me an analytics solution”. This is too broad. In these cases, an organisation is starting with the wrong question. They’re asking, what should I be doing? Rather, they should be asking, why should my organisation be undertaking data analytics and what value and insight can I get from it? 

 

The importance of purpose 

When an organisation asks “why”, they better understand what it is that they want to achieve. This question can help decision-makers to refine a sense of purpose that shapes the type of data analytics they want to employ. 

There are many reasons to pursue data analytics. Is it because they want to gain a better understanding of customer behaviour? Or is it because they want to optimise internal operations? Or do they want to make better investment decisions? 

An organisation needs to get to grips with the reason behind why they want to get the most out of their data.

 

Data analytics in action

data-analytics-in action

For example, let’s say a financial services company wants to use data analytics in order to gain a better understanding of customer behaviour. Data analytics can be employed to:

  1. Build a picture of the customer journeys and characteristics that identify features and events in the sales process that show the likelihood of onboarding a client.
  2. Construct behavioural profiles for customers based on their transactions, highlighting anything at odds with existing beliefs. This feeds into the company’s marketing.
  3. Use learnings gathered in steps 1 and 2 to build a predictive model for future customers. 

By setting out with a clear purpose for its data analytics – it wanted to better understand customer behaviour – this company increased the success of their onboarding journeys, promoted growth and lowered their costs and wastage.

 

Purpose and clarity

Organisations can get stuck when contemplating data analytics. With so much data being generated, people can panic and begin employing data analytics for the wrong reasons. After all, getting insight into the wrong thing is just as bad, if not worse, than gaining no insight at all. Hence, it’s vital that organisations ask the right questions when data analytics is concerned. 

However, with a sense of purpose, an organisation can embark on a specific analytics solution that fits with their wider data strategy. This allows them to take stock of their requirements on a more granular basis and this, over time, will provide greater value and more positive outcomes. 

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