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What is data maturity?

Written By

Sab Caziuc

-

February 19, 2020

in

data

READING TIME ~

3

MIN

You might have heard over and over again that we now live in a world of data and every company seems to have gone mad for it. 

The CMMI Institute reports that “52% of leaders believe the ability to analyse data improves their decisions.” But how does the structure of the data influence its ability to provide a competitive advantage? And why are not more company leaders using it?

First, let’s look at where data sits in the fuel retail business through Deloitte's Data Activation Framework.


What are a fuel retailer’s strategic choices?

  • The geographical considerations of your gas stations
  • The size & facilities of your forecourt
  • The fuel brands you select based on the clients, competition and cost prices
  • The method of financing new developments
  • The supplier selection 

How does a fuel retailer use the data to support your strategy?

  • The pricing strategy by region, by brand or by site
  • Procurement - order when it’s critical or when it’s cheaper
  • Promotions and loyalty schemes

Data - the backbone of your business

Fuel retailers are well known for scrutinising everything. Your business presents data in different shapes from multiple sources - the POS, the pumps, the fuel supplier, the accounts, even from your competitors! 

All of it is filtered through technological tools - PDF reports, Excel files, emails, faxes and so on. You trained your team to work with all these tools and use the data in particular ways.

When you need to take a snapshot of your business for a critical decision, what would you rather look at?


Jackson Pollok; Leonardo da Vinci

Whilst we are by no means art critics, the same information (colour) can be displayed in different ways to convey the entire spectrum between hidden messages to clearer and simpler ones. 

What’s the difference?  The way in which the data is being organised and used, which is how data maturity is defined - and there are tiers:

1. Nascent -  Data Immaturity 

  • Manually compiled data as it comes from all the sources
  • Not standardiser and ready to use
  • Difficult to handle
  • Typically used for setting and tracking basic KPIs
  • Unclear how else it could be used

2. Developing - Data Management & Exploration

  • Data neatly organised
  • Still has to be manually accessed
  • Can shed some light and provide background around the KPIs
  • Serves as reference point for future planning

3. Maturity - Data Aided 

  • Well organised data, automatically formatted in the form you need
  • Ready to come at your fingertips when you need it and in the format you need
  • Provides a detailed analysis of the patterns identified in your business
  • Serves to guide your business decisions
  • Its timeliness and agility allows you to act on it immediately
  • Similar to a transition from using printed maps to Google Maps / Waze

4. Leading - Data-Driven

  • Smart, high quality 
  • Machine Learning algorithms are taking over the previous methods
  • Embedded in all your key decisions and processes
  • Identifies issues and spots opportunities before they even happen through predictive analysis
  • Suggesting the best courses of action so you can become a market leader

If you’re wondering how digitally mature your company is, Google created a special tool.

Thinking of how you define success in the medium to long term, what level of data maturity does your business need to reach?


Insights and stories from the EdgePetrol team.

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