This piece is the second blog in a series, following on from an earlier article ‘How to make data a habit’, in which we explored how brands and marketers should always be asking “Do we have the data to answer that?” when faced with thorny issues.

Essential to answering this question is development of a Data Landscape Definition (DLD) which seeks to lift the veil on the sources and repositories of data that exist across the organisation and help marketers to better understand the opportunities and gaps that exist.

In order to develop this definition, which will go on to underpin all data-based decisions across the business, marketers and key decision makers should aim to answer these four key questions:

Ask yourself, what is a DLD?

At its simplest, a DLD takes the form of a diagram detailing theinteractions between systems and offers a holistic overview of the collective data and data-systems a business has access to. Taken to the nth degree it can comprise an overview of the organisation (including its divisions and departments), a detailed description of each system, those managing and handling data, and the logical design of the systems and a regular audit of the data held.

But no DLD exists in isolation and there is no right or wrong approach. It has to be accommodated into general business and marketing practice and reflect the organisation’s it operates in and its business goals, people and processes. These might include: longer-term business goals; key people; personal data processing; and industry standards.

Ask yourself, why do it?

Simply put, if you don’t understand your data landscape then you are unlikely to understand all your data. And if you don’t understand all your data, you are unlikely to be executing effective marketing, product development or business strategies. Potentially leading to some fundamental and costly mistakes.

At its core, a DLD allows a business to understand the big picture and ensure relevant data is freely flowing, in a timely manner, to the appropriate point of use. But at the granular level, it furnishes decision makers with a point of reference to make informed decisions and ensure they are doing things right to meet business objectives and long-term strategic goals.

This is becoming increasingly relevant as we edge ever nearer to the landing of the General Data Protection Regulation (GDPR) updates, now just over the horizon, and the upcoming Privacy & Electronic Communications Regulation (PECR) overhaul.

Ask yourself, how to define a data landscape?

Think of your DLD as a living, breathing ecosystem that continues to evolve with your business in a format that suits its ever-changing needs. It is easily broken down through a simple checklist:
• Start with a straightforward inventory. Define the divisions, departments and third parties that comprise your data landscape and the customer touchpoints that exist;
• Identify the systems used by each division and department and that sit behind the touchpoints available to customers. And be comprehensive!
• Identify where these systems are shared and how information is exchanged;
• For each system, define the primary inputs and outputs and then take this further, and define the method of data capture for each;
• Understand the system entities e.g. is the system account, customer or email centric? Does it include contact details? and how well populated is the data?

By examining each of these, the outputs can help decision makers to understand the internal relationships between the systems, processes and the data they produce and use that insight to drive decision making at a strategic level.
After all, the quality of your data (in terms of relevancy and accuracy) and the integrity/authority of your data is key to business and marketing success.

Ask yourself, why wouldn’t you do it?

The GDPR is here. The honeymoon period has started and by May 25 2018 your house needs to be in order.

There is a quiet, and growing, concern that the direct marketing industry’s very own ‘PPI bonanza’ will be borne from GDPR so we should be acting now to avoid that risk. Companies are already starting the journey towards compliance and a detailed understanding of a data landscape is a key starting point to that.

For the data aspects of GDPR, the Data Landscape Definition can provide much of the ‘as-is’. GDPR and PECR define the ‘to-be’. Compliance, then, comes down to identifying, understanding and filling the gaps.

So the question really is not ‘Why do it?’, but ‘Why wouldn’t you?’

 

By Malcome Dunsmore, Business Analysis Manager at Occam

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