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Embracing change: Education changes the value of data

“Education changed my life,” said a friend and leading academic in his retirement speech.

He could say this because he was the first person—in his whole extended family—to ever go to university.

Education is a powerful thing. Education is key to changing how people think, live, and act; for example, it promotes equity, closing the gap between race divides, health disparities and gender roles. With education,comes changes in perspectives, the transformation of attitudes and the breaking down of barriers. 

Education can also change organisations; this is especially the case, when it comes to data.


Consider this true story: In the final year of his university course, Alex began working for an organisation as a project analyst.His exposure to data? His science-based university course meant he had to compile and analyse statistically based data. To do this, he taught himself advanced Excel. 

Induction training for information and data was an“Information Management” course, taught online, which educated Alex on the importance of records management. It also taught him how to lodge and retrieve documents in the records management system. Other induction courses included chemical handling, ergonomics and fraud.

Two years down the track, Alex had successfully advanced two levels in the role. His division looked after significant assets: in fact, $1B worth of assets. His role as project analyst was not only to undertake new related initiatives for the division but also to ensure that the information on these assets was of “high quality”. He decided and used Excel to manage these$1B assets. The organisation continued to allow him to do this, consuming the data that Alex and his team curated within its corporate remit.

Alex put the whole organisation and its clients at risk because of a lack of education on how to handle data.

Alex’s story is the story of anyone whose organisation does not: 

1. Decide data is a valuable asset and treat it as such.

2. Put the systems in place so the management of data can be optimised.

3. Educate its people by enabling, supporting and rewarding them to use the systems to manage data properly, as a valuable asset, just as with finances.


How can we begin to change this in our organisations? These steps guide the way:

First, prepare for action:

1. Identify your organisation’s key business activities and projects and impress on your execs the need to prioritise them. You may want to try the Pairwise Comparison approach.

2. Identify the data needed for each business activity to be executed.

3. Determine the data quality needed for each business activity to be successfully executed.

This identified data and its quality (linked to business activities) are your prioritised data requirements for your main business initiatives.


With your prioritised data requirements determined, you can then commission systems.

1. Define what data issues are. For ideas, look at events where the business outcome was substandard: what’s contributing to this is likely to be issues with data.

2. Commission a capability of Data Architecture.Architecture is the keeper of all data requirements; it is the approved authority on appropriate ways to collect, process and use data.

3. Commission a data issues management process and system.With luck, you will be able to piggyback off an effective IT issue system already in place.

4. Upgrade your corporate-wide project management right from the initiation phase to:

– define data requirements

– consult data architecture and

– utilise data issue management processes.


Finally and most significantly, educate your people on:

1. What is a data issue and how to spot one

2. How approved corporate systems are used to:

– Record issues accurately and descriptively

– monitor an issue through to its resolution and

– ensure knowledge derived from solving the issue is consolidated for future troubleshooting across the organisation.


When initiating a project, additional mandatory steps are:

1. Define data requirements along with how we will know each requirement is fulfilled

2. Consult data architecture to specify appropriate ways data will be sourced, processed, stored and produced and

3. Escalate data issues using approved corporate systems so the wider organisation can benefit.

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