Data as an asset

I have recently had to reflect and read on data and data governance and its relevance in today’s digital world. As a result of my immense learning on the topic, I would like to share with you what I personally think is the importance of data governance in any organisation thinking of itself as a data driven business and how they can subsequently achieve value from fully adopting it.

Data governance is an ongoing program where both organisation performance and data quality is measured. In doing so, quantitative and qualitative metrics are established to measure performance and drive a cultural shift to data as an asset.

Organisations today chiefly consider data governance a compliance issue more than it being an investment and asset to their businesses. I would therefore like to challenge this notion and suggest that we look at the data in its holistic view and perhaps learn the unspoken value and returns on investment from it.

For a moment, let’s assume you need insights on the performance of your service or product and before you could make a decision, you probably question the quality, credibility, reliability and completeness of the data being looked at. This is the point where it gets really interesting and data governance wins a cup of being highly prioritised and this is because it is then when you realise the importance and value in promoting data governance program within your organisation.

I am fully aware that your organisation might have data governance programs as expected by regulation bodies and as well as your organisation’s drive to draw actionable insights from the data you collect and store. However, do you then believe that your organisation is investing enough in data governance for optimal level of confidence in the use of its data? If not, let’s continue to read as I am going to continue to highlight the challenges faced by organisations with regards to data and how proper implementation of data governance could just be the ultimate solution.

1.  Organisations share a common vision and that is them striving towards being data driven organisations. And as they are stepping into this milestone, their people find themselves fine tuning and troubleshooting errors in reports and analytics required for decision making or other purposes.

This on the flip side could result to grave consequences and create problems when and if one who works with the data is not aware of data quality issues and/or do not understand the data enough to tell when insights and reporting is anomaly and not true representation of actual events.

2.  Organisations often find themselves collecting and using data from multiple systems and a likely mistake from this could be inconsistent data definition, resulting to data being wrongly analysed and subsequently misleading those who make decisions out of it.

3.  Finally, organisations tend to find themselves reacting to these challenges because of the pressure from the regulation bodies and finding themselves resolving data governance issues as a non compliance challenge at that particular point in time and not realising that as they do that, their initiatives are further not catering for new data coming in during the movement of time and leading to continued frustrations in the boardrooms.

In tackling this, I would draw from the learnings from my second year Internal Auditing class, the control measures namely, (1) preventive, (2) detective and (3) corrective that organisations could start adopting to minimise data related risks.

From my observations I realised that most organisations fall victims to the short of agility and pro-action, i.e. leaning more to being reactive to data governance challenges and not because they’re not doing anything but because it is convenient to focus on immediate goals and objectives than long term initiatives that they 'supposedly' hardly have time to invest in.

If I were to propose any solution, I would first suggest that organisations prioritise People Agenda that is in the core of this topic and secondly ensure that Processes of data governance are being properly established and defined for smooth functioning. And finally leverage available technologies to enable results and achievement of organisational objectives.

In one of the next blogs I will go into detail around the whole process, i.e. data collection, storage and usage and will also highlight existing challenges in each of these three phases to shed some more light about how data governance plays a role in the whole data development cycle.

This blog was to create awareness on data governance and moreover trigger your interest to do more research and learning on the topic to subsequently initiate productive engagements with your colleagues and friends in the field.