Earlier this year I had the pleasure of interviewing Ram Kumar from IAG (Director of Enterprise Information Management) regarding Data Governance and its impact. As an Analytics and BI recruitment consultant I have noticed an increase in organisations who are realising the impact of data governance. However, there is also a lot of confusion as to what data governance actually entails from both organisations and specialists. With this in mind I thought I would find out from someone with far more experience than me.

LY: Given your background what was it that got you into the area of data governance

RK: I’m not a data manager or data governance specialist by profession but given my strong background in information technology what I quickly started to realise long time ago is that majority of the organisations have been focussing on technology, processes and the people to drive business outcomes with no focus on data.

What organisations fail to realise is that it is the data that brings technology, process and people together to drive business outcomes. This is why data is called the “lifeblood” of an organisation as it fuels people, processes and technology. Without data, you do not have a business. It is like blood in your body. Your blood fuels your body to operate. 

An organisation might have the smartest and most efficient business processes, highly capable and smart staff and the best technology, but if the underlying data that touches people, process and technology is poor in terms of its quality and integrity, the outcome will be poor.  So, for the last 17+ years I have been pushing for data driven organisation culture to maximise the generation of value out of data through effective and efficient governance of the lifecycle of data assets.

It has been a long hard battle as it is people that provide the challenge. Technology and processes are the easy bits.

LY: I notice in the industry that there seems to be a lot of confusion about data governance and what it entails. In your opinion what is data governance?

RK: Data is a core strategic asset of any organisation and should be governed like any other asset over the full lifecycle, from collection through to categorisation, storage, use and retention/destruction. Governance also includes management of privacy, security, data quality, master data and metadata management, and must be assessed over its full lifetime  rather than in a bits and pieces fashion.

LY: Why do you think there is such confusion in the industry when it comes to data governance?

RK: The number one reason is that traditionally organisations never saw data as a strategic asset and, as a result, managing the data was seen as IT’s role. IT is just a gatekeeper/custodian of data and does not own data.  The latest phrase that is being used is “Data is the new oil”. Well, it always has been it’s just that organisations never realised it, as data was never considered as a strategic asset. This whole new movement to a data driven world (thanks to Big Data), is seeing organisations realise that data governance is critical. But many are confused about how to develop this capability.

This has resulted in the creation of the Chief Data Officer (CDO) role which is being given responsibility to help drive data driven business outcomes by working with CxOs such as Chief Analytics Officer, Chief Marketing Officer, Chief Digital Officer and the Chief Information Officer.  Many ask the question why we need a CDO when we have a CIO? I would answer that most CIOs are busy doing IT related tasks only and never focus on the “I” in their title, the “Information”. The person managing the information asset lifecycle is handling the “crown jewel” of an organisation which is different to managing the IT assets. I would prefer to describe a CIO’s role as “Chief Information Technology Operations Officer”.

Applying traditional data governance practices will be a challenge in this fast paced, high volume and volatile data environment as it could curb speed to market with new innovative products. How you get the right balance in terms of innovation and speed to market while providing controls through data governance is now a hot and interesting topic. 

LY: In your experience, what are some of the common alignment issues most organisations face?

RK: The biggest problem is getting understanding and support from the top, i.e. the Board and CxOs, to treat data as a corporate/strategic asset. The value of data is often questioned. My answer to  ask them to imagine the case of an insurance company generating a revenue of say $100 million in Gross Written Premium (GWP). If we just remove all the data from the organisation and leave it with just people, process and technology. What is the GWP of the company? $0.

The Board and senior executives must understand and treat data as a corporate strategic asset to maximise the value of data and take “ownership”. If this happens, it will drive data driven culture across the organisation.  You need in accountability and to lead from the front if you want to drive cultural change. Doing analytics with data to uncover insights does not mean an organisation is data driven.

Analytics is one component of the lifecycle of your information assets. An organisation managing its information asset lifecycle effectively and efficiently to generate “value” out of it to drive business outcomes is what I would call as a truly data driven organisation.

LY: How do you structure Data Quality Management within a Data Governance framework? What does a typical roadmap look like?

RK: Data Quality Management is fundamental to Data Governance Framework.  Data Quality should be embedded as part of the data culture in an organisation. This means planning for data quality at the planning and conceptualisation stage of any initiative that involves data consumption rather than being an afterthought that would result in data cleansing activities.   A typical roadmap would include skills, capabilities, tools, processes, monitoring and measurements/metrics.   It is important that a dedicated team looks after data quality by working closely with business and IT.

LY: So far, we’ve talking about traditional structured data. What about newer, less-structured data such as social media feeds–doesn’t that complicate the notion of “data quality”?

RK: This is becoming a major issue for organisations now. At least with internal data assets, an organisation could apply some key data quality measurements such as validity, trustworthiness, frequency, accuracy, etc. to measure the quality of data. But some of these measures are not applicable to data coming from external sources such as social media. Traditional approaches to data quality do not work in a big data type environment where we have to deal with huge volumes of data at high velocity and volatility. Moreover, advanced analytics methods use machine learning algorithms that are designed to handle certain percentage of noise in the data as they use the concepts of identifying “patterns” in data. But combining traditional data assets with the new external data assets (e.g. social media) to generate new data products makes the problem more interesting from data quality perspective.  This is an exciting area that industry will be looking at in the future. 

LY: On a local Australia level who do you think is doing data governance well?

RK: A couple of years ago, Deloitte surveyed the maturity of financial services organisations in Australia in managing their information assets.  The result was 2.4 out of a maximum of 5.  I am sure banks are be in a better position in data governance over other verticals due to the tight legal and regulatory requirements they have to comply with.  My view is that this will change with legal and regulatory bodies starting to closely look into this whole area of data security and privacy.  For example, the Australian Prudential and Regulations Authority (APRA) has release a Data Risk framework as a guideline for organisation to manage its data assets which looks at the lifecycle of data.   

LY: It’s one thing getting people to embrace this at the c level but what about the people at the lower level, what challenges do you think they will have?

RK: Traditionally in organisations, in any project of any size, the last thing people worry about or even think about is data management. Even if some funding is there for data management, in any budget situation, data management is the area that gets cut. Appropriate training programs should be implemented to raise the awareness of the importance of lifecycle of data management to all staff in an organisation. In one of our business divisions, we have included rewards program for staff capturing quality data which has been a huge success.

LY: What changes can we expect in the future?

RK: Today big data, maybe tomorrow it is massive data, but the principles of data management do not change as data is data irrespective of its size. What will change are agile and better data management principles. Data privacy is a subject that will be discussed a lot in the future.  As organisations are streaming ahead to provide one to one personalised customer experiences through advanced analytics by combining different sources of data about a customer, the issue around privacy and ethics will become an important discussion point.  Data management and effective use of data will also determine an organisation’s success in implementing an effective digital transformation particularly when providing digital experiences to customers.  

Leon Young is a Recruitment Consultant at Aurec based in Sydney specialising in Big Data and Analytics. Contact him on 02 9993 1068 or email at: lyoung@aurec.com