Data Changemakers 4: Sri Kanthadai, Global Insights & Data Lead, Capgemini
The Data Changemakers series is a set of interviews and interactions with people who have spent their careers working in or around data and data management initiatives. They have a vision for the data journey and we want to understand what they have learnt and how that drives what they do today. What are their war stories and what advice can they give others embarking on the journey?
Srikant (Sri) Kanthadai is the head of Capgemini’s Global Data Management practice for Insights and Data. He has over 25 years’ experience focussed on transformation of the data landscape in organisations to deliver business benefits and enable the monetisation of data assets. He enjoys the challenges current trends throw up including industrialisation of data assets exploitation, management of “big data” and issues of data privacy & security in todays’ “open plan” landscape.
Please describe a little about your own background and you ended up working with data?
I guess you could say that ending up working with data was a “happy accident”. I gained a degree in Mechanical Engineering and then an MBA in Finance and Market Research. As part of that I did a lot of data analysis and to help with the market research I took a programming course.
What I really liked was the structure and data-focused parts of programming and I ended up with a job in what was DEC working with COBOL. I got into looking how it was used in distributed computer environments, portability and other aspects on both internal research and external customer projects in APAC. Finally, in 2007 I returned to focusing on pure data with a role at Cognizant Technology Services to set up their MDM practice for Europe.
Would you say that you are a business person or a technical person or something else?
My education was a mixture but my career started in Technology.
“Over the years the business education has really helped me understand how technology applies and how it can help people. I see myself as a business enabler.”
What is your current role and its main responsibilities as they relate to data?
I lead Capgemini’s global Data Management practice for Insights & Data, covering Information Strategy, Governance, Data Quality, Architecture, MDM, ILM and Privacy. There are 4 main elements of my job:
- Strategize directions for the practice
- Build capabilities and propositions to deliver that strategy
- Drive the business itself including P&L
- People management – I oversee around 450+ people in this practice
What has been the most challenging data-related project you have worked on and why? What was your role in it and was the project a success and why?
Probably the most challenging project was outside the boundaries of traditional data management; my team was tasked with the responsibility of building a linear asset management system for a transport company.
At the time (c. 5 years ago) people still saw MDM as an operational solution NOT a business-enabling, analytical solution. The approach we took was to sell the concept of a provisioning platform – and then we had to deliver it. It was challenging because:
- It had never been done before
- The systems that had to be integrated were very complex
- We had to create decision support and analytical systems that would enable millions in savings which meant we had to:
Understand from a technical perspective what the organization’s engineers needed
Transform this into a technology architecture to provide the relevant data sets and analytics
What did you learn from it?
That there is always a way.
We had to look at how the organization viewed asset management, not how the available asset management systems viewed it. We then had to figure out how to get the view the business wanted.
“Unlike the other bidders, we walked in with an approach instead of a tool. When we won the bid we then had to work back from the conceptual approach to arrive at the right tool set.”
You have a global role – what do you see as the global data management trends?
I see that the US and Europe are more focused on analytical data management (not just MDM) whereas the less mature markets are still working on operational projects. It is encouraging because in US and Europe most organizations have seen the value of data working for them operationally and now want to exploit it further through analytics.
I think the cloud market is still immature. There are two reasons for this:
- Most platforms still do not have the robust end-to-end data management that is needed – so there are gaps.
- Organizations don’t have a clear cloud strategy.
“Just saying “I want to move to cloud” is not a strategy.”
You need to have business objectives, the right security, the relevant data and perhaps most importantly you need to understand and evaluate the TCO. To do that effectively, you must understand what Cloud is really good for. I believe Cloud is useful where you have a distributed workforce and when you require flexibility in your infrastructure usage. So, Cloud is not always the best option on TCO for all companies.
Build Vs Buy is a similar discussion to Cloud. There is never a simple answer because it changes over time. You need to think about what you win/lose from total outsourcing.
And, it all comes down to organizational maturity – it will take a while. Only when companies have their data and strategy in place will Cloud become an accepted way of life.
This is thought of by most people as lots of data on a Hadoop system. HDFS is a data storage technology that gives you some flexibility but then so did the RDMS over traditional flat files.
The basic concept you need to get right is how to deal with the data – how to store and manage it; and how to exploit it. This has never changed.
“Big data is not new and you still have to get the basics right.”
Most organizations looking into big data go through an R&D phase where they are looking at open source systems and experimenting. I suppose it’s a bit like testing a medicine – you try out different things to determine their business value.
However, when they begin wanting to productionize the outcomes, the tendency is to move away from open source systems. It is all part of an evolutionary process – it is not revolutionary or new.
“HDFS is just a form of filing system – it’s not a new concept.”
You have a reputation of being a great “People Person” with a large number of positive recommendations from colleagues. How important do you think these soft skills are in a technical industry?
I speak honestly and directly – that approach doesn’t work for everyone.
“I initially adopted a management style of treating people as I would like to be treated. As I gained more experience, I realised that it is most important to treat people as they would like to be treated. This is essential in a business that is people-based.”
How can we develop more data management skills and build more data scientists from young people?
I think it goes back to human nature. People go where they feel there are challenges and growth opportunities and think it suits their mental/emotional profile.
“The data space is for people who like to explore the art of the possible”.
Therefore, the key is to ensure we demonstrate this to students from schools and universities and even people starting their first job.
My team will tell you that I always remind them that to have a beautiful rose garden you have to shovel a lot of [manure]. It’s the end results of data management that are exciting and important – but it’s not an easy challenge to convey this.
So how do we do it?
One way to do it is through word-of-mouth. People who have done this should talk about it and open up forums and debates. At Capgemini we have graduates and senior people who go back to schools to share what they are doing. We should be talking often about how we are addressing the challenges of today’s world via data management.
The other aspect is to emphasize the importance of a diverse team and how much a good team can get done when it is focused on the same goal. You need different skills and approaches – quick brilliance and methodical thought together can build great things.
“You don’t have to fit to a special mould to be successful in data management. We need diversity of gender, background, thinking, motivation – everything!”
When you look at staffing from a customer point of view, how do you advise them on having people in-house versus outsourcing?
In the past, the advice would have been that you keep strategic things in-house and outsource the tactical stuff. This is not so relevant anymore because a lot of the tactical tasks have already been automated.
The main thing is to look at what matters. Data management technology is changing so rapidly that you cannot keep abreast of it all. What you need is to have people understand how to take technology and address business needs with it.
I guess I would advise them to take the view that their data is their core business. Therefore, they could outsource the provisioning of it, but they should keep the exploitation of data in-house.
– What advice would you give to someone embarking on a large data-related project today?
“Think big, act small”
You must know where you are going and have an idea of how to get there – but you can’t hop, skip and jump your way to it. You need to take phased steps and realise that the direction of travel might change so flexibility is important. This means keep checking outcomes with the business and delivering value on a regular basis.
What are you best known for or what do you like doing outside of your working life?
I have been known to enjoy good food and drink in company of people. I love cars and any kind of techno-gadget. Badminton is my favourite exercise although I only play it socially now. I also love travel and exploration – I am a very inquisitive and curious person.
Finally, what 3 words would you use to describe yourself?
Well you’ve know me quite a while now, what 3 words would you use?
I would probably say ‘gregarious’, ‘kind’ and ‘unflappable’. Your turn.
I would agree with ‘gregarious’, I would add ‘driven/motivated’ but I think the third one would be ‘balanced’ – so, similar to ‘unflappable’.
“What I mean by that is that there is only ever so much you can do in a work scenario, so killing yourself with stress is not going to help. Have a process and follow it.”
If you jump into a pressured situation and panic you can often be infringing on other people’s jobs and that doesn’t help – they won’t thank you for it.
I have also learned how to switch off and balance work with the rest of my life.
“I travel a lot but when I am home I ensure I am “in the room”, not thinking about something else.”