Data changemakers 15: Kennedy Warwick, Enterprise Process Owner – Data at Thomson Reuters
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?
A senior data/information management professional with over 20 years experience in the financial services, legal, FMCG and government sectors, Kennedy Warwick is Enterprise Process Owner – Data at Thomson Reuters.
Please describe a little about your background and how you ended up working with data?
I did a BA in Political Economy, graduating in 1989 without really knowing what I wanted to do. I applied for lots of graduate schemes in banking – a particularly poor time to be doing that – and I got lots of interviews but no job.
Eventually I took a temporary job working at BT in the Fault Reporting Centre for their major commercial customers. The role meant that I was dealing with lots of bits of incoming paper followed by data entry into horrible mainframe systems. I could see that quite a bit of this data was important or significant – like system alerts. I thought it would be very useful if we could gather up this information and report it back to the business. That way they would have had an overview of their sectors and other insights but that wasn’t the way things were done back then.
However, it kicked off a thought process in my mind about the impact of data and I also knew the technology was improving.
“I had lots of friends who were interested in coding and technology but I was more interested in how that technology, in conjunction with the data, could be used to inform business strategy or change results.”
I also realised I wasn’t particularly well-qualified, so I applied for an MSc available at the University of Brighton on Information Systems and Systems Analysis. I got in and did a year and a half of the hardest work of my life, passed it and came out as a Master of Science and that’s where it all started.
Would you say that you are a business person or a technical person or something else?
I’m a business person with a certain amount of technical knowledge. I would say I have an in-depth knowledge of the impact or potential impact of data across the organisations that I have worked for.
What is your current role and its main responsibilities as they relate to data?
At the moment, I am the enterprise process owner for data for the Thomson Reuters organisation. This means I am responsible for all data that is generated through our order-to-cash processes and supporting systems but not including content like our news and the wonderful bits that flow into EIKON. Most importantly I drive the strategy for master data for the organisation as a whole.
I have a new role – to be decided – coming up in a month or so but my main responsibilities are around MDM for customer, product and related data sets but also data quality, governance and other similar areas.
You have spearheaded a number of cross-functional teams in data-related projects. What has been the most challenging aspect of this and why? How have you managed to be successful?
“I guess the most challenging aspect are the differing levels of understandings of what data actually is across these cross-functional teams. Most functions are very siloed in their views, including their views of data.”
They are either generators of data and think they understand it because they produce it (in their silo’dway) or they have a momentary interaction with the data as part of a process, so they have very little understanding of it in terms of source or significance, as it just flows by them.
For example, sales teams are significant generators of data in its initial form, but they can have very little understanding of how important the data quality is. If you speak to the order management team about that same data, they have a greater understanding of the need for data quality because they know what happens if it’s inaccurate and the impact it has on CX or invoicing etcetera. Other cross-functional teams, for example finance, are very much consumers of the data and as such have an expectation of accuracy and quality that might not actually be there.
Divestitures and M&A are very difficult to deal with because you are managing across multiple functions both within your own business and the newly acquired entity has no idea how it works. They don’t understand why you are asking what you are asking or why you have very specific requests.
The way to succeed is:
- Persevere, in my previous role as Head of Customer Data for F&R the initial couple of years were spent getting moaned at by numerous functions across the business about the quality of customer data and how it impacted their ability to do their jobs properly. My role was to make sure they understood our strategy and that we were seen practically to be improving the data quality in weeks rather than years.
“I had to be pretty thick-skinned, committed and confident in what we were doing was going to be successful and sustainable. I knew we had been successful only when I stopped getting moaned at about the quality of customer data or they moved on to other data sets to complain about.”
If I hadn’t persevered and stood my ground then we wouldn’t have improved the data dramatically, and we definitely wouldn’t have gained the trust and confidence of the business that allowed us to make even greater strides in our data management strategy in more recent years.
- Have a clear plan – complexity is your enemy.
- Be pragmatic – don’t chase absolute perfection – don’t even try it. If you can get 85-90% of your data accurate then you are 90% better off than you where and the remainder can be dealt with over time.
- Make use of the right tools – there are many more available now than there were even 5 years ago.
- People – have the right combination of technical people who understand matching and models etc but also people who remember that you are doing what you are doing to make the business better.
“As part of this you must have a clear set of requirements from the beginning and not dilute them based on functional bias or people who are obsessed with minutiae.”
The good news is, that there is also a far greater understanding of the importance of data right now and budgets are being assigned accordingly. The business is really starting to understand the impact of data.
“I have spent 8 years in this company continually advertising the importance of good quality data and what it does for the organisation. That, coupled with what we’ve managed to achieve means my team has earned some respect and the right to be trusted to know what we are doing without too much interference.”
What do you think are the key trends in data management today and how do you think it will change the way we all do business particularly for marketers?
I am not sure it’s a trend more of a fact, but today’s audiences/customers are far more sophisticated and switched on as to the value of their personal data and the impact that it can have if not managed appropriately or as requested. This has raised the levels of customer expectations and therefore marketers need to be very aware and adjust their marketing actions accordingly, the days of the mass marketing email blitz are over – thank God! You better be able to personalise and focus your marketing efforts or you’re not going to be very successful.
The expansion of compliance and privacy legislation is going to impact how marketers do business as well and as a result how data is managed internally resulting in changing business processes and the adoption of further technologies to try and eliminate risk.
Cloud is a very, very interesting and significant development especially in conjunction with managed services.
“Why have all this hardware, software and resources on-premise when you can have it in the cloud managed by people who own and understand it?”
Some of the underlying technology platforms around MDM are changing significantly- there’s a move towards some of the more niche organisations that are very good at one thing and have “grown up” in the cloud so to speak. MDM has also changed in that it used to be a 3 year, multi-million pounds project but it doesn’t have to be any more. People have realised this and, together with what is available on the market, they are able to deliver more effectively.
There are some fantastic tools now out there that can help you in the realm of data. Can I name a few?
Tools such as Alteryx around data blending and management is one and Tamr is another awesome tool. The other thing that is becoming really interesting now are some of the data governance/meta-data management tools that are out there.
“These enable us to look at underlying core data attributes in conjunction with our analytics architectures. Your ability to understand where your data is coming from and how it’s generated is foundational.”
What advice would you give to someone embarking on a large data-related project today?
- I would absolutely make sure, before you do anything that you understand the requirements – why you are doing this. They have to be set in stone and I have become more and more militant about this as time has gone on. As soon as you get away from that you don’t have the focus and you lose support – someone will always say “well I didn’t ask for that” or “I thought we were getting this”. It also has to be a business-generated programme with a strategic business goal that is a priority or you will lose executive sponsorship early on.
- Manage expectation. If for example you say you are going to begin a master data project for customer data then the chances are the business is going to think it is going to solve every single problem known to man and that this won’t have anything to do with them and how they behave. Business people often don’t understand the process – that MDM is a key generator – that it doesn’t matter how clean you get the data if the process they use to collect data afterwards it is crap. Because then the data will still be crap. They have to understand that they need to improve their processes and manage their own people to follow them – the people are part of this too. Manage expectation from the beginning or otherwise there will be a disconnect between business and the people who are running these programmes.
- Be upfront and honest about costs and resources required.
- Be sensible around the tools that you can use, don’t expect one tool to do everything.
“Ultimately, data management is about producing high-quality diesel to drive the business engine. Your job is to constantly strive to improve the fuel via all means possible – process, technology and people – and to maintain it so it won’t go back to what it was.”
What particular skills or qualifications you consider to be vital to your success?
You have got to understand that data management is about improving the business – it is not about the technology. You have to bring the business strategy together with the data.
“This is not about taking on an intellectual or technology challenge – you need to produce results. This means you need to be determined, committed, confident and tough and you have to see the big picture.”
I have been in meetings with a number of more technical people who like to discuss the technology and my question is always “What it will do for the business?”
“I wish I was twenty years younger – data management is a growth industry and it would be so exciting to be coming into it now!”
What are you best known for or what do you like doing outside of your working life?
I still play cricket competitively – the Old Wimbledonians – in the Summer. I have retired from football in the winter as I found I was getting injured – about every 45 minutes. I am pretty physically active and have a personal trainer called Talla he is a French/Senegalese former pro-boxer, he has devised about 100 ways to use a 12 kilo kettle bell all of which hurt. I spend time with my two boys too.
Oh and I like alcohol. Especially wine. And beer. And going to the cinema although I don’t go as often as I’d like to.
Which three people – alive or dead – would you like to invite for dinner and why?
John Sandford – I think that he is a brilliant writer even managed to make me want to visit Minnesota.
Kenny Dalglish – Childhood hero, I stood on the Kop and watched him play and then he was a great manager plus he had the fortitude and emotional intelligence to deal with the Hillsborough disaster, I can’t imagine what attending the vast majority of the 96 funerals must have been like but somehow he did it.
Susan Travers – The only British woman to join the French Foreign Legion and proper war hero, I doubt you could find a more interesting dinner guest.
For more #datachangemakers interviews click here.
For information on Entity Group’s advisory services in the area of data management and analytics click here.