An in-depth interview with CDO Caroline Carruthers

In-depth with Caroline Carruthers

Part of the In-depth series of interviews

PJT Today I am talking to Caroline Carruthers, experienced data professional and famous as co-author (with Peter Jackson) of The Chief Data Officer’s Playbook. Caroline is currently Group Director of Data Management at Lowell Group. I am very pleased that she has found the time to talk to me about some of her experiences and ideas about the data space.
PJT Caroline, I mentioned your experience in the data field, can you paint a picture of this for readers?
CC Hi Peter, of course. I often describe myself as a data cheerleader or data evangelist. I love all the incredible technologies that are coming around such as AI. However, the foundation we have to build these on is a data one. Without that solid data foundation we are just building houses of cards. My experience started off in IT as a graduate for the TSB, moving into consulting for IBM and then ATOS I quickly recognised that whilst I love technology (I will always be a geek!) the root cause of a lot of the issues we are facing came down to data and our treatment of it, whether that meant we didn’t understand the risks or value associated with it is just different sides of the same pendulum. So my career has been a bit eclectic through CTO and Programme Director roles but the focus for me has always been on treating data as a valuable asset.
PJT The Chief Data Officer's Playbook
The Chief Data Officer’s Playbook has been very well-received. Equally I can imagine that it was a lot of work to pull this together with Peter. Can you tell me a bit about what motivated you to write this book?
CC The book came about as Peter and I were presenting at a conference in London and we both gave the same answer to a question about the role of a CDO; there was no manual or rule book, it was an evolving role and, until we did have something that clarified what it was, we would struggle. Very luckily for me Peter came up with the idea of writing it together. We never pretended we had all the answers, it was a way of getting our experiences down on paper so we (the data community) could have a starting point to professionalise what we all do. We both love being part of the data community and feel really passionate about helping everyone understand it a little better.
PJT As an aside, what was the experience of co-authoring like? What do you feel this approach brought to the book and were there any challenges?
CC It was a gift, writing with Peter. We’ve both been honest with each other and said that if either of us had tried to do it on their own we probably wouldn’t have finished it. We both have different and complementary strengths so we just made sure to use that when we wrote the book. Having an idea of what we wanted it to look like from the beginning helped massively and having two of us meant that when one of us had had enough the other one brought them back round. The challenges were more around time together than anything else, we both were and are full time CDOs so this was holidays and weekends. Luckily for us we didn’t know what we didn’t know; on the day of the book launch was when our editor told us it wasn’t normal to write a book as fast as we did!
PJT There is a lot of very sound and practical advice contained in The Chief Data Officer’s Playbook, is there any particular section, or a particular theme that is close to your heart, or which you feel is central to driving success in the data arena?
CC For me personally it’s the chapter about data hoarding because it came about from a Sunday morning tradition that my son and I have, where we veg in front of the tv and spend a lazy Sunday morning together. The idea is that data hoarders keep all data, which means that organisations become so crammed full of data that they don’t value it anymore. This chapter of the book is about understanding the value of data and treating it accordingly. If we truly understood the value of what we had, people would change their behaviour to look after it better.
PJT I have been speaking to other CDOs about the nature of the role and how – in many ways – this is still ill-defined and emergent [1]. How do you define the scope of the CDO role and do you see this changing in coming years?
CC In the book, we talk about different generations of CDOs, the first being risk focused, the second being value-add focused but by the third generation we will have a clearly defined, professionalised role that is clearly accepted as a key member of the C suite.
PJT I find that something which most successful data leaders have in common is a focus on the people aspects of embracing the opportunities afforded by leveraging data [2]. What are your feelings on this subject?
CC I totally agree with that, I often talk about hearts and minds being the most important aspect of data. You can have the best processes, tools and tech in the world but if you don’t convince people to come out of their comfort zone and try something different you will fail.
PJT What practical advice can you offer to data professionals seeking to up their game in influencing organisations at all levels from the Executive Suite to those engaged in day-to-day activities? How exactly do you go about driving cultural change?
CC Focus on outcomes, keep your head up and be aware of the detail but make sure you are solving problems – just have fun while you do it.
PJT Some CDOs have a focus on the risk and governance agenda, some are more involved in using data to drive growth and open new opportunities, some have blended responsibilities. Where do you sit in this spectrum and where do you feel that CDOs can add greatest value?
CC I’d say I started from the risk adverse side but with a background in tech and strategy, I do love the value add side of data and think as a CDOs you need to understand it all.
PJT The Chief Data Officer’s Playbook is a great resource to help both experienced CDOs and those new to the field. Are there other ways in which data leaders can benefit from the ideas and insights that you and Peter have?
CC Funny you should mention this… On the back of the really great feedback and reception the book got we are running a CDO summer school this summer sponsored by Collibra. We thought it would be an opportunity to engage with people more directly and help form a community that can help and learn from each other.
PJT I also hear that you are working on a sequel to your successful book, can you give readers a sneak preview of what this will be covering?
CC Of course, it’s obviously still about data but is more focused on the transformation an organisation needs to go through in order to get the best from it. It’s due out spring next year so watch this space.
PJT As well as the activities we have covered, I know that you are engaged in some other interesting and important areas. Can you first of all tell me a bit about your work to get children, and in particular girls, involved in Science, Technology, Engineering and Mathematics (STEM)?
CC I would love to. I’m really lucky that I get the chance to talk to girls in school about STEM subjects and to give them an insight into some of the many different careers that might interest them that they may not have been aware of. I don’t remember my careers counsellor at school telling me I could be a CDO one day! There are two key messages that I really try to get across to them. First, I genuinely believe that everyone has a talent, something that excites them and they are good at but if you don’t try different things you may never know what that is. Second, I don’t care if they do go into a STEM subject. What I care passionately about is that they don’t limit themselves based on other people’s preconceptions.
PJT Finally, I know that you are also a trustee of CILIP the information association and are working with them to develop data-specific professional qualifications. Why do you think that this is important?
CC I don’t think that data professionals necessarily get the credit they deserve and it can also be really hard to move into our field without some pretty weighty qualifications. I want to open the subject out so we can have access courses to get into data as well as recognised qualifications to continue to professionalise and value the discipline of data.
PJT Caroline, it has been a pleasure to speak. Thank you for sharing your ideas with us today.

Caroline Carruthers can be reached at

Disclosure: At the time of publication, neither Ltd. nor any of its Directors had any shared commercial interests with Caroline Carruthers or any entities associated with her.

If you are a Chief Data Officer, a Chief Analytics Officer, a Director of Data, or hold some other “Top Data Job” and would like to share your thoughts with the readers of this site in an interview like this one, please get in contact.


See An in-depth interview with experienced Chief Data Officer Roberto Maranca.

From:, home of The Data and Analytics Dictionary, The Anatomy of a Data Function and A Brief History of Databases


An in-depth interview with experienced Chief Data Officer Roberto Maranca

In-depth with Roberto Maranca

Part of the In-depth series of interviews

PJT Today’s interview is with Roberto Maranca. Roberto is an experienced and accomplished Chief Data Officer, having held that role in GE Capital and Lloyds Banking Group. Roberto and I are both founder members of the IRM(UK) Chief Data Officer Executive Forum and I am delighted to be able to share the benefit of his insights with readers.
PJT Roberto, you have had a long and distinguished career in the data space, would you mind starting by giving readers a brief overview of this?
RM Certainly Peter, looking back now Data has been like a river flowing through all my career. But I can definitely recall that, at a certain point in my life in GE Capital (GEC), someone who I had worked with before called me to take a special assignment as IT lead for the Basel II implementation for the Bank owned by GEC in Europe. For the readers not in the Finance industry, Basel II, for most of us and certainly for me, was our Data baptism of fire because of its requirement to collect a lot of data across the organisation in order to calculate an “enterprise wide” set of risk metrics. So the usual ETL build and report generation wasn’t good enough if not associated to a common dictionary, validation of mappings, standardised referential integrity and quality management.

When Basel went in production in 2008, I was given the leadership of the European Business Intelligence team, where I consolidated my hunch that the reason that a 6 months dashboard build project would fail pre-production tests was mainly “data is not good enough” and not our lack of zeal. Even if was probably amongst the first in GEC to adopt a Data Quality tool, you had the feeling that IT could not be the proverbial tail shaking the dog in that space. A few years went by where I became much closer to operations in a regulated business, learning about security and operational risk frameworks, and then one day at the end of 2013, I saw it! GEC was to be regulated by the Federal Reserve as one entity, and that posed a lot of emphasis on data. The first ever job description of CDO in GEC was flashed in front of my eyes and I felt like I had just fallen on the way to Damascus. All those boxes that had been empty for years in my head got ticked just looking at it. I knew this was what I wanted to do, I knew I had to leave my career in IT to do it, I knew there was not a lot beyond that piece of paper, but I went for it. Sadly, almost two years into this new role, GE decided to sell GEC; you would not believe how much data you need to divest such a large business.

I found that Lloyds Banking Group was after a CDO and I could not let that opportunity go by. It has been a very full year where I led a complete rebuild of their Data Framework, while been deeply involved in the high-profile BCBS239 and GDPR initiatives.

PJT Can you perhaps highlight a single piece of work that was important to you, added a lot of value to the organisation, or which you were very proud of for some other reason?
RM I always had a thing about building things to last, so I have always tried to achieve a sustainable solution that doesn’t fall apart after a few months (in Six Sigma terms you will call it “minimising the long term sigma shift”, but we will talk about it another time). So trying to have change process to be mindful of “Data” has been my quest since day one, in the job of CDO. For this reason, my most important piece of work was probably the the creation of the first link between the PMO process in GEC and the Data Lineage and Quality Assurance framework, I had to insist quite a bit to introduce this, design it, test it and run it. Now of course, after the completion of the GEC sale, it has gone lost “like tears in the rain”, to cite one of the best movies ever [1].
PJT What was your motivation to take on Chief Data Officer roles and what do you feel that you bring to the CDO role?
RM I touched on some reasons in my introductory comments. I believe there is a serendipitous combination of acquired skills that allows me to see things in a different way. I spent most of my working life in IT, but I have a Masters in Aeronautical Engineering and a diploma in what we in Italy call “Classical Studies”, basically I have A levels in Latin, Greek, Philosophy, History. So for example, together with my pilot’s licence achieved over weekends, I have attended a drama evening school for a year (of course in my bachelor days). Jokes apart, the “art” of being a CDO requires a very rich and versatile background because it is so pioneering, ergo if I can draw from my study of flow dynamics to come up with a different approach to lineage, or use philosophy to embed a stronger data driven culture, I feel it is a marked plus.
PJT We have spoken about the CDO role being one whose responsibilities and main areas of focus are still sometimes unclear. I have written about this recently [2]. How do you think the CDO role is changing in organisations and what changes need to happen?
RM I mentioned the role being pioneering: compared to more established roles, CFO, COO and, even, CIO, the CDO is suffering from ambiguity, differing opinions and lack of clear career path. All of us in this space have to deal with something like inserting a complete new organ in a body that has got very strong immunological response, so although the whole body is dying for the function that the new organ provides (and with the new breed of regulation about, dying for lack of good and reliable data is not an exaggeration), there is a pernickety work of linking up blood vessels and adjusting every part of the organisation so that the change is harmonious, productive and lasting. But every company starts from a different level of maturity and a different status quo, so it is left to the CDO to come up with a modus operandi that would work and bring that specific environment to a recognisable standard.
PJT The Chief Data Officer has been described as having “the toughest job in the executive C-suite within many organizations” [3]. Do you agree and – if so – what are the major challenges?
RM I agree and it simply demonstrated: pick any Company’s Annual Report, do a word search for “data quality”, “data management“, “data science” or anything else relevant to our profession, you are not going to find many. IT has been around for a while more and yet technology is barely starting now to appear in the firm’s “manifesto”, mostly for things that are a risk, like cyber security. Thus the assumption is, if it is not seen as a differentiator to communicate to the shareholders and the wider world, why should it be of interest for the Board? It is not anyone’s fault and my gut feeling is that GDPR (or perhaps Cambridge Analytica) is going to change this, but we probably need another generational turnover to have CDOs “safely” sitting in executive groups. In the meantime, there is a lot we can do, maybe sitting immediately behind someone who is sitting in that crucial room.
PJT We both believe that cultural change has a central role in the data arena, can you share some thoughts about why this is important?
RM Data can’t be like a fad diet, it can’t be a program you start and finish. Companies have to understand that you have to set yourself on a path of “permanent augmentation”. The only way to do this is to change for good the attitude of the entire company towards data. Maybe starting from the first ambiguity, data is not the bits and bytes coming out of a computer screen, but it is rather the set of concepts and nouns we use in our businesses to operate, make products, serve our customers. If you flatten your understanding of data to its physical representation, you will never solve the tough enterprise problems, henceforth if it is not a problem of centralisation of data, but it is principally a problem of centralisation of knowledge and standardisation of behaviours, it is something inherently close to people and the common set of things in a company that we can call “culture”.
PJT Accepting the importance of driving a cultural shift, what practical steps can you take to set about making this happen?
RM In my keynotes, I often quote the Swiss philosopher (don’t tell me I didn’t warn you!) Henry Amiel:

Pure truth cannot be assimilated by the crowd: it must be communicated by contagion.

This is especially the case when you are confronted with large numbers of colleagues and small data teams. Creating a simple mantra that can be inoculated in many part of the organisation helps to create a more receptive environment. So CDOs should first be keen marketeers, able to create a simple brand and pursuing relentlessly a “propaganda” campaign. Secondly, if you want to bring change, you should focus where the change happens and make sure that wherever the fabric of the company changes, i.e. big programmes or transformations, data is top priority.

PJT What are the potential pitfalls that you think people need to be aware of when embarking on a data-centric cultural transformation programme?
RM First is definitely failing to manage your own expectations on speed and acceptance; it takes time and patience. Long-established organisations cannot leap into a brighter future just because an enlightened CDO shows them how. Second, and sort of related, it is a problem thinking that things can happen by management edicts and CDO policy compliance, there is a lot niftier psychology and sociology to weave into this.
PJT A two-part question. What do you see as the role of Data Governance in the type of cultural change you are recommending? Also, do you think that the nature of Data Governance has either changed or possibly needs to change in order to be more effective?
RM The CDO’s arrival at a discussion table is very often followed by statements like “…but we haven’t got resources for the Governance” or “We would like to, but Data Governance is such an aggro”. My simple definition for Data Governance is a process that allows Approved Data Consumers to obtain data that satisfies their consumption requirements, in accordance with Company’s approved standards of traceability, meaning, integrity and quality. Under this definition there is no implied intention of subjecting colleagues to gruelling bureaucratic processes, the issue is the status quo. Today, in the majority of firms, without a cumbersome process of checks and balances, it is almost impossible to fulfil such definition. The best Data Governance is the one you don’t see, it is the one you experience when you to get the data you need for your job without asking, this is the true essence of Data Democratisation, but few appreciate that this is achieved with a very strict and controlled in-line Data Governance framework sitting on three solid bastions of Metadata, User Access Controls and Data Classification.
PJT Can you comment on the relationship between the control of data and its exploitation; between Analytics and Governance if you will?Do these areas need to both be part of the CDO’s remit?
RM Oh… this is about the tale of the two tribes isn’t it? The Governors vs. the Experimenters, the dull CDOs vs the funky CAOs. Of course they are the yin and the yang of Data, you can’t have proper insight delivered to your customer or management if you have a proper Data Governance process, or should we call it “Data Enablement” process from the previous answer. I do believe that the next incarnation of the CDO is more a “Head of Data”, who has got three main pillars underneath, one is the previous CDOs all about governance, control and direction, the second is your R&D of data, but the third one that getting amassed and so far forgotten is the Operational side, the Head of Data should have business operational ownership of the critical Data Assets of the Company.
PJT The cultural aspects segues into thinking about people. How important is managing the people dimension to a CDO’s success?
RM Immensely. Ours is a pastoral job, we need to walk around, interact on internal social media, animate communities, know almost everyone and be known by everyone. People are very anxious about what we do, because all the wonderful things we are trying to achieve, they believe, will generate “productivity” and that in layman’s terms mean layoffs. We can however shift that anxiety to curiosity, reaching out, spreading the above-mentioned mantra but also rethinking completely training and reskilling, and subsequently that curiosity should transform in engagement which will deliver sustainable cultural change.
PJT I have heard you speak about “intelligent data management” can you tell me some more about what you mean by this? Does this relate to automation at all?
RM My thesis at Uni in 1993 was using AI algorithms and we all have been playing with MDM, DQM, RDM, Metadata for ages, but it doesn’t feel we cracked yet a Science of Data (NB this is different Data Science!) that could show us how to resolve our problems of managing data with 21st century techniques. I think our evolutionary path should move us from “last month you had 30k wrong postcodes in your database” to “next month we are predicting 20% fewer wrong address complaints”, in doing so there is an absolute need to move from fragmented knowledge around data to centralised harnessing of the data ecosystem, and that can only be achieved tuning in on the V.O.M. (Voice of the Machines), listening, deriving insight on how that ecosystem is changing, simulating response to external or internal factors and designing changes with data by design (or even better with everything by design). I yet have to see automated tools that do all of that without requiring man years to decide what is what, but one can only stay hopeful.
PJT Finally, how do you see the CDO role changing in coming years?
RM To the ones that think we are a transient role, I respond that Compliance should be everyone’s business, and yet we have Compliance Officers. I think that overtime the Pioneers will give way to the Strategists, who will oversee the making of “Data Products” that best suit the Business Strategist, and maybe one day being CEO will be the epitome of our career ladders one day, but I am not rushing to it, I love too much having some spare time to spend with my family and sailing.
PJT Roberto, it is always a pleasure to speak. Thank you for sharing your ideas with us today.

Roberto Maranca can be reached at and has social media presence on LinkedIn and Twitter (@RobertoMaranca).

Disclosure: At the time of publication, neither Ltd. nor any of its Directors had any shared commercial interests with Roberto Maranca.

If you are a Chief Data Officer, a Chief Analytics Officer, a Director of Data, or hold some other “Top Data Job” and would like to share your thoughts with the readers of this site in an interview like this one, please get in contact.


The CDO – A Dilemma or The Next Big Thing?
Randy Bean of New Vantage Partners quoted in The CDO – A Dilemma or The Next Big Thing?

From:, home of The Data and Analytics Dictionary, The Anatomy of a Data Function and A Brief History of Databases


An in-depth Interview with Allan Engelhardt about Analytics

In-depth with Allan Engelhardt

Part of the In-depth series of interviews

PJT Today’s interview is with Allan Engelhardt, co-founder and principal of insights and analytics consultancy Cybaea. Allan and I know each other from when we both worked at Bupa. I was interested to understand the directions that he has been pursuing in recent years.
PJT Allan, we know each other well, but could you provide a pen picture of your career to date and the types of work that you have been engaged in?
AE I started out in experimental physics working on (very) big data from CERN, the large research lab near Geneva, and worked there after getting my degree. Then, like many other physicists, I was recruited into financial services, in my case to do risk management. From there to a consultancy helping business make use of bleeding edge technology and then on to CRM and customer loyalty. This last move was important for me, allowing me to move beyond the technology to be as much about commercial business strategy and operations.

In 2002 a couple of us left the consultancy to help customers move beyond transactional infrastructure, which is really what ‘CRM’ was about at the time, to create high value solution on top, and to create the organizational and commercial ownership of the customer needed to consistently drive value from data, inventing the concept of Customer Value Management which is now universally implemented by telcos across the world and increasingly adopted by other industries.

PJT There is no ISO definition of either insight or analytics. As an expert in these fields, can I ask you to offer your take on the meaning of these terms?
AE To me analytics is about finding meaning from information and data, while insights is about understanding the business opportunities in that meaning. But different people use the terms differently.
PJT I must give you an opportunity to both explain what Cybaea does and how the name came about.
AE At Cybaea we are passionate about value creation and commercial results. We have been called ‘Management consultants with a black belt in data’ and we help organizations identify and act upon data driven opportunities in the areas of:

Cybaea offering

  1. Customer Value Management (CVM), including acquisition, churn, cross-sell, segmentation, and more, across online and offline channels and industries, both B2C and B2B.
  2. Customer Experience and Advocacy, including Net Promoter System and Net Promoter Economics, customer journey optimization, and customer experience.
  3. Innovation and Growth, including data-driven product and proposition development, data monetisation, and distribution and sales strategy.

For our customers, CVM projects typically deliver additional 5% EBITDA growth annually, which you can measure very robustly because much of it is direct marketing. Experience and Advocacy projects typically deliver in the region of 20% EBITDA improvement to our clients, but it is harder to measure accurately because you must go above the line for this level of impact. And for Innovation and Growth, the sky is the limit.

As for the name, we founded the company in 2002 and wanted a short domain name that was a real word. It turned out to be difficult to find an available, short ‘.com’ at the peak of the dot-bomb era! We settled on ‘cybaea’ which my Latin dictionary translated as ‘trading vessel’; historically, it was a type of merchant ship of Greek origin, common in the Mediterranean, which Cicero describes as “most beautiful and richly adorned”. We always say we want to change the name, but it never happens; I guess if it was good enough for Cicero, then it is good enough for us.

PJT While at Bupa you led work that was very beneficial to the organisation and which is now the subject of a public Cybaea case study, can you tell readers a bit more about this?
AE Certainly, and the case study is available at for anyone who wants to read more.

This was working with Bupa Global; a Bupa business unit that primarily provides international private medical insurance for 2 million customers living in over 195 different countries. Towards the end of 2013, Bupa Global set out on a strategic journey to deliver sustained growth. A key element of this was the design and launch of a completely new set of products and propositions, replacing the existing portfolio, with the objective of attracting and servicing new customer segments, complying with changing regulation and meeting customer expectations.

The strategic driver was therefore very much in the Innovation and Growth space we outlined above, and I joined Bupa’s global Leadership Team to create and lead the commercial insights function that would support this change with deep understanding of the target customers and the markets in which they live. Additionally, Bupa had very high ambitions for its Net Promoter programme (Experience and Advocacy) where we delivered the most advanced installation across the global business, and for Customer Value Management we demonstrated nearly 2% reduction in the Claims line (EBITDA) from one single project.

For the new propositions, we initially interviewed over 3,000 individuals on five continents to understand value- and purchase drivers, researched 195 markets to size demand across all customer segments, and further deep-dived into key markets to understand the competitors with products, features, and prices, as well as the regulatory environment, and distribution options. This was supported by a very practical Customer Lifetime Value model, which we developed.

Suffice to say that in two years we had designed and implemented a completely new set of propositions and taken them live in more than twenty priority markets where they replaced the old products.

The strategic and commercial results were clearly delivered. But when I asked our CEO what he thought was the main contribution of the team and the new insights function, he focused on trust: “Every major strategic decision we made was backed by robust data and deep insights in which the executive team had full confidence.”

In a period of change, trust is perhaps the key currency. Trust that you are doing the right things for the right reasons, and the ability to explain why that is. This is key to get everybody behind the changes that need to happen. This is what the scientific method applied to data, analytics, and insights can bring to a commercial organization, and it inspires me to continue what we are doing.

PJT We have both been engaged in what is now generally called the Data arena for many years, some aspects of the technology employed have changed a lot during this time. What do you think modern technology enables today that was harder to achieve in the past and are there any areas where things are much the same as they were a decade or more ago?
AE Ever since the launch of the Amazon EC2 cloud computing service in late 2006 [1], data storage and processing infrastructure has been easily and cheaply available to everybody for most practical workloads. So, for ten years you have not had any excuse for not getting your data in order and doing serious analysis.

The main trend that excites me now is the breakthroughs happening in Deep Learning and Natural Language Processing, expanding the impact of data into completely new areas. This is great for consumers and for those companies that are at the leading edge of analytics and insights. For other organizations, however, who are struggling to deliver value from data, it means that the gap between where they are versus best practice is widening exponentially, which is a big worry.

PJT Taking technology to one side, what do you think are the main factors in successfully generating insight and developing analytical capabilities that are tightly coupled with value generation?
AE Two things are always at the forefront of my mind. The first is kind of obvious, namely to start with the business value you are trying to create and work backwards from that. Too often we see people start with the data (‘I got to clean all the data in my warehouse first!’), the technology (‘We need some Big Data infrastructure!’), or the analytics (‘We need a predictive churn model!’). That is cart before the horse. Not that these things are not important; rather, that there are almost certainly a lot of opportunities you could execute right now to generate real and measurable business value and drive a faster return on your investments.

The second is to not under-estimate the business change that is needed to exploit the insights. Analytical leaders have appetite for change and they plan and resource accordingly. Data and models are only part of the project to deliver the value and they are really clear on this.

PJT Looking at the other side of the coin, what at the pitfalls to look out for and do you have any recommendations for avoiding them?
AE The flip-side of the two points previously mentioned are obvious pitfalls: not starting from the business change and value you are trying to create. And it is not easy: great data scientists are not always great commercially-minded business people and so you need the right kind of skills to bridge that gap. McKinsey talks of ‘business translators who combine data savvy with industry and functional expertise’, which is a helpful summary [2]. Less helpfully they also note that these people are nearly impossible to find, so you may need to find or grow them internally.

Which gets to a second pitfall. When thinking about generating value from data, many want to do it all themselves. And I understand why: after all, data may well be a strategic asset for your organization.

But when you recruit, you should be clear in your mind if you are recruiting to deliver the change of creating the first models and changed business processes, or if you are recruiting to sustain the change by keeping the models current and incrementally improving the insights and processes. These two outcomes require people with quite different skills and vastly different temperaments.

We call them Explorers versus Farmers.

For the first, you want commercially-focused business people who can drive change in the organization; who can make things work quickly, whether that is data, analytics, or business processes, to demonstrate value; and who are supremely comfortable with uncertainties and unknowns.

For the second, you want people who are technically skilled to deliver and maintain the optimal stable platform and who love doing incremental improvements to technology, data, and business processes.

Explorers versus Farmers. Call them what you will, but note that they are different.

PJT Many companies are struggling with how to build analytical teams. Do they grow their own talent, do they hire numerate graduates or post graduates, do they seek to employ highly skilled and experienced individuals, do they form partnerships with external parties, or is a mixture of all of these approaches sensible? What approaches do you see at Cybaea clients adopting?
AE We are mostly seeing one of two approaches: one is to do nothing and soldier on as always relying on traditional business intelligence while the other is to hire usually highly technical people to build an internal team. Neither is optimal in getting to the value.

The do-nothing approach can make sense. Not, however, when it is adopted because management fears change (change will happen, regardless) or because they feel they don’t understand data (everybody understands data if it is communicated well). Those companies are just leaving money on the table: every organization have quick wins that can deliver value in weeks.

But it may be that you have no capacity for change and have made the informed decision that data and analytics must wait, reflecting the commercial reality. The key here is ‘informed’ and the follow-on question is if there are other ways that the company can realise some of the value from data right now.

The second approach at least recognises the value potential of data and aims to move the organization towards realising that value. But it is back to those ‘business translator’ roles we discussed before and making sure you have them, as well as making sure the business is aligned around the change that will be needed. Making money from data is a business function, not a technical one, and the function that drives the change must sit within the commercial business, not in IT or some other department that is still an arms-length support function.

We see the best organizations, the analytical leaders, employing flexible approaches. They focus on the outcomes and they have a sense of urgency driven from the top. They make it work.

PJT I know that a concept you are very interested in is Analytics as a Service (AaaS). Can you tell readers some more about what this means and also the work that Cybaea is doing in this area?
AE There is a war on analytical talent and a ‘winner takes it all’ dynamic is emerging with medium-sized enterprises especially losing out. Good people want to work with good people which generates a strong network effect giving advantage to large organizations with larger analytical teams and more variety of applications. Leading firms have depth of analytical talent and can recruit, trial, and filter more candidates, leaving them with the best talent.

Our analytics-as-a-service offering is for organizations of any size who want to realise value from data and insights right now, but who are not yet ready to build their own internal teams. We partner with the commercial teams to be their (commercial) insights function and deliver not just reports but real business change. Customers can pay monthly, pay for results, or we can do a build-operate-transfer model.

One of our first projects was with a small telco. They were too small to maintain a strong analytical team in-house, purely because of scale. We set up a monthly workshop with the commercial Marketing team. We analysed their data offline and used the time for a structured conversation about the new campaigns and the new changes to the web site they should implement this month. We would point them to our reports and dashboards which had models, graphs, t-tests, and p-values in abundance, but would focus the conversation on moving the business forward.

The following month we would repeat and identify new campaigns and new changes. After six months, they had more than 20 highly effective and precisely targeted campaigns running, and we handed over the maintenance (‘farming’) of the models to their IT teams. It is a model that works well across industries.

PJT Do you have a view on how the insights and analytics field is likely to change in coming years? Are there any emerging areas which you think readers should keep an eye on?
AE Many people are focused on the data explosion that is often called the ‘Internet of Things’ but more broadly means that more data gets generated and we consume more data for our analytics. I do think this opens tremendous opportunities for many businesses and technically I am excited to get back to processing live event streams as they happen.

But practically, we are seeing more success from deep learning. We have found that once an organization successfully implements one solution, whether artificial intelligence or complex natural language processing, then they want more. It is that powerful and that transformational, and breakthroughs in these fields are further expanding the impact into completely new area. My advice is that most organizations should at least trial what these approaches can do for them, and we have set up a sister-organization to develop and deliver solutions here.

PJT What are your plans for Cybaea in coming months?
AE I have two main priorities. First, I have our long-standing partner from India in London for a couple of months to figure out how we scale in the UK. This is for the analytics as a service but also for fast projects to deliver insights or analytical tools and applications.

Second, I am looking to identify the right partners and associates for Cybaea here in the UK to allow us to grow the business. We have great assets in our methodologies, clients, and people, and a tremendous opportunity for delivering commercial value from data, so I am very excited for the future.

PJT Allan, I would like to thank you for sharing with us the benefit of your experience and expertise in data matters, both of which have been very illuminating.

Allan Engelhardt can be reached at Cybaea’s website is and they have social media presence on LinkedIn and Google+.

Disclosure: Neither Ltd. nor any of its directors have any direct financial interest in either Cybaea or any of the other organisations mentioned in this article.

If you are a Chief Data Officer, a Chief Analytics Officer, a Director of Data, or hold some other “Top Data Job” and would like to share your thoughts with the readers of this site in an interview like this one, please get in contact.


McKinsey report The Age of Analytics, dated December 2016,

From:, home of The Data and Analytics Dictionary, The Anatomy of a Data Function and A Brief History of Databases


An in-depth Interview with Blockchain luminary Gary Nuttall

In-depth with Gary Nuttall

Part of the In-depth series of interviews

PJT Today I am speaking with Gary Nuttall, Managing Director of Distlytics Ltd. Distlytics is a ground-breaking consultancy implementing Distributed Ledger
Technology (aka “Blockchain”) within Financial Services. I know Gary from when we both worked in the Business Intelligence space and wanted to get his perspective on both the current state of this area and its future possibilities.

Gary, would you mind telling readers a little about yourself and your journey prior to Distlytics?

GPN My career spans multiple industries – I began in retail 25+ years ago working on Management Information, Decision Support and Expert Systems. Moved on to Pharmaceuticals (implementing a greenfield BI/DW platform), then the wine industry, commodities trading and then commercial insurance.

The strand that has remained central to my career has been business intelligence and analytics – using data to improve business processes and enabling better informed decision making.

PJT Can you expand on what Distlytics does and how it does it?
GPN I’ve been interested in Blockchain for several years and saw that many developments are implemented using a shared Distributed Ledger architecture. This made me think, how do you perform analytics on a distributed ledger? Lots of people are exploring using a blockchain-based solution to improve business performance or create new products and services but nobody was thinking about the analytics layer. So: Distributed Ledger + Analytics = Distlytics.

The original focus therefore was to identify how an analytics layer could be introduced, what the best architecture would be, were there suitable existing technologies or would something unique need to be developed etc. All very interesting stuff and right up my street as it involved new and emerging technology, business improvement and BI.

It quickly became clear however that I was ahead of the game and that many organisations were only just at the “what’s blockchain and how can we use it?” phase. Therefore I started with providing consultancy and running Proof of Concepts to explore the technology and its suitability in the London Commercial Insurance Market.

PJT Given your work over the last few years, you would seem to have an ideal perspective from which to comment on the future adoption of blockchain technology and how it is evolving. Even in early 2017, it seems that the word blockchain is likely to cause furrowed brows and a change of topic to something less challenging than public keys, distributed databases and hash values.

Before talking to us about how you have seen blockchain used, can you try to provide a brief business-centric overview of what a blockchain is and how it works?

GPN I have a fairly simple, albeit technical, definition of what it is: It’s a Write-only, cryptographically secured, distributed, programmable, database. It sounds quite boring and nothing massively new, in terms of what it is; and that criticism is fair. The magic happens when you look not at what it is but rather on what it enables “out of the box”. Each of the individual features can be delivered by existing technologies but it would be very difficult (and expensive) to provide them all as standard.

Part of what I do as a consultant is to get people excited about what the technology enables, not how it does it. Fundamentally, blockchain is a protocol (it describes how something is done). In the 1980s there was a protocol introduced called TCP with the IP layer added to give us TCP/IP. Most non-technical people haven’t heard of TCP/IP and techie people would struggle to explain how it works. However, everyone agrees that “The Internet” has changed the World and that’s what TCP/IP is used for. I usually try to move conversations on from what it is/how it works to what it enables and what benefits it brings (more of which later).

PJT It seems that sometimes while people might grasp the essentials of blockchain there is then a “so what?” moment.

In your experience, are there any key facts, examples of usage, or even just anecdotes that help the penny to drop?

GPN The major consultancies appear to be in the game of “who can publish the biggest number” currently when talking about potential savings that organisations could achieve. PwC suggested Reinsurers could save $5-$10Bn in reduced expenses. Accenture indicated banks could save $8-$12Bn p.a. and McKinsey suggested up to $110Bn saving in Financial Services over three years.

So, some attention grabbing numbers about the potential. Nobody has, Bitcoin aside, actually implemented anything at scale and delivered the magnitude of benefits proposed.

PJT Can you tell me a bit more about how Distlytics recommends blockchain is used and the advantages that this confers?
GPN The starting point is to emphasise that blockchain is not necessarily the right answer. There are occasions when a traditional database is better, or a change to a business process would deliver more benefit at lower risk. With each use case it’s important to examine key requirements and to map them against what blockchain can offer.

At one extreme, if the problem is around maintaining a central master list that teams within a single organisation can use then something like Master Data Services (or for a small firm, a central spreadsheet!) suffices. At the other end of the spectrum, if there’s a need for multiple parties to access a common data repository that is write-only (thereby providing good in-built audit), is distributed (and so cyber resilient), cryptographically stored (so cyber resistant), and would benefit from multiple parties having access to “their” data then a blockchain begins to look like a potential solution.

PJT What about the broader market, what compelling blockchain stories have emerged over the last 12 months?
GPN I’ve been attending blockchain conferences for several years (and have presented at quite a few). The technology seems to be following a familiar path – we’re not actually moving forwards that much. There’s increasing investment, lots of hype but very few examples of anybody moving beyond Proof of Concept. Whilst 2016 was the year of PoC’s, it’s hoped that 2017 will be the year of pilots and 2018 the year of productionisation.

There are however two notable exceptions. First, Everledger is putting diamonds on a blockchain to prove origination and authenticity as so reduce fraud and blood diamond trade. Second, Estonia, as a nation, is the first to put many of its digital services onto blockchain and it already provides a global digital identity scheme. There’s likely to be a big change in 2017 as projects move out of stealth mode (several financial trading exchanges are moving from PoC to pilot). Watch this space.

PJT Are there any newer features or capabilities, either existing or pending, which you see as providing greater utility based on blockchain foundations?
GPN The Bitcoin protocol code was released in 2009 (at that time the word blockchain wasn’t even used). Since then we’ve seen the launch of numerous other protocols (e.g. Ripple, Ethereum and Eris/Monax). There have been major developments in scalability (e.g. BigChainDB) and performance (SETL.IO) and the market is rapidly evolving with new protocols being developed and existing ones maturing. It is however still a fairly new technology.
PJT What challenges do you see to the wider adoption of blockchain, be these regulatory, legal, technical, to do with privacy (on both sides of the argument) or relating to people’s understanding of the technology and what it can do?
GPN I’m going to stick my neck out and say that regulators shouldn’t try to regulate blockchain. Just like how they don’t regulate relational databases or spreadsheets. What they do regulate is organisations and processes and how the technology is applied. So, regulators will take a great interest in cryptocurrencies and how smart contracts are used to auto-execute trades, etc. They’re unlikely to attempt to regulate the protocols themselves.

Privacy is going to be interesting with the upcoming EU GDPR. I’m writing a paper on this as there’s a range of issues to address (how do you delete a record from a write-only database?) As mentioned earlier, people don’t really need to understand how the technology works, they need to understand how it can be used. Likewise the regulators will need to develop their awareness. Kudos to the FCA who are running their Innovation Sandbox with 14 companies pushing the regulatory boundaries – of which eight of the projects are blockchain-based.

PJT Concerns around blockchain have sometimes centred on possible issues such as the enforceability of smart contracts in law, the potential for specific miners to monopolise a market (negating the benefits of the distributed model) and the time taken to mine new chain links not being compatible with some types of transactions. What do you say to allay the fears of people who raise these issues?
GPN It’s now generally accepted that “Smart Contracts” was a poor choice of words as they’re neither smart not contracts. It does sound more innovative that “computer programmes” which is what they actually are! There are several approaches to resolve the enforceability issue – The simplest is to retain existing, legally recognised contracts and reference them to the smart contract. The smart contract performs the execution of the contract and the original provides the legal wrapper. Another is to write smart contracts in a form that is legally binding and accepted. This is an opportunity that lawyers who want to write software are getting excited about (it gives them work!)

Miner monopolisation really depends upon which protocol is being used and whether the implementation is a public or private blockchain. Bitcoin is currently dominated by the computing power controlled by Chinese miners – and that’s making some people (and Governments) nervous.

Time taken to mine is, again, protocol dependent. Bitcoin takes around 10 minutes for a transaction to be confirmed, Ethereum is at least twice as fast, so neither are suited for low latency volume processing. By comparison, Symbiont claims 87,000 transactions per second and that should suffice for most processing requirements. Ethereum is working on its Raiden Network to offer very high speed processing too.

For those who have concerns about legality and performance I’d say that this is a rapidly evolving technology. In just a few years we’ve seen orders of magnitude performance improvements. On the legal side, there remains uncertainty and that’s why I suspect there’ll be a blend of old and new ways run in parallel until new precedents have been established in law.

PJT Many people will associate blockchain with its most well known implementation, Bitcoin. Not everyone will immediately have a positive reaction to this association. How do you address concerns that might arise relating to everything from the volatility of Bitcoins, to news stories of Bitcoin theft, to the perennial linkage with money laundering and the dark economy?

Given this less than propitious environment, how do you provide an alternative and more positive message?

GPN Every Bitcoin “failure” has been at the application, not protocol, level. Bitcoin thefts (e.g. Mt Gox) are rather like a bank being broken into – it doesn’t reflect a failure of pounds (or dollars). Most blockchain protocols are open source and the associated cryptocurrencies are worth millions. This means that they’re highly susceptible to attack and that’s actually what strengthens the protocol. Human beings develop immunity to disease through exposure to it and it’s the same with Bitcoin.

As for Bitcoin’s associated with Dark Web and drug dealing and other illicit activities, it’s true! However, dollars and pounds have been used to fund illicit activities too but that doesn’t erode people’s confidence in traditional currencies. Interestingly, crime prevention agencies actually like cryptocurrencies such as Bitcoin! Don’t tell the criminals but cryptocurrencies such as Bitcoin aren’t completely anonymous. In fact a complete ledger of every transaction is publicly available. This means the lineage of payments is easily traceable. As recent convictions of Danish drug dealers has proved!

PJT What industry sectors or business processes do you think blockchain is likely to have the greatest impact on in coming months? Are there any areas which you see as crying out for such a new approach?
GPN Imagine we’re in the 1980’s and the same question was asked a lot about the Internet! Financial Services have spent over $1Bn figuring out how to use the new technology but there’s a lot of work going on in Public Sector and third sector (i.e. charities) too. Having spoken with a wide range of people doing fascinating work, I reckon that it’ll end up transforming areas that we’re not even thinking about – there’s so much going on with copyright, media protection, music distribution, charity donations, etc. that we’ll probably be surprised by how widespread its adoption is.
PJT We have both spent considerable time working in insurance and reinsurance. An increasing number of commentators, including yourself, have suggested that blockchain can play a pivotal role in driving change and reducing costs in this sector. There has even been talk of alternative models, such as peer-to-peer insurance and of the possible disintermediation of brokers. What are your views on the potential of blockchain in Insurance?
GPN One of the powerful features of blockchain is that it provides an opportunity to fundamentally disrupt any business model that requires an intermediary. The insurance value chain currently involves multiple intermediaries, each of whom believe they add value (rather than cost). The work I’ve been doing in the London Commercial Insurance Market is paving the way for radical new approaches and could see the value chain between a client with an insurable risk and a capital provider underwriting the risk being dramatically shortened.

Brokers talk about removing the need for Underwriters and Underwriters question the need for Brokers in a future model. Blockchain enables both approaches and we could see radical changes in operating models as well as new products and services being developed. It’s possible that insurance may be augmented (or replaced) by alternative financial instruments that can be developed using blockchain. As an example, think of an insurance contract sliced into individual components that can then be traded in a marketplace – a new derivatives marketplace. Other financial sectors have Swaps, Options, etc. and this could extend to insurance as alternative mechanisms for risk mitigation.

PJT Are there any other aspects of blockchain technology, current or future, which you feel it would be helpful for readers to know about?
GPN Things are changing so fast, it’s likely that if I were to recommend something then it would be out of date before the interview is published. I would suggest that readers try to keep a watching brief on some of the bigger things – protocols such as Bitcoin, Ethereum, Ripple and Monax as well as technology consortia such as Hyperledger and also consortia specific to their sector (e.g. R3 I banking and B3I in Insurance).
PJT What is next for Distlytics?
GPN If a week is a long time in politics then it’s an age in blockchain. There is so much happening around the World. I’m working with a number of fellow consultants to build a Global capability, known as “Team Blockchain”, to help company board executives to better understand the risks and opportunities that the technology offers. I’ll continue to offer bespoke consultancy through Distlytics and will continue research into Distributed Ledger Analytics.
PJT What is next for Gary Nuttall and do you see blockchain as being at the centre of your future endeavours?
GPN I’m not a surfer but I think that blockchain is a huge wave of opportunity. It’s all about timing it right and choosing the time to surf it and, importantly, realise when it’s time for the next wave. There’s plenty to do in the blockchain space for a few years I reckon and then there’ll be another wave – Artificial Intelligence, Robo-Process Automation, Internet of Things are all growing (and in many ways complement blockchain nicely). Meanwhile I’ve become an advisor for Blocksure who’re developing a (General) Insurance platform. Having met many startups who’re working on prospective industry solutions, these guys are worth watching!

I’ll be monitoring how long the blockchain wave continues to grow and provide opportunities whilst watching the other waves. Of course, the really exciting stuff is when big waves converge and technology is no different – Blockchain, AI and IoT all provide massive opportunities. Now if we link them together then the opportunities become paradigm shifting.

PJT Gary, thank you for your time and the insights and information you have provided.

Gary Nuttall can be reached at Distlytics’s website is and Gary regularly tweets with the @gpn01 hashtag.

Disclosure: Neither Ltd. nor any of its directors have any direct financial interest in either Distlytics or any of the other companies or organisations mentioned in this article.

If you are a Chief Data Officer, a Chief Analytics Officer, a Director of Data, or hold some other “Top Data Job” and would like to share your thoughts with the readers of this site in an interview like this one, please get in contact.

From:, home of The Data and Analytics Dictionary, The Anatomy of a Data Function and A Brief History of Databases