The Future of the CDO - The COO

Following on from the discussion of the 7 Habits of the Highly Effective CDO/CDAO I wanted to discuss the future of the role, where it should sit and to whom it should report.

The reality in 2023 is that most Chief Data Officers/Chief Data and Analytics Officers do not report to the CEO, rather to someone else on the Executive Committee such as a COO, CFO, Chief Commercial Officer, or a Chief Digital Officer. Some do report to a CEO, but as a ‘Staff/Strategy’ function, with majority of actual Data & Analytics resources distributed across the business and finally a very small percentage are full members of the Executive Committee and a key CEO direct report.

The History of the CDO 

There are disputes about where the first CDO was appointed, but there is definitive proof that Capital One had a Chief Data Officer in 2003, followed by Yahoo!, but by 2010 the role was starting to be established in banks and larger public sector organisations.

• The clue initially was in the name – the Chief Data Officer – and the responsibilities focused on data - governance, quality, management, and related regulatory compliance. Many of these teams were therefore an off shoot of the IT/CIO organisation and often worked to support separate Business Insight/Data Mining and Business Intelligence teams.
• In parallel, many consultancies, including Capgemini (where I was UK and Global Leader), and Accenture also established substantial data and analytics practices, and were therefore working with CIOs, CDOs as well as business intelligence and data mining teams.

Clive Humby (of DunnHumby) first coined the term ‘data is the new oil’ in 2006, but things really began to change in 2011/12, with the advent of the big data and big data analytics revolution and the emergence of the first data scientists.

• Data scientists, as with data miners and business intelligence professionals found that they were still spending 80% of their time on what became known as ‘data wrangling’ (in essence the traditional purview of the Chief Data Officers)
• It became more logical for Chief Data Officers to have responsibility for these new analytics and data science professionals with a focus on how to ‘monetise data’ for the business.
• For me it had always been a ‘no brainer’ as data and analytics are like yin and yang: you need good (not perfect) data to create great analytics (in a timely fashion) and analytics creates the value cases that supports the investment in good yin data management/governance and quality.

Whilst CDOs or CDAOs gradually appeared in more business organisations, it was seen still as a more ‘technical’ discipline, unlikely to report to a CEO, but as more strategic could report to the biggest user of analytics and data, which might be a COO, CFO or CMarketing/CommercialO and hence be more of a peer to a CIO.

The CDAO Today

The Chief Data & Analytics Officer sits in a truly unique role:

• Data is the fuel of the business – and the CDO is the person refining that fuel for the enterprise and enterprise systems;
• Data is the source of key decision-making insights – the CDAO produces analytics that generate insights and/or machine learning models that give predictive, prescriptive and potentially adaptive insights that allow the business to continually improve itself.
• Data is a source of revenue – more and more organisations see the opportunity to create data products and/or services that deliver insights that can be directly sold to an end customer (typically a B2B customer) to generate revenue.

Combining my research and industry experience I developed the Seven Habits of Chief Data & Analytics Officers (the CDAO), which are summarised below. 

1. Customers are King (or Queen):  Data is central to understanding your customers – what motivates them, what their needs are, and what they are inclined to buy (and for how much).
2. Masters of the External Environment: In addition to collecting great Customer Data, the real advent of ‘big data’ was the need to start to collect and leverage data from outside the organisation including video, audio, social media etc.  That data can be used to augment an understanding of customers and in addition central to understanding our external environment, competitors, and suppliers.  
3. Building a Data Driven Business Model:  In building your business model, it needs to be underpinned by an extendable Data Model.  The Data model should be built by looking at the Value Drivers of the organisation, which allows the creation of a KPI /Metric Model which gives uninterrupted line of sight between your Level 1 Key Performance/Results Indicators (like Revenue, EBITDA, Free Cash Flow) you report to Shareholders, and the underlying operational metrics of the business (Customer Lifetime Value, Cost of Goods sold, Employee Costs etc etc); as well as those critical Sustainability and ESG metrics. 
4. Governance and Regulation – Your Friend Not Your Enemy.  Data Governance has been seen as a problem and the enemy of successful Data Leaders, but in my opinion #Risk and #Performance are two sides of the same #Data. If you have a single Data Model, built in partnership with the rest of the business you have the nirvana to manage #risk, #performance and #sustainability. 
5. Migrating to a Data Driven (Micro Services) Architecture in the Cloud:  The Intelligent Business operating model is one where Data Serves People and masters Process and Technology.  Businesses need to redefine their operating model so they are not limited by the strait jacket of legacy ‘process models’, so that they can embrace a much more Agile approach. Processes will need to be dynamically reconfigured to meet the rapidly changing needs of customers and reconfigure what the business is delivering as Services.   
6. Servant Leadership – Data Serves People.  It’s all about people!!  And three key communities that need to be addressed.  The first community are your (external) Customers (mentioned in principle 1, Customer is King or Queen) – you must be using Data & AI to develop products and services that make a difference to the end customer.  The second community is the people within organisation – the whole concept of the Intelligent Business is to ensure that the Data in your business serves the people in your business to help them make better decisions, which improve service to the end customer and allow the organisation to deliver better revenues, lower costs and improved ESG outcomes.  That means upskilling the whole business and developing amongst other things ‘citizen’ data scientists as well as ownership of data amongst the whole employee population.  The third population is the Data & Analytics team themselves, and the job of the effective Data Leader is to create, grow and nurture a great team and provide them with exciting work that delivers transformational products and services for the other two populations.   Data rarely delivers value in isolation, it’s when it’s combined with other activities that it becomes an enabler, and a multiplier of value creation. 
7. Data Strategy Spins the Business Strategy:  Critically, your data strategy and more importantly the tactics and logistics you employ to execute upon it, will be at least as important as your people strategy in delivering your business outcomes and the data-enabled transformation the fundamental business change your business needs over the next 10-15 years. The reality is that we discuss data literacy as key, but ultimately data and analytics capabilities are not just part of the data team, rather data & analytics (DnA) needs to be central to the DNA of the organisation or business for it to be effective and productive to operate effectively in today and tomorrow’s world. How your business (or organisation) chooses to differentiate and deliver sustainable competitive performance, data and analytics capabilities will be a valuable, rare, difficult to imitate and the organisation therein will be both key to delivering that competitive performance as well as measuring and managing it. Many of you will have heard of the ‘Fly Wheel’ concept from Jim Collins and Good to Great. Of those quite a few will know that Jeff Bezos took that concept, and his strategy was to use data and analytics to spin the fly wheel at Amazon faster than anyone else! For everyone else this is why if you live in a business that may at some point come across or compete with Amazon you need a data strategy that spins your business strategy.

This unique position of supporting, enabling and directly delivering revenue (& profit) for the business makes for a position that should in theory be an Executive Committee role. That said, the typical CEO can only support so many direct reports, so where should the CDAO fit in?

The Future CDAO

Habit 7, Data Strategy Spins Business Strategy, talks to the reality that increasingly data is a primary source of competitive advantage (and critically a lack of capability gives an increasing competitive disadvantage). The other 6 habits address the points that the CDO must be:

• Deep understanding of the business and its customers, and critically, insight around the future of the companies’ markets and customers;
• Strong knowledge of process and technology and the way that data is key to driving them;
• Intimate knowledge of governance and regulatory implications;
• Excellent people-leadership capabilities, with the ability to build a capability that serves the whole business; and,
• To deliver this all together, requires great business transformation capabilities.

Putting those things together, it is central to my research hypothesis that exploitation of data (leveraging analytics and through that AI) is the singular most important incremental capability that organisations must build upon to deliver both sustained and sustainable competitive performance for the next 15-20 years. 

I have crystallised this as the transformation of an organisation into an Intelligent Business: one that uses insight to dynamically reconfigure itself in response to the expected needs of its customers, and simultaneously anticipate and respond to changes and events in the external environment i.e. an organisation that has truly embedded data and analytics capabilities into its organisational DNA. 

On the journey to becoming Intelligent Businesses:

• The winners will be leaders in their markets, and/or industries;
• The losers will disappear…

This has been electrified in the past few months with the exciting developments around Artificial Intelligence. AI is basically built on analytic models and the most common AI is machine learning based, where the algorithm learns from data, which logically implies that the CDAO is the person best placed to lead the business on its AI journey. The impact of tools like ChatGPT will fundamentally change whole industries in the coming few years.

Businesses therefore have no choice, but to transform to embrace these capabilities and frankly to avoid being blow away by the AI hurricane. However, let us not forget that transformations are painful, which is why they are only usually done every 10 or so years… That said, if my research and hypotheses are correct once a business has transformed into an ‘Intelligent Business’, it will no longer need to transform (except in response to a major acquisition or divestiture) as it will be able to continuously evolve and adapt ahead of the needs of markets and customers. In other words, the Intelligent Business Transformation, should be the last major transformation that a company needs to undertake.

 In my view there are therefore two futures for the CDAO, a short and a medium term:

• Short-term, the CDAO needs to support the CEO and become the Transformation Leader for the journey towards an Intelligent Business. If they can demonstrate a grip of the 7 Habits of the Effective CDAO, they are uniquely positioned to lead this change journey. Unfortunately, many CDAOs do not have all the requisite skills and experience, and will be weaker in 2, 3 or 4 of the key habits, in which case the CEO should look to partner them with another key executive in the business to drive the change. 
• In the medium term, when that transformation is done, the business is then designed for Change. Having led that change the CDAO either leaves or can choose their destination role, which for me naturally becomes the Chief Operations or Operating Officer (COO) who will use Data and AI to orchestrate the ongoing evolution of the business. Their combination of People, Data, Tech, Process and Change skills makes them the natural heir to this role, and as the CFO supports one hand of the CEO, the CDAO/COO will support the other.

 The Transformational CDAO, may not want to become the COO; instead, they may want to drive more change or assume more leadership. Having completed a successful fundamental change to a business and exhibited a rich set of operational and leadership skills it may be possible for the CDAO to progress to the ultimate role of CEO.

• Sharing my own prerogative, and having been a business unit leader or CEO, that’s not my own personal choice. I enjoy change too much and others are far better leading a company overall. 
• However, I do believe in the next 5 or so years the door is open for the CDAO to become the COO and if they want it, to push towards the door of the CEO!