Building a Business to survive and thrive in the world of AI - Seven Habits of Highly Effective Data, Analytics and AI Leaders

The advent of Generative AI and its ‘non-identical twin’ Reinforcement Learning are leading to fundamental disruptions of entire industries.??We need to see Data, Analytics & AI (DAI) Leaders as people who help their businesses surf rather than get swamped by this wave everybody has access to the technology and that continues to develop and raise the bar, but it’s the skills you must exploit the technology and how you ride the wave that makes the big differences.?

Combined with 25 years in the Data (and Analytics & AI) industry, as a ‘Chief’ for multi-nationals in multiple industries and global consulting Leader at Capgemini and KPMG, I am also researching for a Doctorate around how these capabilities can deliver sustained and sustainable competitive advantage for a business.

• 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.??

But where do we start???We hear a lot about Data Strategies, but surely, they are insufficient to help an entire organisation to transform.??There has been no ‘5 Forces’, Value Chain or 6 Sigma for the world of DAI, so my Doctoral research has focused on ‘Resource Theory’, which focuses on Valuable, Rare, Immutable and Organisational (VRIO) capabilities that businesses and organisations use to create sustained competitive advantage.???Resource Theory has come to prominence in the 21st?Century and along with another theory ‘Dynamic Capabilities’ seem to help explain how organisations can really survive and thrive in the complex and Volatile world we live in where CEOs are not just facing the challenges of AI, but also squaring the circle between Financial Performance and their own and investor needs to deliver ‘sustainable’ (Net Zero) performance.

Technology and Tech Vendors dominate the DAI landscape, but when you consider VRIO in the context of the DAI world, you can see there are multiple almost interchangeable Data Management, Analysis, Analytics and Data Science platforms and similar Cloud platforms to host them.??That tells you that Technology fails the VRIO principles, and therefore, whilst Technology is a fundamental enabler for your Data journey, it is in no way a source of competitive advantage.??

Not being distracted by the many different new shiny vendor solutions is the first key challenge for any DAI leader who wants to help their CEO transform the business.??For me, the first step in this journey in using the VRIO Organisational principle the organisational management and governance of Data & Analytics and AI are in my experience symbiotically connected, and the leaders who bring them together can therefore truly differentiate their businesses.??Therefore, combining my research and industry experience I am developing the Seven Habits of Chief Data, Analytics and AI Leader.??The Seven Habits are as follows:

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).???The great companies combine all the data they must predict the needs of their customers and designs products and services that meets those future needs.??They achieve that when their Data Leaders works in partnership with product, marketing and customer stakeholders and identifying the opportunities where Data, Predictive and Prescriptive Analytical Models (Machine Learning and AI) can be deployed to create transformative products and services for Customers.??If you think that a typical Credit Rating agency uses about 100 Data Attributes to provide a Customer Credit Score, a leading Grocery Retailer has c.1000 data attributes to tune products and promotions for their customers, but the likes of Amazon and Google have 25,000 (!!) attributes of data about each of their customers, your Data Leader and how they can collect, manage, refine and fuel data for your Marketing, Product and Supply Chain will be one of the critical, if not the most critical Value Drivers of your business.
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.??Those companies that live in highly competitive markets have already had to understand this, they use data and analytics to understand what competitors and new entrants are doing and aim to be at least one step ahead. As markets and environments become more and more volatile, all businesses need to be more agile and data is central to sensing, identifying, and responding to potential external challenges as, and when, if not before they happen!??
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.??The Data Model can be built around that core performance model and will be owned by your Data Leader.??A Data Model will be central to your business operating model and facilitate the migration of your process model into the background.?I weep when people say they can’t measure the benefits of Data investments… Why, because the discipline of Data & Analytics, includes Business Intelligence and Reporting!??In other words, the smart Data Leader is also accountable for providing the key reporting of business performance, so you have the absolute levers at your disposal to measure whether the initiative you’re accountable for has made a difference to the cost, revenue and/or profitability of the business!?
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 .??That’s easier said than done, and just understanding the components of Cost, Revenue and Profit in a large business is a substantial undertaking.??Building a network of Data Owners and Data Stewards in the business, who use the data every day, and hence have a vested interest for it to be right is critical and cost effective.??Furthermore, central to the privacy laws of most countries is a set of principles that define how personal data are collected, shared and processed. However, consumers often do not know the benefits and costs of the data that pertain to them. Data Leaders need to understand those laws and work closely with Legal/General Counsel (the Data Protection Officer) as well as Marketing, Sales and Finance – typically the data you use to market and sell to a customer is the same a regulator wants to know that you sell and market to a customer and whether you have their consent!??
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 straight 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.???As more logic moves into your Data estate, your monolithic business process systems (CRM, ERP, SCM etc) can be dramatically downsized and become what Technologists call ‘Micro Services’ – at a fraction of the cost.??We will do that with APIs, machine learning and analytics, all supplied by your Data & Analytics leader, and managed by your integrated Data Model.??Your Technology Estate is increasingly sitting, not in your premises, but in the Cloud, and with your Data available in one (or multiple cloud platforms) and liberated from the control of your 'enterprise systems providers', your business can take control of the Data Model and use that to drive agility across the organisation.
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:??A Business Strategy for the 2020s does not contain a chapter or pillar about Data, Analytics and AI, rather they are fundamental to every aspect of your business and the change your business needs over the next 10-15 years.??The reality is that whilst we discuss Data Literacy as key, but ultimately Data and Analytics capabilities are not just part of the Data team, rather Data & Analytics 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.

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