The Seven Habits of the Data Enabled, AI Powered “Intelligent” Enterprise

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For decades organisations have been talking about how they leverage Data and Analytics to enable competitive performance, and yet even many of those who claimed to succeed at some point, don’t always seem to succeed over the longer term.? Despite many hundreds of articles and case studies in Forbes, HBR there is no manual for how to deliver Sustained and Sustainable performance using Data, Analytics and AI.? The seven habits of the Highly Effective Data Enabled; AI Powered Business (aka The Intelligent Enterprise) is my answer to this.

?In my opinion, Data & Analytics leadership is not about Governance, Architecture, Machine Learning modelling or other Technical Disciplines.? Borrowing from Stephen Covey, I’ve created 7 Habits of the Highly Effective Data Enabled, AI powered business, and those Habits are 80% leadership and 20% Technical.? The role and the habits are fundamentally about business transformation. ?

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• Why – Data is both the fuel of business processes, and the material from which insights are derived to better improve decision making in the business.? It is therefore the primary means for improving People, Process and Technology performance in your organisation – in other words Transformation.?
• When your Transformation is ‘completed’, you will have reached a state of perpetual evolution and/or adaptation, what I’ve called an ‘Intelligent Enterprise’.? Or to borrow the famously misquoted Charles Darwin? “It is not the strongest of the species that survives, nor the most intellectual that survives. It is the one that is most adaptable to change.”

?In fact, when I work with many organisations and talk about their business and then their IT, the problem is they don’t really have ‘Information Technology’ they have Technology.? Organisations treat Data as another ‘Technology’ and are not using Information to connect the processes and decision making around their organisation.?

?The Intelligent Enterprise

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I first coined the term ‘Intelligent Enterprise’ in 2004, as a development of the term ‘Adaptive Enterprise’, which was all the rage after the millennium.? The folks who coined that were limited by a lack of understanding of the importance of data and using it to drive insights and decisions, which is where this definition arose!

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The Intelligent Enterprise is an organisation that utilises predictive and adaptive 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.

?Reaching this Intelligent Enterprise state, requires a Transformational Strategy and Plan.? Whilst you will hear a lot about Data Strategies, and Data Transformations, the scope is typically far too narrow and are insufficient to help an entire organisation to transform.? What is required is an understanding of what makes your organisation perform, and that requires strategic management theories.?

?Almost all of us have heard of Michael Porters Five Forces and Value Chain, which helps an organisation to develop its competitive strategy.? Having spent 2 years looking at Strategic Management theories as part of my Doctoral research I would say that Porter’s work is now almost 50 years old, and the world has moved on somewhat since then.? The prevailing academic research looks towards two newer theories:

• ‘Resource Based Theory’ (RBT), which focuses on the capabilities that businesses and organisations use to create sustained competitive advantage.? On the basis that you can’t be ‘world class’ at everything, you should focus on one or two capabilities that will give you competitive advantage.? RBT identifies those truly differentiating capabilities if they are Valuable, Rare, Inimitable (difficult to copy) and Organisationally embedded (VRIO).
• ‘Dynamic Capabilities’ seem to help explain how organisations can really survive and thrive in the Volatile, Complex, Uncertain, and Ambiguous (VUCA) 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.? In essence your capabilities to change and adapt quickly, which is uniquely important to the ‘Intelligent Enterprise’ definition.

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In the case of Digital, Data, Analytics and AI, we have a fixation on Tools and Technology! The Technology is the table stakes, but it is not the source of competitive advantage.? If we consider the VRIO of Resource Based Theory, unless you are a Tech firm, Data and AI technology does not pass the VRIO ‘sniff test’.??

• Technology is increasingly one of the biggest tangible assets on many company balance sheets.?Technology can be uniquely valuable, and companies can organise themselves to capture the Value (albeit many do not make a success of this).? However, whilst Technology can be expensive if you are buying Commercial Off the Shelf Software (CRM, Cloud, ERP, BI etc etc) it is by not costly to Imitate and clearly far from Rare!? For example, Visualisation Tools like Tableau, PowerBI and Qlik are pretty much interchangeable.
• Organisations thinking of spending money on the latest Data Mesh, Data Platforms, Analytics and AI platforms need to fundamentally recognise the fact that the tools themselves may be essential, but by no measure confer a source of Competitive Advantage.??

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Therefore, combining these two strategic management theories and my 25 years of making organisations perform using Data, Analytics and AI, (borrowing from Stephen Covey) I have developed the Seven Habits of the Highly Effective Data Enabled and AI Powered Organisation.? Considering these seven habits forms the outline of the Practitioners Guide to delivering the Transformation to an Intelligent Business.

Seven Habits of the Highly Effective Data Enabled and AI Powered Organisation (Intelligent Enterprise)

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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.? The Seven Habits are as follows:

1. Customer and Customer Experience First:? This sounds like a statement of the obvious, and yet too many organisations do not put the customer first!? 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).?? In fact it is not Data, but Data with Context, which is Information, which is key to understanding Customers, Suppliers, Financials etc.

This may seem pedantic, but as Confucius said ?“The beginning of wisdom is to call things by their proper name.”? ?We need to stop talking Data and start talking Information!

I see companies prioritising Finance and islands of Data in Marketing, Sales that don’t talk to each other.? In one company it took 2 years to even agree on the data definitions between Sales, Marketing and Finance… The great companies combine all the Information they need to predict the needs of their customers and designs products and services that meets those future needs.? As Steve Jobs famously said, ‘My Customers Will Know What They Want When I Show It To Them!’.

?Whilst most of us lack the genius of Steve Jobs, when Data Leaders work 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 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.? It is therefore critical that you make the collection of data about your customers the central pillar of your journey to an Intelligent Business, 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.

?Ultimately if we are talking about serving customers you will be talking about Value and contribution to the top and bottom line of the business, something which is scarily absent from the conversations of many Data Leaders, and yet critical to engaging and maintaining the support of the CEO, CFO and other business leaders.

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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!? That long history lesson is the precursor to the importance to being Master of the External Environment.?

In my language in driving insights from the External Environment is the need to understand both ‘strong’ signals and ‘weak signals’.

• Strong Signals come from your structured Data Warehouse and the sophisticated analytical techniques they can be exploited with, giving large amounts of data to train Machine Learning models which allow them to develop sophisticated correlations and sometimes actual causation that and will help you with immediate models (as in ‘Customer is King’ – Churn, Propensity, Decisioning!).?
• Weak Signals come from the external environment.? The most obvious ones of late would be the full implementation of Brexit, the Russia/Ukraine conflict, and the COVID-19 Pandemic.? These would, if correctly interpreted have told us in March 2020 and March 2022 that are highly curated Machine Learning Models would rapidly start to deliver us horribly inaccurate results.

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3.??? Develop a KPI/Value Driver Business Model with an Information Foundation:? I see companies spending millions on Dashboards and ‘Democratising Data’, but those organisations lack the strategy and understanding that aligns those Dashboards to how the business should be performing.? One critical people forget is that Data is both an Input and an Output to business processes.? Too many companies and their data leaders only focus on the output data and the metrics associated Revenue, Profit, Free Cash Flow etc.? These measures are obviously critical, but they only tell you how you have done – they are ‘backward looking’ by Design.?

The leading businesses, look at Input Metrics as well as Output Metrics, after all Information is the fuel of the business and therefore drives the processes that operate the business.? Input Metrics could include Page Views, Stock Availability, Price, Discounts, Convenience.? To institutionalise this, you need to build an extendable Data Model for your business.?

The Information 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.??? 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.?? Your AI and Machine Learning Algorithms are your source of competitive advantage.?

MACH (microservices, API-first, cloud-native SaaS, headless) are the design principles behind modern enterprise technology. Built to integrate easily, these technologies are helping companies untangle and step off their legacy tools. With a modular design, MACH solutions give businesses the freedom to choose from the best tools on the market today and provide a structure that makes it easy to add, replace, or remove technologies in the future.

Over time we can then migrate away from the ERP, CRM platforms and in their place, you need dramatically downsized and become what Technologists call 'Micro Services' - at a fraction of the cost.?? Microservices are an architectural and organizational approach to software development where software is composed of small independent services that communicate over well-defined APIs.? Microservices can be developed by your #CTO, a trusted software vendor and/or provided OpenSource.?

We connect the Data Model to the micro-services with APIs which can be delivered by your #CDAO and #CTO working together and mastered by your integrated Data Model.?? As you build more, you can pull more and more logic away from those complex monolithic ERP and CRM platforms.? The business becomes more agile and data driven by design!? As more logic moves into your Data estate, your monolithic business process systems (CRM, ERP, SCM etc) can be dramatically downsized and replaced with ‘Micro Services’ at a fraction of the cost.??? As we discuss in the principles above, too many companies only focus on the output data and the metrics associated Revenue, Profit, Free Cash Flow etc.? These measures are obviously critical, but they only tell you how you have done – they are ‘backward looking’ by Design.? The leading businesses (like Amazon), look at Input Metrics as well as Output Metrics, after all Data is the fuel of the business and therefore drives the processes that operate the business.? Input Metrics could include Page Views, Stock Availability, Price, Discounts, Convenience.?

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For those organisations, Data becomes the master of process and technology in your strategy and input (as well as output) metrics are the fuel and instrumentation that drive you forward! ?As you build more AI algorithms and models, more and more logic moves from those process centric enterprise systems and into a data enabled AI powered brain of your business.? 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.?

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5.??? Compliance by Design - Risk and Performance two sides of the same Data.? 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.? The data you need to sell, target, cross and up sell to your customers, is the same data you need to evidence to regulators that you are abiding by their laws and regulations – so why do we treat them as parallel universes??

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.? Combining that with a Data Driven Cloud Architecture, you can dramatically simplify technology and reduce costs.? Imagine using the same systems for Risk Management, Compliance and for Marketing?

Building a network of Data Owners and Data Stewards in the business, who will be your arms and legs (and use the data every day, so it’s in their 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!??

6.??? Servant Leadership for Data and AI Services.? There are many definitions of Servant Leadership, but the term originally came from the leader who is only noticed when they are gone.? Great Data Leadership is like that, we make other people the heroes and it’s all about people!!? 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.??? Spin Strategy with Data and AI:? Bringing the continuously adaptable Intelligent Enterprise to life requires a Capability Flywheel.? Many of you will have heard of the ‘Fly Wheel’ concept from Jim Collins and his famous business book ‘From Good to Great’.? Of those quite a few will know that in 2001 when Jeff Bezos was rebuilding Amazon (post the Dot.com crash) and took that concept, and his strategy was to use input and output KPIs and associated Data and Analytics to spin the fly wheel at Amazon faster than anyone else!?

?This becomes the heart of the Intelligent Enterprise, where we move away from the traditional People, Process, Technology model (which in practice was Process, drives Technology, with People as the business case), to a new Operating Model framework of People, Data, AI with Process and Technology as second order concepts mastered by Data and AI.? The essence therefore is that Data, Analytics and AI move from being a ‘bolt on’ to the operating model, to ‘built-in’, and core to the DNA of the business.?

?With that in mind, the famous quote of Gen Omar Bradley is that ‘Strategy is for Amateurs and Professionals discuss logistics!’ ??The Intelligent Enterprise is not a strategy framework, it’s a logistics framework to help you build a business fit for 2030 and beyond.? The key logistics here is that for a Business Strategy (powered by Data) is that Data is both an Input and an Output, and with AI masters process and technology.?

?The Intelligent Enterprise and the Seven Habits are my first steps towards creating an empirical framework that organisations and leaders can utilise to deliver sustained and sustainable value from Data, Analytics and AI.

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