Companies are investing billions of dollars in building their data assets in the hope of becoming data-driven.
What leaders don’t realise is that having the data and using the data for business are two very different things. This is not to say that they won’t benefit from good data. Everyone can benefit from good data and nicely done analytics but that makes you ‘data rich’ not ‘data-driven’.
Becoming Data-first or AI-first is the new battle cry. But what does it really mean? When Jeff Bezos wanted to steer Amazon as an ‘API-first’ service-oriented company in 2002, he released the following mandate:
All teams will henceforth expose their data and functionality through service interfaces.
Teams must communicate with each other through these interfaces.
There will be no other form of inter-process communication allowed: no direct linking, no direct reads of another team’s data store, no shared-memory model, no back-doors whatsoever. The only communication allowed is via service interface calls over the network.
It doesn’t matter what technology they use.
All service interfaces, without exception, must be designed from the ground up to be externalizable. That is to say, the team must plan and design to be able to expose the interface to developers in the outside world. No exceptions.
The mandate closed with the instruction ‘Anyone who doesn’t do this will be fired. Thank you; have a nice day!’
This may sound too harsh but Bezos meant it and he wanted to make it clear what was at stake. Amazon’s subsequent transformation as A-Z marketplace and the development and growth of Amazon Web Services are the witness to the effectiveness of his relentless approach. If you truly believe that you want to be Data/AI first, then ask yourself — what is at stake for the business? Is it growth, innovation, competitive advantage, margin, customer trust or a combination of all these and more?
Another question you must ask is if Data/AI is not your first priority today, then what is?
In traditional companies, today rules and processes are at the core of all business decisions. When business rules define what needs to be done and processes define how it needs to be done, the entire business becomes a rule-processing machine where people exist to just run it.
The true meaning of Data/AI first strategy is that you put information or prediction at the core of all your business decisions.
Data/AI first approach means breaking down and converting this machinery into business tools and empowering people with the right information and autonomy to decide business outcomes and take business decisions.
Anne Thomas, vice president and analyst at Gartner said, “Digital business demands a rapid response to events. A convergence of events generates a business opportunity, and real-time analytics of those events, as well as current data and wider context data, can be used to influence a decision and generate a successful business outcome.”
The precursor to data/AI driven business strategy is ability to handle business events. Events are the future of business intelligence and business processes. The traditional management approach uses reports and transactions of the past to take decisions of the future — it is reactive by design. It is like driving looking in the rear-view mirror. But the events happen in the present and need intelligent responses in the present.
“The degree of agility or responsiveness of a company can be measured by its average lead-time in intelligently and decisively responding to critical business events both positive e.g. new customer order, customer appreciations, new business opportunity, new product idea, new regulations and negative e.g. machine failure, raw material delay, customer churn, fraudulent transactions, cyber attacks, low inventory etc.”
The rule-based strategy is like procedural programming where the procedure and rules take precedence over the business outcome or event response. Processes and tasks are pre-defined based on a set of business rules. An events-driven strategy is like object-oriented programming where business outcome and response to business events take precedence. Business processes are a set of ‘event responses’ derived from the lessons learnt from processing events and solving problems to get the desired outcome.
“Application of Data and AI facilitate business outcomes in event-driven business strategy by providing context and understanding to events and how they impact the expected outcome.”
Event Driven Architecture (EDA) is a key technology approach to delivering this goal,” says Thomas. “Digital business demands a rapid response to events. Organisations must be able to respond to and take advantage of ‘business moments‘ and these real-time requirements are driving CIOs to make their application software more event-driven
Data/AI provides the ‘business context’ which when merged with the event stream allows identifying the underlying situation, analysing its root cause and developing potential next actions. Understanding of events and their causes is the fastest route to achieve the expected business outcome. The fastest route to any given problem cannot be known beforehand. It is an iterative process that evolves with the events, information, decision, action, result (next event) and so on. It is like a game of chess where every next action depends upon the past actions and response from the environment. Over time, some of the event sequences can be standardised as named strategies or standard operating procedures (SOP).
In the pre-digital era, business processes were stable and outcomes were predictable. This allowed companies to develop lean and robust processes that served their purpose most of the time. In today’s world, variability and volume of business events is so high that it renders any attempt to design an overarching process. Responsiveness beats efficiency to the second place. Lack of responsiveness means lack of competitiveness and lack of trust from the customers. There is no fun in being the most efficient ‘out of business’ company. And that’s what blind adherence to static processes leads to.
In the digital era, analysing and responding to a critical event takes highest priority. Solving the problem is important, the steps taken to solve it are not. Contextual guidelines, policies and heuristics are more valuable to problem solving than standard operating procedures.The effectiveness of the problem solving activity can be strengthened by empowering people with ‘data-rich’ business systems and tools. The strength of a business system is to pull in streams of structures and unstructured information to drive and manage the lifecycle of business events to achieve business outcomes. But if a person isn’t able to take decisions and actions in real-time, all the data and AI in the world won’t help.
Ultimately, it’s the ‘ability to respond to events’ that distinguishes data-driven companies from data-rich companies. It is the response that really counts.
“This business event lifecycle is ultimately being driven by big data. Multiple points of input are correlated against (run against) business rules, policies, computer inference, and from this, dashboards and reports of the results are provided to enable human inference and human decision-making, allowing action to be taken or captured, to which further information is applied informing the next step to take. Thus, the “process” is not a hard-wired workflow per se, but a template for guiding actions and decision-making through a host of input run against a set of rules and sub-tasks defined within the system.” Excerpt from the book ‘How Knowledge Workers Get Things Done: Real-World Adaptive Case Management’ by Nathaniel Palmer and Max Pucher
The only way to be data-driven is to use data at every possible decision point for every important business event to inform action and create more data for learning. It means being responsive to critical business events and to incentivize experimentation, creative problem solving and continuous learning. It means getting rid of rigid ‘blind’ rules and replacing them with analytical insights that have real contextual significance in real-time. This requires a change in attitude, culture and management philosophy of the organisation. If you are not simultaneously working on these ‘soft aspects’ of business, investments in tools and technology alone cannot cause a transformation.
About the Author:
Somil Gupta is an AI Strategy Advisor for Nordic Manufacturing and Retail Companies. Before starting this practice, Somil led Digital Business Development for digital and AI solutions for Bosch in the Nordics.
In this role, he was responsible for taking Digital Solutions to market, consulted C-Suite executives in understanding the disruptive impact of digital technologies e.g. IOT, AI, Blockchain and AR/VR and plan organisation-wide systems and processes to create business value in customer’s business segments. Somil specialises in Agile Business Development, Agile Business Operations and Technology monetization.
Using writing, consulting and training as a way to share his expertise, Somil helps leaders and managers to get ready for disruptions and ride the wave of change and leverage technology strategically in the fast changing world.
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