“We’d be able to make a much better decision on this if only we had data on that.” If you’ve heard that lately, you’re not alone. In 2021, that missing data might be on vaccines. In 2020, it was likely data related to COVID-19 and its effects.
But those are just highly visible examples of what senior executives have struggled with for years: Too many business decisions rely heavily on data and analytical models designed for the status quo. When the context changes, decision making can’t keep up.
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We still make decisions as we did decades ago. Things need to change.
Rethink the role of data and analytics in effective decision making
For every organization, decision making is a core undertaking that is becoming more complex. Decision making involves much broader considerations — their potential impacts extend across enterprises — and the lines between strategic, tactical and operational decisions are blurring.
Effective decision making requires business leaders to reframe what is essential, who or what is involved — and rethink how to leverage data and analytics to improve decision making. The result will be a new core competency, driving better business outcomes.
Critically, this isn’t about reengineering every decision; it’s about applying this reengineered thought process to the most important and impactful decisions — those that can’t be made effectively with traditional approaches.
Consider what kind of data you need, what data you could exploit, what pieces of the decision making are best left to humans and what should be handled by machines. And determine the collaborations that are critical, rather than what you can manage.
What effective decision making looks like
In a recent survey, Gartner found that 65% of decisions made are more complex (involving more stakeholders or choices) than they were two years ago. The current state of decision making is unsustainable.
To reengineer decisions in a way that deals with higher complexity and uncertainty, good decision making is more connected, contextual and continuous.
No decision stands on its own. Decisions by one actor affect other actors in the enterprise and ecosystem, and vice versa. Decision making needs to become much more connected, on all levels — not only hierarchically (strategic > tactical > operational), but also in a networked sense. Sharing of data and insights across organizational boundaries is critical.
Decision alternatives need to be evaluated in a context-sensitive manner, beyond the scope of the individual event or transaction. Organizations often neglect to give their own business data and analytics the same personalization that they know a consumer would expect.
Organizations must be as responsive as possible to opportunities and disruptions. Decision making is becoming a much more continuous process in which organizations need to keep their options open.
Effective decision making — that is connected, contextual and continuous — results in a host of business benefits, including greater transparency, accuracy, scalability and speed.
What decision making traditionally looks like
Effective decision making is also much more inclusive. It takes all necessary stakeholders into account and is collaborative. It scrutinizes multiple aspects of a business opportunity and takes place where it matters most to your customer, citizen or organization.
Consider a midsize industrial parts company. Traditionally, supply chain decisions were made by discrete, siloed teams, one at a time. They didn’t consider the scope of the supply chain, much less other interconnections like the impact on order-to-cash.
The company’s decision making might work, but does it work well? Further, does it work well in the era of digital acceleration?
What reengineered, effective decision making looks like
Consider how to make these decisions with a connected, contextual and continuous mindset. The conversations begin much earlier in the process and include more stakeholders asking what data and which insights would enable a more impactful outcome.
What if we wanted to optimize the decision for both production and the supply chain? How do we then predict the conditions that would cause a change to our playbook before they occurred?
You might even consider optimizing across production, supply chain and sales, where excess supply results in digital offers to customers most likely to accept the deal. This changes the conversation from one about supply chain to one about optimizing the business at a higher level with all the involved stakeholders.
Striving to make decisions more connected, contextual and continuous is the same thought process driving the use of digital twins of machines for predictive maintenance — or even of the entire business. In the public sector, it drives the desire to optimize and coordinate citizen services across agencies. Simply put, it’s about providing a better understanding of the bigger context and enabling continuous decisions that are connected across the entire environment.
You can’t (and shouldn’t) automate everything
One might jump to the conclusion that any reengineering of decision making should try to eliminate the last unreliable element in the process: the human. Many firms assume hyper-automation means the automation of everything. But that would be unfortunate.
Automation has its place. Augmentation is ideal where actions and work are repeatable but data can add intelligence. But in general, machines and humans each have a role in effective decision making. Human decision makers certainly shouldn’t be replaced everywhere; rather, they should be complemented by the power of data, analytics and AI.
If all these elements are carefully orchestrated, the result can be a rich synergy arising from the combination of humans’ common sense and practical experience with the insights that AI models and algorithms can derive from ever-larger amounts of data.
Why good decisions matter
Decisions should be a trusted, reliable core capability for every organization and its people. Without making effective and efficient decisions, the organization is adrift, or blind to changes in market conditions, customer perceptions and citizen behaviors.
Effective decision making, reengineered to be connected, contextual and continuous, accounts for uncertainty and improves our ability to add clarity to once opaque considerations. It becomes a competitive differentiator. If you are able to handle more uncertainty than others, comfortably and with skill, then you have the ultimate advantage.