Decision-Centric Outcomes: Removing Limits to Scale, Scope & Learning

In a recent Harvard Business Review article, “Competing in the Age of AI,” Harvard Business School professors Marco Iansiti and Karim R. Lakhani noted that businesses that lead with and lean toward agile decisions will enjoy unbridled growth. The compelling thing about implementing these new technologies is that it’s not just hype or trend. They are part of a silo-busting path to superior data management and better thinking and decision-making with real data.

Let’s look at the science of decision making. If you cannot trace accountable components to their end, then the data is not trustworthy. Decisions made from those sources have likely been formed with errors and therefore cannot be accurate. While large enterprises have a plethora of business tools, they often keep data as isolated sources, ultimately requiring spreadsheets to make sense of it all. Human intervention invites fat fingers and invalid documents. Hours and even days and weeks are wasted preparing material that is rendered “dated” the moment it is plunked in a spreadsheet.

Using AI/ML and live data, leaders can aggregate data at scale. You need a vision that allows you to see inter-dependencies associated with a prescribed algorithm, as well as an archive of past decisions and the data behind them. That algorithm directs how changes and predications are applied to each new sub-factor or KPI.

As these variables are measured and monitored, outputs start to reveal a pattern that emphasizes one decision over another. You want to see support for your decision, but you also need to see alternative scenarios that take into account changes in budget, time, parts or service. Dashboards bring this all together in a visual framework that shows proof of each hypothesis in a live story versus a static cell. 

Consider applying it to military leadership. Leaders in that environment need to know the various conditions of their ships and vehicles, such as the age, repairs in progress, parts needed, etc. Instead of keeping that information in spreadsheets, they can keep it in an open format. Using visual dashboards with live data, they are able to examine scenarios to bolster their fleet. They could also view multiple spending options and make decisions on whether they need to build new vehicles and how much that might cost. Human capital, the role of the soldier, could be measured and articulated, as well as the number of people needed for roles throughout their departments.

You could also consider geopolitical situations, which draw on several variables. An organization needs to ingest subjective facts, but then make them objective. Senior leaders could be trained in tracking the components that lead from one decision variable to another as they draw their hypotheses.

Regardless of industry, most businesses can’t afford to lose time and money on siloed data and spreadsheet-based decisions. AI/ML tools govern the data we need to identify and pursue a strong course of action. Visual stories help us communicate and understand more primally and with greater efficiency.

That’s the competitive edge, and that’s where AI/ML can deliver decision confidence.

Check out our partner Coras for outstanding decision management SaaS options.