Smart Decisions on a Shoestring?
It’s common sense that corporate investments in large enterprise software systems would become more difficult to justify during a downturn, and a couple of studies out this month indicate that that’s the case. But the goal of business performance management (BPM) software — gaining better insight into the true drivers of a business’s performance so that decisions made within the organization optimize its results — is even more crucial when good results become harder to achieve.
For organizations that can afford to buy services and technologies to improve the insights provided by their BPM activities, those improvements are as likely to pay off today as they were back in boom times. But for organizations that simply can’t afford external advice, the results of a new McKinsey & Company survey might help improve decision-making on the cheap.
McKinsey spoke with more than 2,500 executives in a wide range of industries, functions, and geographic regions about one specific capital or HR decision that their company had made. The study explored how successful each of these decisions was and examined what factors influenced its success. Two-thirds of the decisions met or exceeded the company’s expectations for revenue growth and/or cost savings. Still, the survey was able to pinpoint activities that correlate, either positively or negatively, with smart decision-making.
One factor that can affect a decision’s success is the identity of the decision’s initiator and its approver. More specifically, the decisions in the survey that were initiated and approved by the same person generated the worst financial results. Collaboration, it seems, improves the likelihood of positive outcomes. When McKinsey delved more deeply into the nature of collaborative activities that boost decision quality, the firm was able to identify three characteristics that appeared to substantially affect decisions’ results: choosing participants in the discussion based on individuals’ skills or experience, reliance on transparent approval criteria for the decision, and discussion of the decision’s place within the company’s entire portfolio of decisions. What else helps a company make better decisions?
Four analysis activities emerged as beneficial: performing sensitivity analysis and financial-risk modeling, considering comparable situations from the decision-maker’s or the company’s past experience, considering the decision’s risks in light of the company’s entire portfolio of projects, and creating a detailed financial model of the decision. Those that took this last step and generated NPV, IRR, ROIC, or another type of financial model before proceeding with the decision saw the results of that decision beating expectations for revenue, profitability, and/or speed to project completion by more than 50 percent.
Finally, McKinsey considered the role of corporate politics in decision-making and made a somewhat counterintuitive discovery. Although the study found that political maneuvering is detrimental to decision quality when those engaging in the politics are looking out only for the interests of one business unit (rather than the interests of the organization as a whole), it also found that some “horse trading” can be beneficial, particularly in achieving a better-than-expected speed to project completion.
Changing a company’s decision-making climate from top-down to collaborative, or dramatically increasing analysis activities, is obviously not a quick fix for a business that wants to improve management on a tight budget. How decisions are made is a cornerstone of corporate culture, and one that is difficult to dislodge. Nevertheless, the McKinsey results come at an interesting time. Perhaps an organization that has had to postpone a large BI initiative will find less daunting a project that presents a portfolio management view of decision-making. Or, on a smaller scale, maybe a company will be able to improve the quality of its decisions by more carefully choosing which people are involved in the discussion.
What activities have you found to positively or negatively impact the likelihood that decisions in your organization will be successful — in other words, that they’ll result in outcomes that exceed expectations? I’d love to hear from you.
