As soon as we put things to bed, we begin to contemplate modifications for the next year to the Drucker Institute’s gauge of corporate effectiveness, which is grounded in the teachings of the late management scholar Peter Drucker and serves as the basis of the Management Top 250. We define “effectiveness” as Mr. Drucker did: doing the right things well.
For our 2020 analysis, we examined 886 major corporations in all, using 33 indicators across five categories: customer satisfaction, employee engagement and development, innovation, social responsibility and financial strength. Corporations are compared in each of these areas, as well as in their overall effectiveness, through standardized scores with a typical range of 0 to 100 and a mean of 50.
Sometimes, the adjustments we make to our statistical model are substantial. In 2019, for example, we revamped the way that we determine financial strength by adding to our mix of metrics “economic value added,” or EVA, which takes stock of a company’s operating efficiency, asset management, capital discipline and profitable growth.
Other times, we make smaller tweaks, such as when we eliminated a few indicators in 2018 to prevent the possible overweighting of data from the same provider.
In either case, our aim is the same: to better reflect Mr. Drucker’s core principles, which underlie the rankings, and to bolster the model’s empirical validity. (Our data sources, methodology and other details going back to 2017, when our model was introduced, can be found at drucker.institute/programs/company-rankings.)
This year, we undertook several revisions that were relatively minor—but that still affected how a number of prominent companies fared.
For starters, we fine-tuned what’s included in the customer-satisfaction category, ascribing far less importance to certain indicators that track how marketing professionals assess a business’s brand reputation and whether a company has a data privacy and security policy or program. The reason: Neither really captures a consumer’s experience (as opposed to what some experts think or what a company says it’s going to do but may not deliver on).
We also honed our approach in the innovation category. In this arena, how a company stacks up on a variety of different indicators is calculated relative to the industry average. That way, we aren’t comparing how many patents are filed by a software firm with those from, say, a retailer or an insurer.
The trouble is that companies don’t always reveal the activity they’re engaged in. This is particularly true when it comes to investments in research and development, where many firms fail to report any R&D expenditures. Previously in our model, this would register as $0, pulling down the industry average and, in turn, giving those that did disclose their spending an artificially high score. To correct for that, we now derive the industry average only from those companies that supply data.
In addition, this year for the first time we evaluated the extent of a company’s cutting-edge job postings—for positions in artificial intelligence, robotics, blockchain and so forth—and R&D-related job postings in the context of its total hiring.
For some in our rankings, these alterations had a notable impact.
For instance, largely because of how we reworked our formula, Amazon.com Inc.’s innovation score fell by more than 76 points from 2019 to 2020—though it still ranked No. 1 in the category this year with an off-the-charts mark of 135.9.
Meanwhile, Facebook Inc.’s customer-satisfaction score declined from 41.6 in 2019 to an abysmal 26.3 this year, as Clorox Co.—which has seen a surge in sales of coronavirus-killing cleaning products amid the pandemic—leapt from an already impressive 67.1 in that category to a sky-high 72.5. The movements for both companies were caused, in no small part, by how we changed the composition of our model.
And yet, while it can be kind of exciting to follow who is up and who is down from year to year, that is never our focus. What guides us is the data—not the drama—and a commitment to ensuring that the entire model is sound from a statistical standpoint.
To that end, the correlation between customer satisfaction and overall effectiveness increased to 0.58 in 2020 from 0.48 in 2019, while the correlation for the innovation category climbed to 0.77 from 0.71. Correlations of this type range from zero (signaling that the model explains nothing) to 1.0 (whereby the model explains everything).
As we look to 2021, we will continue to try to find that sweet spot: improving the model that we’ve built without going so far that we obscure the actual performance of the companies we cover.
This story has been published from a wire agency feed without modifications to the text.
