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Moving Beyond ESGs

Naming the Dominant Logic and Making Sense of the Real Governance Metrics 

Welcome to a set of unfolding presumptions about how we transition to a survivable social, environmental, and political climate. This is a second in a series of explorations about how we might think about investments that connect across public and private sectors and the spaces in between called Contribution Value Design (the first post is here, and the first example of a new type of multi-perspective investment brief).

We value community agency and resilience locally but struggle with finding investments that meaningfully move the needle globally. 

So we search for investments that can scale. 

There are massive barriers to complex systems change, but the crucial problem is that we know how to scale market solutions, but seem to be stuck with markets-solve-everything delusions. 

Most of our complex problems are already embedded in systems that combine private, public, and third sectors, together. We can’t just innovate inside of the market to upgrade our infrastructure, refactor our supply chains, and transition our healthcare, housing, education, and energy systems to work better for us. We need to admit we’re great at creating new technology in new spaces, but not so great at shifting legacy industries.

All eyes rest on the evaluation metrics as the core leverage point to change how we move a company or industry or society from one horizon to the next. 

Thousand of finance folks worked on all of the standards that led to the alphabet soup of investment metrics: TCFD, PRI, GRI, SASB, IFRS, ISSB, and SDR, all rolled up into an umbrella term that has not quite succeeded: ESG or environmental social and governance. The theory of change works something like this:

Yet what’s happened along the way is that the alphabet soup has confused everyone. The people and perspectives needed to develop rigorous whole-planet sustainability frameworks have not yet risen to the top of these financial industry convenings. Critically, the business model of the financial industry has not changed to respond to the growing end-customer demand for it to change. 

A business model is a conceptual idea for how activities and resources are organized around the core relationships of a firm, centered around the value created for customers. In complex networked industries, business models can connect across companies and sectors to generate value for the larger sector or ecosystem. 

While I’d like to see the industry adopt the approach of contribution value design which recognizes multiple stakeholders, we need to get to name the dominant logic that currently governs the current shareholder-centric model. 

The finance industry is trying to change nothing about itself but instead dictate how the companies it invests in change. 

Indeed, business model change is difficult in legacy industries. 

As the late father of disruption theory Clayton Christensen reminded us:

Why? Because dominant logic gets in our way. 

Dominant logic is the disease that killed Kodak, Blockbuster, and Nokia, and it threatens every successful large-scale company facing disruption—which is all of them. The danger isn’t so much the disruption itself, a product of fierce new competition and shifts in the technology landscape; it’s the faulty mindset that hampers senior management when it’s preparing for and responding to non-linear change.

“Dominant logic consists of the mental maps developed through experience in the core business and sometimes applied inappropriately in other businesses,” according to C.K. Prahalad. 
Prahalad was researching the failure of diversified conglomerates when he found that a top executive group’s ability to manage is limited by the dominant general-management logic they’ve already learned and practiced. Senior leaders, particularly if they are not organized with alternate perspectives and diverse contributors, are sometimes subconsciously unaware of how they make decisions. When the management mindset favors the core business at the expense of preparing for technological, market, and social/cultural change, its dominant logic can undermine the company’s chances for survival.

Jump forward to 2022 and it seems like we’re struggling with dominant logic when we try to imagine how we’ll transition our legacy sectors, starting with the finance sector. That’s why, before we try to develop a new way of thinking about value, we need to name the dominant logic that has geared our legacy sectors. These logics also tend to operate as invisible forces, blocking us from even imagining a different path forward.

One quick way to surface dominant logic is to discover the core metric that truly drives governance in companies and sectors. 

Older industrial-era companies and organizations also tend to be structured around one key metric, though these metrics are typically for the whole sector and not all employees are aware that the metric drives many decisions around budgeting, incentives, salaries, and strategic planning. Some of these metrics are reported to investors, and others are whispered in hushed tones during management meetings:

  • Retail companies like Walmart and Target: month-over-month same-store sales
  • Hospitals: hospital census (or colloquially, # of heads in beds per year)
  • Auto companies: number of vehicles sold vs. market share
  • Oil and Gas Companies: reserves and production volume
  • Semiconductors: book-to-bill ratio
  • Consumer Packaged Goods companies: sales volume vs. market share
  • Pharmaceutical companies: “script lift” – the # of prescriptions written by doctors 
  • Banking: Net interest margin (NIM), a bank’s net profit on interest-earning assets
  • Large financial institutions: Assets Under Management. 

Newer digital-first companies came across the concept of the North Star Metric. The North Star Metric is a startup practice that reveals the way most companies arrange themselves around one core number to gauge their success. Coined by Sean Ellis who calls himself the father of growth hacking, the North Star Metric allows teams to focus on one common goal in startup mode to avoid distractions and reduce documentation. 

  • Spotify: Time spent listening
  • Amazon: Number of purchases per month
  • Airbnb: Booked nights
  • LinkedIn: Monthly Active Users
  • Netflix: Watch time
  • Meta: Monthly Active Users for the family of apps
  • Uber: Rides per week

If we compare tech-driven companies to industrial-era companies you’ll notice that the North Star Metrics for tech describe customer experience metrics, while the industrial-era companies describe organization-centric metrics. 

But the North Star Metric concept co-opted the idea of the North Star serving as an ethical compass or orientation to achieve a purposeful vision. None of these companies will help us to survive or thrive in the coming transitions if they get the most booked nights, the most monthly active users, or the most time listening.

What do WE value?

To move beyond the company-centered metrics of the industrial era, and the user experience-centered metrics of the Internet era, we need to reexamine what it is that we collectively value. This doesn’t mean adding to yet another acronym of standards adding to the alphabet soup ESG. 

As a financial modeler, a scientist, an engineer, or a policy maker, we really do not understand all of the science, technology, history, and perspectives that we need to make decisions. Not everyone is an expert in statistics, epidemiology curves, or climate scenarios. Not everyone knows all of the histories of indigenous tribes, rural families, or front-line communities that have already experienced the consequences of prior investments. 

But humans are wise observers of our words and our commitments to each other in our lived experiences. We all make decisions from this context. Contribution value modeling asks key participants in new investments to share their perspectives about what they see in the future, and invites them not just to learn, vote, or decide, but to commit their own contribution, and design that future.

And before we can start convening in circles of community-engaged understanding, we need to name the structures and scaffolding that organize and operate our experiences today. We need to identify the dominant logic and key metrics that govern how current company, organization, and industry metrics that will continue to define investment decisions for what comes next. 

Then what? Stay tuned for more on this series – sign up to get the first read on Contribution Model Design. If you have a dominant logic metric to suggest, or you work in a company or industry I mentioned above and you want to share your perspective on the real metric that governs those spaces, please reach out, I’m eager to hear from you.

  1. The Dominant Logic: A New Linkage between Diversity and Performance, C. K. Prahalad and Richard A. Bettis, Strategic Management Journal, Vol. 7, No. 6 (Nov. – Dec., 1986

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