On Being Decision-Centric

When you hear an organization say that they are setting out to be more “something”-centric, it’s usually a veiled admission that they weren’t emphasizing it enough.

Announcing that you are now “something”-centric is a way to drive a shift, or focus, to “something”, tipping the balance in trade-off choices made across the organization.

It’s natural that at different points of an ecocycle an organization would want to emphasize different things. It’s even more interesting when companies across a whole industry shift together, opening the floodgates for consultants to step in with guidance on how to do it.

The last few decades in tech, we have seen this in waves:

• We became quality-centric to shift the focus to “doing it right the first time”.
• We became cost-conscious (i.e. cost-centric) to ride through a downturn.
• We became commitment-centric to drive accountability and get more goal-oriented.
• Which naturally led to becoming data-centric to improve those goals.
• Until the wrong kinds of goals emerged, so we became outcome-oriented (i.e. outcome-centric).
• And then we sensed we were too reliant on systems (and the pandemic hit), so we became relationship-centric.
• But those internal relationships baked in an “inside-view”, so we became customer-centric.

And now, we get overwhelmed by the complexity of all this, and dream of cutting to chase by being more decision-centric.

It’s an area that has not seen much emphasis over the last couple decades. So is it a good time to give decision making a moment in the spotlight, to cut through the complexity?

What does putting decisions in the center mean, anyway?

We like to say that decisions “punctuate the flow of information across an organization”. So it follows that if you are not decision-centric, days at work will feel like a long run-on sentence.

Yep, that hits.

But there are different kinds of decisions, and it’s important to not lump them all together for this discussion. This chart does a nice job of highlighting some differences.

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In some organizations, high-quality decisions are essentially part of “the product”, or at least a source of differentiated value. Classic examples are fraud detection for credit card companies, or claims processing for insurance companies. These are low impact (individually), but high volume, and thus can significantly drive revenue.

At the other end, high-stakes decisions consuming the attention of the C-suite are low volume and high impact. The approach taken for these (i.e. from a decision architecture) should reflect that significance.

In between, we find the bulk of decisions that keep the organization moving. Moderate volume (e.g. several per month) and moderate economic impact decisions (e.g. high-stakes for the unit or group, but not moving the needle a lot for the company as a whole) are everywhere, appearing all the time.

Decision-centricity for high-volume decisions leads to rules and automation, to reduce the noise.

In the C-suite, well, they don’t need to be told what to do, and decision-centricity is in their DNA.

For that middle-ground, though, a message of decision-centricity can drive an organization-wide pursuit of higher-quality decision-making, and cast a wider net for change.

What would this look like?

Decisions are choices:

• Choices about strategic movement or what changes to pursue
• Choices about how to interpret or make sense of the external environment
• Choices about whether an observation (or evaluation) has yielded an insight

When we emphasize “deciding how to decide” (i.e. build a decision architecture), it can bring decisions out of the background and into to the foreground, in all of our:

• Conversations
• Agendas
• Plans
• Communications
• Reviews
• One-on-ones (mentoring on decision-making, and status discussions)

Putting decisions (choices) back in the foreground grants permission to leaders to monitor the impact of the decisions, as they boldly move the organization away from the status quo into the unknowable future.

Decision-centricity should lead to a more open acknowledgment of uncertainty. New behaviors that navigate the uncertainty, replace behaviors that used to pretend it doesn’t exist (or pretend that we are powerful enough to suppress its impact).

When we emphasize decision-centricity, we start to ask questions like:

• What decisions are looming?
• What bold decisions have we recently made?
• What are our hedged decisions?
• Have the circumstances changed since these decisions were made?
• Would we make this decision again today, given what we know now?
• Was it a good decision, or did we just get lucky?
• Where are we maintaining the status quo? (a decision in itself, so treat it as such…)
• Where are our decentralized decisions aligned? Misaligned?
• Where have past decisions shaped existing behaviors in our organization (i.e. the system)?
• Where are decisions shaping new behaviors in our individuals, teams, departments?
• Which investments (i.e. past decisions) have the most risk due to uncertainty? What decisions can we make to mitigate that risk?
• Are we suffering from decision fatigue from high cognitive loads and poor collaboration/ support/ architecture around decisions?
• Are we clear (in the decision architecture) on when a decision-to-make is worthy of documenting? Of when it is worthy of collaboration and dialog?
• Do we teach decision-making skills (e.g. good judgment)?
• Do we assess decision making performance?
• Do we treat decision making as a business capability? Do we measure its performance with KPIs?
• Do we drive strategic investments in improvements in organizational decision making?

Decision-centric means we start with decisions - we put it in the center. Contrast this with a data-centric mindset that starts with the data at hand.

When we thoroughly understand where we are today, and where we need to go, we see that all work is sparked by (1) a choice of movement from the current position, and (2) a choice of tactics to drive the movement.

In a large organization, being decision-centric means finding the sweet spot that yields decentralized decision making and strategic alignment. An organization that fails to decentralize will grow rigid and stagnant. On the other hand, a completely decentralized, “do-what-you-want”, “create your own projects” environment will rarely be aligned enough to be effective or efficient.

Being decision-centric also means that you “see” decisions, both explicit and implicit, across the organization. Capturing explicit decisions involves directly recording a decision that has been consciously and intentionally made (e.g. the high-stakes strategic choices we talked about earlier). On the other hand, implicit decision capture involves deducing decisions that have been indirectly made and are not formally documented as such.

Examples include:

• Approving a budget
• Setting a roadmap
• Green-lighting headcount increases

These actions implicitly signal strategic choices about resource allocation, priorities, and organizational structure, but often are not expressed as “decisions”.A decision-centric organization recognizes these as decisions, and looks to relate them to other decisions.

What about AI?

A decision-centric organization can use the lens of decision-making to explore how to leverage new AI technologies.

If a decision is composed of a prediction, followed by a judgment, then AI will transform our ability to predict, yet leave the judgment to humans, either via rules or case-by-case assessment.

How well does your organization understand this idea of decisions as a combination of prediction and judgment?

Decision-centric organizations will likely have a head start on this evolution.

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