Second-order thinking: how to assess what happens next

Second-order thinking examines how the consequences of a decision can prompt further responses. When offering free software implementation, for example, a company needs to assess the work new contracts will bring and what happens if the offer attracts customers whose needs differ from those of current customers.

In this hypothetical case, sales wants to remove the charge to close more contracts. The team that configures the product has not yet been consulted. The analysis starts with the promise of more sales and follows the path from selling to support.

First- and second-order thinking in the same decision

The first consequence also needs evidence. If data integration is the main obstacle, removing the price may change only who pays for a difficulty that remains.

Follow people's responses

If the offer works, more implementations may compete for the same team's time. Salespeople might start promising an immediate start, while those doing the work organize a queue. Customers expecting speed might need assistance while they wait.

Each step depends on a condition. The queue grows if additional demand exceeds available capacity. Sales promises change if limits are unclear. Dissatisfaction also depends on the expectations created and communication during the process.

Talk to those receiving the work. Each department's incentives help explain possible responses, but cannot automatically establish how a person will behave. Record what you observed and what you are assuming.

A completed consequence map

Choose one relationship that could change your decision and record it in the decision journal. Define who will watch the sign and when. The queue, for example, needs monitoring while the trial can still be limited; checking revenue only at the end would be too late to control promises.

Compare keeping the implementation charge

Maintaining the price might protect capacity and deter suitable customers. It might also fund a service that distinguishes the offer. Examining only the risks of change favors the current approach without investigating it.

The Government Office for Science systems thinking toolkit presents methods for mapping relationships, examining indirect effects and monitoring interventions.

Stop where the analysis loses support

It is possible to connect a promotion to an endless chain of effects. After several steps, the story may depend more on imagination than available information. Choose a horizon related to the decision and the consequences you can still monitor.

For a commercial trial, it may be enough to observe contracting, implementation and the first period of use. Later consequences remain relevant, but may call for monitoring conditions rather than a detailed prediction now.

Mark each weak relationship with a question. If you assume customers will refer others after implementation, look for evidence of that step. A coherent scenario helps direct an investigation; its coherence does not tell you how likely it is.

Turn the sequence into monitoring

The company could test the offer with a limited group, matching places to team capacity and communicating the start date. Before beginning, it would define who can accept exceptions and which observations would prompt stopping or changing the trial.

Tracking contracts without looking at implementation effort would leave part of the decision invisible. Compare the new customers' profiles, the work consumed and what was postponed. An additional sale may justify that cost; the assessment needs to include it.

Before expanding free implementation, the company needs to know whether additional contracts fit its operations and which customers the offer is attracting. If effort per implementation increases, it can limit places, revise the accepted customer profile or charge again. Discuss those alternatives while there is still capacity to serve customers already admitted.