Life is not a game.

People enter a game voluntarily to navigate unnecessary obstacles to earn rewards.

To be born into this world is not a conscious decision and we perform activities essential for us to provide food, water, clothes and shelter.

As a result, our actions are focused on producing immediate rewards using our environment to maximise return irrespective of the broader consequences.  

A why does not feature.

Self-serving behaviour, short-sightedness and instant gratification prevail to secure our own survival.

This course of action is more than understandable in light of different circumstances.

Yet, the accumulative effect of this type of behaviour creates a downward spiral causing widespread destruction with disastrous consequences for the environment at large.

Life is not a game and it is certainly not enjoyable this way.   

Considering this scenario, organisations must re-engineer their reward structure to optimise not only individual performance but also overall performance.

To reinforce or reward actions that serve the broader environment.

In simple terms, without knowing anything, we must be encouraged to do the right thing, no matter what the situation, to not only benefit ourselves but also the organisation and environment at large.

Organisations must construct an ‘Optimal Reward Function’ to give themselves a better chance to survive any operating environment without having to compromise on its core set of values, principles or purpose.

An organisation’s unique culture, or set of behaviours, is maintained throughout different episodes to potentially even secure longevity.

An Optimal Reward Function also eliminates the need for ‘Quartiling’ to compare performances within groups to calculate the appropriate level of compensation.

So let’s develop an Optimal Reward Function.

Using psychologist Kurt Lewin’s equation for behaviour as follows:

B = f (P, E)

Where, Behaviour (B) is a function of Person (P) and their Environment (E).

An Optimal Reward Function can be re-written as:

R = f (P, B, O, E)

Where, Reward is a function of Person, Behaviour, Objectives and Environment with a cumulative grade point average representing the total of the different award values.

This dynamic approach to the optimisation of performance rewards acknowledges that multiple, different and competing forces drive our performance.

The whole situation must be considered.

  • The Person (P) refers to an individual’s character, abilities and knowledge to perform certain activities, functions or jobs
  • Behaviour (B) covers to the different types of interactions ranging from exchange, competition, conflict, co-operation and accommodation
  • Objectives (O) highlights the complexity of agenda, goals or mission
  • Environment (E) sums up the operating climate

A Talent Pool (click here) must encode these four elements into its framework to not only reward what has been achieved but also how this was accomplished and in what circumstances.

Let’s take a closer look at some of the four pillars.

To start off, the Person (P) represents the base layer of the reward function with character, ability and knowledge representing its primary variables.

To determine the appropriate level of reward for a person, test scenarios determine someone’s character, their qualifications typically highlight their abilities whereas knowledge refers to their experiences.

It is worthwhile to note that Person and Behaviour are separate pillars within the reward function because a person’s behaviour can partly be in response to other forces, dynamics or circumstances.

A person can also, in extreme cases, still be of value to an organisation irrespective of their behaviour because his or her skill set is difficult to find in the market place.

Organisations must therefore take responsibility to reward behaviour separately in line with their values, principles and purpose.

For example, a challenging environment cannot give anyone the right or ticket to behave out of step with an organisation’s ethos.


Besides the Person (P) pillar, Behaviour (B), Objectives (O) and Environment (E) are the other parts of the reward function with each pillar allocated an appropriate weighting to contribute to the Total Reward.

The Behaviour (B) pillar focuses on how a person interacts with others within the organisation covering various aspects such as exchange, co-operation, conflict, competition and accommodation.

The following non-exhaustive list provides insight into how an organisation can guide interactions particularly throughout challenging periods:

  • Exchange: (Emotional) support; serves interest of the individual, department, region or organisation; facilitates introductions to expand networks; creates exposure to build a platform for success
  • Co-operation: Actively aligns mutual interests; establishes common ground; incentivises, motivates and channels energies in a productive or constructive manner; pro-actively finds ways to get things done; displays a give and take attitude where appropriate.
  • Conflict: Balances personal interest with group interest to progress the agenda; makes goals compatible between teams; flexible, approachable and willing to go out of their way; shares resources appropriately.
  • Competition: adheres to policy, protocols and other (in)formal work arrangements; keeps calm and collected in adverse conditions; challenges, replicates best practice and evaluates proposals based on merit
  • Accommodate: respects personal space; adheres to appropriate levels of contact; modifies habits to suit new situations; open to new (temporary) ways of working; sets consensus-driven targets     

Behaviour is subject to interpretation, however, an appropriate amount of dual diligence leveraging a diverse set of sources gets us closer to an objective score.

The other two parts of the reward function are the Objectives (O) and Environment (E) pillars. Both deal with the complexity of the agenda.

For example, operating in new, developing or mature markets each represent different challenges.

These factors must be appropriately accounted for to create more of a level playing field across the organisation.

It must be made attractive to start afresh to spark creativity, ingenuity and innovation rather than choosing what suits, is easy or convenient.

The point is that an Optimal Reward Function reinforces new ways of thinking, acting or operating to align personal and group interests to not only allow us to enjoy the fruits of our labour but also to keep pushing boundaries to secure progress overall.

More importantly, a Reward Function eliminates the need for ‘Quartiling’ to compare performances within a group as each person may be running an entirely different obstacle course.

Knowing this, feedback becomes unbiased, collaboration improves and the organisation as a whole moves forward.

There is an entire body of work around ‘Reinforcement Learning’ to design an equation for success irrespective of individual preferences, goals and desires.

An overall score based on a selection of weightings to more accurately recognise, reward and celebrate achievements.

This type of transparency must represent the new direction of travel.

Like life, work is not a game.

But we can make it more rewarding.

If we all ‘play’ responsibly.

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