What managers actually do

AQA gives you five verbs. Learn them — they structure almost any "role of the manager" answer:

• Setting objectives — turning the mission into SMART targets for the team.
• Analysing — gathering and interpreting data on the market, the operation, the competition.
• Leading — motivating and directing people to deliver those objectives.
• Making decisions — committing resources under conditions of imperfect information.
• Reviewing — comparing outcome with target, and feeding that back into the next round.

Management vs leadership: a useful distinction — management is about systems, control and doing things right; leadership is about direction, vision and doing the right things. Most real managers must do both, and the balance shifts with the situation.

The Tannenbaum & Schmidt continuum

Leadership is not a binary. Tannenbaum and Schmidt place styles on a continuum from boss-centred to subordinate-centred, according to how much authority the manager keeps and how much freedom the team is given.

The Blake Mouton grid plots the same problem on two axes instead — concern for production against concern for people — giving country-club, impoverished, produce-or-perish, middle-of-the-road and, ideally, team management (high on both).

Which style, and when?

What determines the style — and does it work?

Influences on a manager's style:

• The manager — personality, experience, and their assumptions about people (McGregor's Theory X: people dislike work and must be controlled → autocratic; Theory Y: people seek responsibility → democratic).
• The subordinates — skill, experience and willingness to take responsibility. You cannot delegate to a team that is not ready for it.
• The situation — time pressure, risk, the nature of the task, the organisational culture.

Effectiveness is judged against outcomes: productivity, labour turnover, absenteeism, quality, engagement scores, and — ultimately — whether objectives were met.

Evaluation: resist "democratic is best". Democratic leadership raises motivation and the quality of decisions where staff have relevant expertise, but it is slow, can produce weak compromises, and is dangerous in a crisis. Autocratic leadership is fast and decisive but corrodes motivation, wastes the team's knowledge, and creates dependency. The best leaders move along the continuum.

Scientific vs intuitive decision making

Scientific decision making means basing the decision on data — set the objective, gather data, analyse options, decide, implement, review. Intuition means relying on hunch, experience and judgement.

Scientific methods produce decisions that can be justified, defended and reviewed — but they cost time and money, they are only as good as the data behind them, and they can be paralysingly slow when a market moves fast. Intuition is fast and cheap and is sometimes all you have (a genuinely new product has no historic data), but it is prone to bias and cannot be audited.

Four concepts to define precisely:

• Risk — the possible outcomes are known and can be assigned probabilities.
• Uncertainty — outcomes cannot be assigned meaningful probabilities (a pandemic, a war, a disruptive technology).
• Reward — the payoff that justifies bearing the risk.
• Opportunity cost — the benefit of the next-best option you gave up. Every "yes" is also a "no".

Match each decision-making concept to its precise meaning

Tap an item on the left, then its partner on the right.

Decision trees

A decision tree is a diagram that forces you to price the uncertainty.

• Square = a decision node — a choice the business controls.
• Circle = a chance node — outcomes the business does not control. The probabilities on the branches leaving a chance node must sum to 1.
• Costs of each option are written on the branch; payoffs at the far right.

You work right to left ("rolling back"): calculate the expected value at each chance node, subtract the cost of the branch leading to it to get the net gain, then at the decision node choose the branch with the highest net gain.

Your turn — expected value

Your turn — net gain

Roll back the tree

Your turn — sensitivity

The value — and the limits — of decision trees

Strengths: they force managers to quantify risk rather than argue about it; they set out all options and their costs side by side; they take account of the probability of failure, not just the size of the prize; and they make the reasoning visible so it can be challenged and reviewed.

Limitations — and this is where the marks are:

• The probabilities are estimates. As question 3 just showed, moving B's success probability from 0.6 to 0.8 nearly doubled its net gain and reversed the decision. A tree is only as good as its weakest guess.
• They ignore qualitative factors — brand damage, staff morale, ethics, the reaction of competitors.
• They assume the payoffs are known and that the manager is risk-neutral. A firm close to insolvency may rationally reject the higher-EV option because the downside would kill it.
• They are static — drawn at a point in time in a market that keeps moving.
• Managers can (consciously or not) set the probabilities to justify the decision they already wanted.

The A-level judgement: a decision tree is a decision aid, not a decision maker. Use it to structure the argument, then temper it with experience, ethics and an honest look at how sensitive the answer is to the assumptions.

What the tree cannot see

Influences on decision making

No decision is taken in a vacuum. AQA's list:

• Mission — a business built on ethical sourcing cannot simply switch to the cheapest supplier, however good the numbers look.
• Objectives — a firm chasing growth and a firm chasing survival will read the same data and decide differently.
• Ethics — the gap between what is legal and what is right. Ethical choices frequently reduce short-run profit and protect long-run value.
• The external environment, including competition — a rival's likely response changes the payoff of your move.
• Resource constraints — finance, capacity, skills and time. The best decision you cannot fund is not a decision at all.

Stakeholders and stakeholder mapping

A stakeholder is any individual or group affected by, or able to affect, the business: shareholders, employees, customers, suppliers, lenders, government, the local community, pressure groups.

Their needs overlap more often than students admit — everyone benefits from a business that survives and grows. But they also conflict: a wage rise pleases employees and cuts the dividend; automation raises productivity and destroys jobs; a price cut delights customers and squeezes suppliers.

Stakeholder mapping plots each group on two axes — power (can they force the business to act?) and interest (how much do they care?) — and prescribes a strategy for each quadrant:

• High power, high interest → manage closely. Consult, involve, keep on side.
• High power, low interest → keep satisfied. Do not provoke them into engaging.
• Low power, high interest → keep informed. Communicate; they can become vocal.
• Low power, low interest → monitor with minimal effort.

Stakeholder mapping

Tap a stakeholder, then tap the quadrant they belong in.

Managing stakeholder relationships

The two tools AQA names are communication and consultation. Done well they build trust, surface problems early, and buy consent for hard decisions. Done badly — or only after the decision is made — they are seen as spin and make resistance worse.

Influences on the relationship include the power balance (a supplier with one customer is in a weak position), the firm's culture and mission, the time horizon (long-term partnerships behave differently from one-off transactions) and the regulatory environment.

Shareholder vs stakeholder concept (returns in 3.7.6): the shareholder view says a firm's only duty is to maximise returns to its owners within the law. The stakeholder view says a firm that ignores employees, suppliers, communities and the environment will destroy the very relationships its long-run profits depend on. Most examinable judgements sit somewhere between the two — and the strongest answers say where, and why.

Stakeholder conflict

Thinking like an examiner

• Always compute the net gain, never the raw EV. And always ask how sensitive the answer is — if a 0.1 shift in a probability flips the decision, say so.
• Style is contingent. The examinable claim is never "democratic is best"; it is "given this team, this task and this time pressure, the style should sit here on the continuum — and here is what would move it."
• Stakeholder analysis needs a verdict. Listing who is affected is AO1. Ranking them by power and interest, and saying whose interests must prevail here and why, is AO4.
• Data does not decide. Scientific decision making improves the odds; it does not remove uncertainty, bias, or the need for judgement.

The big ideas to know

Press Finish to see your score.