APM Advanced Performance Management

A. Strategic management accounting, performance hierarchy and measurement

Strategic management accounting uses information about the external environment, competitors, customers and long-term decisions, as well as internal information, to help the organisation to set, monitor and achieve its strategic goals and create value. It differs from traditional management accounting by looking outward and forward, and by combining financial and non-financial information. Sustainability affects the setting of goals, targets and measures, and external factors such as stakeholders, market conditions, competitors and regulation affect management issues.

The performance hierarchy links the mission, the strategic goals and objectives, the strategies, the critical success factors, and the targets and key performance indicators at each level. Performance measures should be linked to the objectives so that managers act in a way that supports the strategy, and they should be controllable, understandable and timely. Total shareholder return (TSR) and similar measures link performance to shareholder value.

Financial performance measurement. Profitability, liquidity, efficiency and gearing ratios, return on capital employed and residual income are used. Economic value added (EVA) is net operating profit after tax less a charge for the capital employed at the cost of capital, and market value added compares the market value of the business with the capital invested. They link performance to the creation of shareholder value, but depend on the adjustments and the estimate of the cost of capital. Financial measures are historical, can be manipulated, may encourage short-termism and ignore non-financial factors.

Non-financial performance measurement. Frameworks include the balanced scorecard (financial, customer, internal business process, and innovation and learning perspectives), the Building Block model (dimensions, standards and rewards), the performance pyramid and the performance prism, which looks at stakeholders. For service businesses and not-for-profit organisations, measures such as quality, customer satisfaction, value for money and outcomes are important. The costs of quality (prevention, appraisal, internal failure and external failure) help to link quality to cost. Sustainability measures cover emissions, energy, waste, social impact and governance, and the challenge is to measure them reliably and to link them to value.

Worked figures

EVA: net operating profit after tax is $12,000,000, capital employed is $80,000,000 and the cost of capital is 9 percent. The capital charge is $7,200,000 and EVA is 12,000,000 - 7,200,000 = $4,800,000.

Key terms

• Economic value added: Net operating profit after tax less a charge for capital at the cost of capital.
• Performance hierarchy: The cascade from mission and goals down to targets and indicators.
• Short-termism: Putting short-term results ahead of long-term value.

Study tip: State the objective first and then choose measures that link to it. A list of measures without a link scores poorly.

Practice questions for section A

B. Performance optimisation

Budgetary planning and control. Budgeting supports planning, coordination, communication, motivation and control. Approaches include incremental, zero-based, activity-based, rolling and flexible budgets, and the beyond budgeting model, which replaces fixed targets with relative performance and rolling forecasts. Budgets can create problems: slack, gaming, short-termism and demotivation if targets are imposed. The usefulness of a budgetary system depends on the environment: in a stable environment, a detailed budget works well, while in a volatile one, more flexibility is needed.

Performance and reward. Rewards motivate managers when they are linked to controllable performance, are fair, are understandable and are consistent with the goals of the organisation. Reward can be financial (bonuses, profit sharing, share options) or non-financial (recognition, development). Poorly designed schemes can encourage manipulation of results and a focus on a few measures at the expense of others, so a balance between short-term and long-term measures, and between financial and non-financial measures, is needed.

Performance improvement models and techniques. Total quality management aims for continuous improvement and quality at every stage, with the ideas of zero defects and getting it right first time. Lean thinking removes waste and uses just in time, and Six Sigma reduces variation and defects using the DMAIC cycle (define, measure, analyse, improve and control). Kaizen means continuous small improvements, business process re-engineering is a radical redesign of processes, and benchmarking compares performance with the best. Value chain analysis and supply chain management look for improvements across the whole chain, including suppliers and customers. Each has benefits and risks, such as cost, resistance and the danger of focusing on one measure.

Specific contexts. Service organisations are harder to measure because of intangibility, variability and perishability, so they use a mix of measures such as quality and customer satisfaction. Not-for-profit organisations use value for money and outcome measures, and have many stakeholders with different objectives. Divisionalised businesses need measures that are controllable by managers and consistent with group objectives, such as residual income, and consider transfer pricing. In complex supply chains, performance needs to be measured across organisational boundaries, using shared data and agreed measures.

Worked figures

Six Sigma: 45 defects are found in 5,000 units, each with 4 opportunities for a defect. Defects per million opportunities = 45 / (5,000 x 4) x 1,000,000 = 2,250.

Overall equipment effectiveness: availability 90 percent, performance 95 percent and quality 98 percent give 0.90 x 0.95 x 0.98 = 83.8%.

Key terms

• Six Sigma: A method for reducing defects and variation, using the DMAIC cycle.
• Kaizen: A philosophy of continuous incremental improvement.
• Benchmarking: Comparing performance with the best in class to identify improvements.
• Beyond budgeting: A management model that replaces fixed annual budgets with relative targets and rolling forecasts.

Study tip: For improvement techniques, always give a benefit, a risk and the conditions in which the technique works best.

Practice questions for section B

C. Performance reporting

Management reports should be designed to support the decisions of the people who use them and so that they match the organisation's goals. A report is useful if it is relevant, accurate enough for its purpose, timely, understandable, and cost-effective, and presented in a suitable format. It should show a clear link between the measures and the objectives, and give a comparison with targets, benchmarks and trends.

Evaluating a reporting system covers what the information is used for, the quality and sources of the data, the frequency and timing of reports, the level of detail, the balance between financial and non-financial measures, internal and external information, and whether managers can control the items they are measured on. The system should avoid information overload and give early warning (leading indicators) as well as results (lagging indicators).

Reports can be improved by using dashboards that show key indicators with clear visuals, exception reporting that highlights deviations beyond a set limit, variance analysis with explanations and actions, drill-down capability, and forward-looking information such as forecasts and scenarios. Integrated reports should link performance to strategy and to the creation of value for stakeholders. Reports must also consider confidentiality, security and the ethical use of data.

Key terms

• Dashboard: A visual summary of the key performance indicators for a user.
• Exception reporting: Reporting only the items that deviate from the plan beyond a set limit.
• Leading indicator: An indicator that gives early warning of future performance.

Study tip: When criticising a report, say who uses it, what decision it supports and how it fails them.

Practice questions for section C

D. Data science, analytics and technology

Technology and information systems. Systems used for performance management include enterprise resource planning systems, business intelligence tools, data warehouses and dashboards, and cloud-based platforms. They can integrate data across functions, give real-time information and reduce manual effort. Systems need to be selected to fit the needs, with attention to cost, integration, data quality, security and user adoption. Developments such as the internet of things, blockchain, automation and artificial intelligence affect how information is captured and used.

Data science and analytics. Data analytics is used to describe what has happened (descriptive), to understand why (diagnostic), to forecast what will happen (predictive) and to recommend what to do (prescriptive). Techniques include regression and time series, clustering, classification, text analysis and machine learning. Applications in performance management are customer analytics, forecasting demand, spotting fraud and anomalies, cost modelling and supply chain optimisation. The value depends on the quality of the data, on skills, and on whether the results are acted on.

Risks and limits. Data science brings issues of privacy and data protection, bias in data and models, lack of transparency in complex models, security, the cost of data and skills, and the danger of finding relationships that are only coincidence. Governance should cover data ownership and quality, model validation, ethical use and accountability. Management accountants should interpret the output critically and communicate it clearly to decision makers.

Key terms

• Predictive analytics: The use of data and models to forecast what is likely to happen.
• Data warehouse: A central store of integrated data used for analysis and reporting.
• Algorithmic bias: Systematic error in a model's output that comes from biased data or design.

Study tip: Whenever you recommend analytics, state the data needed, the decision it supports and the main risk.

Practice questions for section D

E. Professional skills in APM

APM examines four professional skills across the case study and the other questions: communication, analysis and evaluation, scepticism and commercial acumen. Ten of the 50 marks in Section A are for professional skills, and five of the 25 marks in each Section B question. Communication needs a clear structure and a suitable format, such as a report to the board. Analysis and evaluation means using the information to reach a justified conclusion and weighing alternatives. Scepticism means questioning the reliability and completeness of the information and the assumptions behind it. Commercial acumen means showing an understanding of the business, its sector, its stakeholders and the practical consequences of a recommendation.

Practise by taking each requirement and asking what the examiner is looking for: technical points from the syllabus, applied to the facts of the case, and the professional skill that is named. State your recommendation clearly, with limits and next steps.

Key terms

• Professional scepticism: A questioning mind and critical assessment of information.
• Commercial acumen: An understanding of the business, its context and the practical effect of decisions.

Study tip: Give one clear recommendation with reasons. Do not leave the examiner to choose between options.