ACCA APM Exam 1

Report to the board of Kericho Ridge Tea Co — performance measures, divisional appraisal and reward

Introduction: this report derives critical success factors (CSFs) and key performance indicators (KPIs) from the mission, evaluates how the two divisions and their managers should be appraised, and assesses the finance director's proposed reward scheme.

1 CSFs and KPIs

The mission promises the finest Kenyan tea and fair treatment of workers, yet the board pack measures only volume, cost per kilogram and ROI. The operations director's view that full factories mean a healthy business is doubtful: volume can rise through coarse plucking while the value per kilogram falls, so volume is a misleading guide to success against Objective 2.

Objective 2 — CSF: consistently fine-plucked, high-grade leaf. International buyers judge Kericho Ridge on the quality of every lot, so leaf quality is what the company must get right. KPI: average auction price premium per kilogram compared with the Mombasa auction average for the same grade, reported monthly. This is justified because it measures quality the way the buyers themselves value it, it is SMART (a measurable premium tracked over time), and it removes the effect of general price falls such as the 9% drop this year. The data is practical to collect from the auction catalogue prices and broker valuation Kericho Ridge already receives for every lot. A supporting KPI is the percentage of leaf meeting the fine plucking standard at factory intake.

Objective 3 — CSF: retaining a skilled, safe workforce. Being the employer of choice depends on keeping experienced pluckers, whose skill also drives fine plucking. KPI: labour turnover, the percentage of pluckers leaving within their first season, against the current 22%, reported each season by garden. It is justified because high staff turnover is direct evidence that Kericho Ridge is not yet the employer of choice and it raises training costs. A second KPI, the lost-time injury rate per 100000 hours worked, would measure safe work.

📋 Objective: 1.2 (Performance hierarchy (A2))

2 Divisional and managerial performance (KES m)

Workings — manager basis (controllable profit on controllable net assets, as the manager cannot influence head office machinery or apportioned costs):

Estates: ROI = 1260 ÷ 7000 = 18%; RI = 1260 − 12% × 7000 = 1260 − 840 = 420.

Specialty Teas: ROI = 600 ÷ 2500 = 24%; RI = 600 − 12% × 2500 = 600 − 300 = 300.

Workings — division basis (traceable profit after head office depreciation, before apportioned head office costs, on total divisional net assets):

Estates: traceable profit 1260 − 360 = 900; net assets 7000 + 2000 = 9000; ROI = 900 ÷ 9000 = 10%; RI = 900 − 12% × 9000 = 900 − 1080 = −180.

Specialty Teas: traceable profit 600 − 90 = 510; net assets 2500 + 500 = 3000; ROI = 510 ÷ 3000 = 17%; RI = 510 − 360 = 150.

Evaluation of the non-executive director's view. The annual report ROI of 8% includes apportioned head office costs, which are not caused by either division, so it is a poor basis for any judgement. Separating managerial performance from divisional performance gives a different picture. The Estates manager earns 18% on the assets she controls and the highest RI of 420, so she adds more value above the cost of capital than the Specialty Teas manager (RI 300); ROI favours the smaller division. Replacing her would be unjustified. The negative divisional RI of 180 is caused mainly by head office machinery, a head office decision.

The figures should also be treated with caution. Estates suffered a dry spell and a 9% auction price fall, both uncontrollable, so this year's results understate the manager's performance. Conversely, Estates' old, heavily depreciated assets flatter its ROI on net book value, while Specialty's recent packing lines depress its ROI, so neither ROI is fully comparable.

Cold-brew investment. Project ROI = 240 ÷ 1500 = 16%, above the 12% cost of capital, so it adds value: project RI = 240 − 180 = 60. But it would cut the manager's ROI from 24% to 840 ÷ 4000 = 21%, which explains the rejection. Her RI would rise to 840 − 12% × 4000 = 360. Appraising on ROI has caused a lack of goal congruence: a decision good for shareholders (Objective 1) was rejected to protect a percentage. The project should not have been rejected, and managers should be appraised on RI, which encourages every investment earning above the cost of capital.

📋 Objective: 1.3 (Financial performance measurement (A3))

3 Assessment of the proposed reward scheme

Fitzgerald and Moon's building blocks say rewards should have clarity, should motivate, and should be based on controllable measures.

Divisional managers — clarity. The ROI formula and threshold are easy to state, so the scheme is clear in form. However, managers cannot see how head office apportionment is set, so they will not understand how much of the measure they can move.

Divisional managers — controllability. ROI after all charges includes head office machinery depreciation, head office net assets and apportioned head office costs. These are outside the managers' control, so the scheme breaks the controllability principle. Estates' result is also driven by rainfall and Mombasa auction prices.

Divisional managers — motivation. On this year's results, Estates' ROI of 8% earns no bonus, while Specialty's 15% earns (15 − 10) × 2% = 10% of salary. The Estates manager, who produced the higher RI, receives nothing, which is inequitable and likely to demotivate her. ROI-based bonuses would also reinforce the rejection of value-adding projects such as cold-brew.

Field supervisors. The kilogram bonus is very clear and largely controllable through team management, and it may motivate effort. But what gets measured gets done: supervisors will push pluckers towards coarse plucking to add weight, which lowers auction value and damages Objective 2. One target for every garden ignores altitude and rainfall, so targets fail the achievability and equity standards; supervisors on dry, low gardens will give up. The scheme also gives pluckers a reason to work unsafe hours, against Objective 3.

The finance director's claim that the scheme is simple, fair and focused on profit is therefore only partly true: it is simple, but not fair, and focuses on volume rather than value.

Recommendations. Base managers' bonuses on RI of controllable profit on controllable net assets, adjusted for rainfall and auction price movements. Pay supervisors on value per kilogram, combining kilograms with the share of leaf meeting the fine-plucking standard, with targets set for each garden with the supervisors.

Conclusion: Kericho Ridge should add quality and workforce KPIs to the board pack, judge managers on controllable RI rather than ROI after all charges, support the cold-brew investment, and redesign the reward scheme as above before any bonuses for 20X8 are committed.

📋 Objective: 2.2 (Performance and reward (B2))

Taking each objective in turn, the report gives the board little of what it needs.

Objective 1 — portfolio quality. The report contains nothing on overdue loans. Using Exhibit 3, portfolio at risk over 30 days was 1440 ÷ 36000 = 4% in 20X6 but 5280 ÷ 48000 = 11% in 20X7, more than double the 5% target, while overdue loans rose by 267%. This is the most important risk to depositors and funders and it is hidden from the board.

Objective 2 — reaching women. Women fell from 78% to 64% of active borrowers, below the 75% target. Average loan size rose from 54000000 ÷ 30000 = GHS 1800 to 75600000 ÷ 36000 = GHS 2100, which suggests lending is drifting towards larger, male or urban borrowers. Neither fact is reported, so the claim of delivering the mission cannot be tested.

Objective 3 — self-sufficiency. There is no information on income against operating and financing costs, so the board cannot see whether growth is profitable; rising arrears suggest loan loss provisions will reduce income.

Narrative. The headline is a misleading narrative: disbursement growth measures activity, not mission, and rapid growth with rising arrears is a warning sign rather than a record year. The comparison with the weakest month of last year is selective and flatters the trend.

Presentation. A 46-page report with monthly branch tables to the pesewa causes information overload; the training course list is irrelevant to board users. The three-dimensional pie chart distorts the size of the slices and makes 18 branches impossible to compare; a simple ranked bar chart would be clearer. Figures should be rounded to GHS 000.

Timeliness. Issuing the report ten weeks after the year end is too late for the board to act on rising arrears.

Overall, the report does not meet the board's needs: it celebrates volume while the indicators linked to the mission are deteriorating.

📋 Objective: 3.1 (Management reports (C1))

Comparability. A commercial bank's microloan unit in Accra serves mainly urban, salaried or larger business clients with individual loans, and pursues profit only. Ho Valley serves rural women through group lending with a social mission, so its costs per loan and loan sizes will naturally differ. Comparing them may lead to the wrong conclusions, such as pressure to raise loan sizes, which would further harm Objective 2.

Data availability and reliability. In competitive benchmarking the partner will not share detailed process data; the bank's annual report gives only summary figures, which may combine the microloan unit with other lending and use different definitions of overdue loans. The association's table is based on self-reported, unaudited figures, which members may present in their best light, so its reliability is doubtful.

Copying rather than innovating. The chief executive's aim of finding "what we must copy" is questionable: benchmarking only shows what others do now, so it encourages catching up rather than innovation, and practices that work for a bank may not suit village groups.

Focus and complacency. Managers may concentrate on the benchmarked areas and neglect others, and if Ho Valley compares well against a weak table it may become complacent despite its 11% portfolio at risk.

Cost and staff reaction. Collecting and adjusting the data takes management time for a small organisation, and branch staff may see unfavourable comparisons as a threat, leading to resistance.

📋 Objective: 1.1 (Strategic management accounting (A1))

Lost or stolen devices. The stolen laptop shows that client data leaves the office on unprotected devices. A bank client's real customer data has probably been exposed, which may breach the client's data protection obligations under the EU's General Data Protection Regulation and Tunisian law, and could cost Medina Code the contract. Controls: full-disk encryption of every laptop, remote wipe, and a rule that test environments use anonymised or masked data, never real customer records.

Unauthorised access. 37 accounts of leavers are still active, and every developer can see every client's code. A former employee could steal code or data, and one compromised account exposes all clients. Controls: a leavers process linked to HR that disables access on the last day, role-based access controls on a need-to-know basis per client project, multi-factor authentication, and quarterly access reviews.

Phishing and malware. Finance staff clicking fake supplier links shows vulnerability to phishing, which can install ransomware or lead to payment fraud. Home connections are less secure than the office network. Controls: staff awareness training with simulated phishing tests, email filtering, a virtual private network for remote working, and firewalls and up-to-date anti-malware software on every laptop.

Loss of data and continuity. Weekly backups held with the same provider mean up to a week's work could be lost, and a provider outage or ransomware attack could affect both live data and backups. Controls: daily backups held with a separate provider or offline, and a tested disaster recovery plan.

The chief technology officer's view. The claim that security is entirely the provider's job is wrong. Cloud security is a shared responsibility: the provider secures its infrastructure, but Medina Code remains responsible for who has access, how data is configured and what staff do.

Because Medina Code competes on quality and reliability for European banks, strong security is a source of competitive advantage: it should seek independent certification, such as ISO 27001, which clients increasingly ask for in tenders.

📋 Objective: 4.1 (Technology and information systems (D1))

The problem. 228 ÷ 600 = 38% of fixed-price projects overran by more than 10%, and overruns have cut the operating margin from 18% to 11%. Estimating by individual judgement is inconsistent and cannot learn systematically from past results.

How machine learning could help. Medina Code already holds four years of structured history: estimated and actual hours, team size, languages, client sector, change requests and defects. A machine learning model trained on this data could find patterns that humans miss, such as which combinations of sector and language overrun, and give predictive analytics: an expected effort range and a probability of overrun for each new bid. This supports better pricing of fixed-price bids, earlier warnings during projects, and a learning loop, because each completed project becomes new training data that refines the model. Defect data could also be used to predict which modules need more testing, supporting quality, Medina Code's chosen basis of competition.

Generative AI coding assistant. It could raise developer productivity, for example by drafting routine code and test cases, reducing hours per project and improving margins.

Risks and limitations.

• Data quality: past estimates may have been recorded inconsistently, and 600 projects is a small data set, so data cleansing is needed and outputs will be uncertain.
• Bias: the model learns from past behaviour, including over-optimistic estimates and old technologies, so it may repeat past errors.
• Explainability: a black box model is hard to explain to clients or to challenge; senior developers should review its output rather than accept it.
• Confidentiality: an assistant hosted outside the company may receive client source code, breaching client contracts and data security, given the incidents in Exhibit 1; Medina Code should use a privately hosted tool or block client code from it, and review AI-written code for errors.

The vendor's claim of a 90% cut in estimating errors within three months is unproven marketing; Medina Code should run a pilot, testing the tool on past projects it did not learn from before relying on it.

Advice. Adopt the estimating tool after a successful pilot, and the coding assistant only under strict confidentiality controls.

📋 Objective: 4.2 (Data science and analytics (D2))