## **Learning Outcomes**

After reviewing this article, you will be able to explain the four key analytics techniques: descriptive, diagnostic, predictive, and prescriptive analytics. You will differentiate each type, identify their use in performance management, select the most suitable method for different business needs, and interpret analysis outputs as required in ACCA APM assessments.

## **ACCA Advanced Performance Management (APM) Syllabus**

For ACCA Advanced Performance Management (APM), you are required to understand how advanced analytics methods support organisational performance management. This article covers:

- The principles and interpretation of descriptive, diagnostic, predictive, and prescriptive analytics
- How analytics techniques support performance measurement, forecasting, and decision-making
- Evaluation of different analysis techniques in providing actionable information
- The application of these methods to real-world scenarios and exam requirements

## **Test Your Knowledge**

_Attempt these questions before reading this article. If you find some difficult or cannot remember the answers, remember to look more closely at that area during your revision._

1. Which analytics technique focuses on understanding root causes of past results?  
   a) Descriptive  
   b) Diagnostic  
   c) Predictive  
   d) Prescriptive

2. An ACCA candidate is given a dataset showing declining sales followed by suggestions of actions to reverse the trend. Which type(s) of analytics are being used?

3. True or false? Prescriptive analytics relies on combining prediction with modelling possible outcomes of alternative actions.

4. Briefly state when it would be most suitable to use descriptive analytics rather than predictive analytics.

## **Introduction**

Performance management increasingly relies on extracting actionable information from organisational data. Analytics techniques help managers answer not just what happened, but why, what might happen next, and what to do as a result. Understanding the four main types—descriptive, diagnostic, predictive, and prescriptive analytics—enables you to select the right approach for each scenario posed in the ACCA APM exam.

> **Key Term: analytics**  
> The process of systematically examining data to discover patterns, draw conclusions, and inform decision-making.
>
> **Key Term: descriptive analytics**  
> The method of analysing historical and current data to summarize and present what has happened in the business.
>
> **Key Term: diagnostic analytics**  
> The process of analysing data to identify causes and relationships behind historical outcomes.
>
> **Key Term: predictive analytics**  
> The use of statistical techniques to forecast likely future events based on historical data.
>
> **Key Term: prescriptive analytics**  
> The application of analytics and models to recommend optimal actions in response to predicted outcomes.

## THE FOUR MAIN TYPES OF ANALYTICS

Analytics in performance management can be divided into four categories, each answering a different management question.

### Descriptive Analytics

Descriptive analytics is the starting point for most organisations. It organises, visualises, and summarises raw data.

- Answers the question: What has happened?
- Includes trends, key performance indicators, averages, and summary statistics

**Typical uses:** Monthly sales reports, dashboard summaries of operational results, variance analysis.

> **Key Term: data visualisation**  
> The graphical presentation of analysis results to support rapid management interpretation.

### Diagnostic Analytics

Diagnostic analytics goes a step further to explain why something happened.

- Answers the question: Why did it happen?
- Involves comparison, correlation, cause-and-effect assessment, and data drilling

**Typical uses:** Analysing reasons for revenue shortfalls, investigating cost overruns, identifying process bottlenecks, or explaining variance causes.

### Predictive Analytics

Predictive analytics uses historical data and statistical models to forecast future events or trends.

- Answers the question: What is likely to happen?
- Applies regression, forecasting, scenario modelling, and machine learning tools

**Typical uses:** Sales or demand forecasts, credit risk assessments, inventory demand projections, projecting project outcomes under different scenarios.

### Prescriptive Analytics

Prescriptive analytics recommends specific, data-driven actions given predicted scenarios.

- Answers the question: What should be done?
- Combines predictive models with optimisation, simulation, or machine learning to suggest decisions

**Typical uses:** Resource allocation, setting production schedules, designing pricing strategies, or choosing risk mitigation policies.

### Relationship and Progression

Each method increases in complexity and organisational value:

- **Descriptive analytics** is required for solid reporting.
- **Diagnostic analytics** supports improvement by identifying root causes.
- **Predictive analytics** assists forecasting and proactive management.
- **Prescriptive analytics** supports optimisation of decisions by considering possible future outcomes and recommending actions.

The progression is:

Descriptive → Diagnostic → Predictive → Prescriptive  
(From understanding the past towards making and justifying future decisions)

## SELECTING THE RIGHT ANALYTICS TECHNIQUE

Choosing the most suitable technique depends on:

- The business question being asked
- The availability and reliability of data
- The skills and tools within the organisation
- The required output for planning, decision-making, or reporting

### **Worked Example 1.1**

GlobalWafer Ltd has noted a fall in margin over two quarters. As the management accountant, you generate a detailed report showing trends in profit margins by region and by product.

**Which analytics techniques are used, and what are the limitations?**

> **Answer:**  
> The main approach is descriptive analytics: summarising profits by region and product to present what has happened. This provides clarity on where margins are falling but does not explain the causes or suggest solutions. Without diagnostic analytics, management may overlook root reasons for the margin drop.

### **Worked Example 1.2**

A chain of restaurants uses regression analysis to forecast customer numbers by day of week over the next month, factoring in weather forecasts and prior promotions.

**Which analytics technique is being applied, and how can this support management decisions?**

> **Answer:**  
> The technique is predictive analytics. Using past customer data and external variables, the management accountant forecasts demand to support planning for staffing and ordering. Managers can act proactively rather than reactively.

### **Worked Example 1.3**

A retailer receives an automated dashboard summary showing a sharp drop in online conversions. The management accountant drills into the data, finds a link to slow page load times, and recommends an urgent website upgrade. Predictive models show losses will increase if no action is taken.

**How is prescriptive analytics involved, and why is it important to go beyond description and diagnosis?**

> **Answer:**  
> The recommendation is based on diagnostic analytics (identifying the page speed issue) and predictive analytics (forecasting losses). Prescriptive analytics is evident in recommending a specific action (website upgrade) supported by forecasts of avoided losses, allowing management to select an optimal solution among alternatives.

### **Exam Warning**

In ACCA APM exam scenarios, a common error is to rely solely on descriptive analytics for performance reporting. Always consider whether a deeper (diagnostic), forward-looking (predictive), or action-oriented (prescriptive) analysis is required by the question. Clearly state which method you are using and justify its suitability.

## COMPARISON OF THE FOUR ANALYTICS TECHNIQUES

| Technique    | Key Question       | Typical Output                | Example Application               | Limitations                         |
| ------------ | ------------------ | ----------------------------- | --------------------------------- | ----------------------------------- |
| Descriptive  | What happened?     | Trends, summaries, KPIs       | Monthly sales dashboard           | Does not explain causes or predict  |
| Diagnostic   | Why did it happen? | Variance analysis, drill-down | Root cause of cost increases      | May not suggest future action       |
| Predictive   | What will happen?  | Forecasts, scenarios          | Demand forecasts for next quarter | Dependent on data/model reliability |
| Prescriptive | What should we do? | Decision recommendations      | Scheduling, pricing optimisation  | Complex, data- and skill-intensive  |

## **Summary**

Analytics techniques support better performance management by moving from simple reporting (descriptive) through understanding (diagnostic), anticipating (predictive), to advising on action (prescriptive). For the ACCA APM exam, be able to identify each type, select appropriately based on the scenario, and interpret outputs to support recommendations.

## **Key Point Checklist**

_This article has covered the following key knowledge points:_

- Define and distinguish between descriptive, diagnostic, predictive, and prescriptive analytics
- Identify the business question each technique is suited to answer
- Describe the benefits and limitations of each technique for performance management
- Apply the correct analytics type to example ACCA APM scenarios and explain your choice
- Interpret analysis outputs to inform management decisions or recommendations

## **Key Terms and Concepts**

- analytics
- descriptive analytics
- diagnostic analytics
- predictive analytics
- prescriptive analytics
- data visualisation

Analytics techniques and knowledge generation - Descriptive diagnostic predictive and prescriptive analytics