Interpreting financial data

This article was written following marking of the December 2007 exam papers, which revealed more guidance was required on this topic
The transition from Paper F2 to Paper F5 cannot be underestimated. When preparing for the Paper F5 exam, students need to carefully consider what the examiner is looking for. The purpose of this article is to point students in the right direction when studying the interpretation of financial data – which is a major topic in the Paper F5 syllabus.
This article has been written following marking of the December 2007 exam papers. Although there were many very good answers to Question 2 (‘Ties Only’), it was clear that more guidance is needed for some candidates. Students are advised to look at Question 2 while reading this article, as extracts from the question are used to illustrate points and explain the techniques needed.

ASSESSING FINANCIAL PERFORMANCE

In the December 2007 exam, candidates were asked to assess the financial performance of the business in its first two quarters, when sales had jumped 61% from Quarter 1 to Quarter 2. This calculation should present no problem ((Q2/Q1) - 1) expressed as a % increase). However, an ‘assessment’ requires a qualitative comment or two. A percentage alone will not gain a pass mark.
In most questions there will be some background information – you should use it. Ties Only operated in a competitive environment – as stated in the question – and so a 61% increase in one quarter sounds pretty good in a competitive situation, and to say so will earn a mark. It was also the first two quarters of the business year and so this level of growth is impressive – another mark. If you then go on to say that such high growth rates are often hard to maintain, you will gain another mark. Top-scoring students should be aiming to make these kinds of observations. Hypothesising as to why the growth is happening is also a source of marks. Revenue growth can be the result of extra volume or increasing prices. In the case of Ties Only, it is much more likely to be increased volume; the price will surely be constrained by competition, and from the information provided in Part (b), you can work out that prices are falling (although that calculation was not required). Suggesting that Ties Only has secured more customers, and hence increased volume of sales, scored a mark.
Candidates must be brave and commit themselves. You must express an opinion. It is not acceptable to suggest that management investigate. Although in the real world this may well happen, in the exam hall you have to demonstrate that you know where to look.

INTERPRETATION

The principle of interpretation can be applied to other areas of the syllabus. In Question 3 of the December 2007 exam, candidates were required to interpret sales performance. Again, it is recommended that you refer to Question 3. Broadly, in this question, the market was shrinking and the company was struggling a little as a result. It had reduced sales prices and fought off an 11% fall in the market, losing only 2% of its budgeted sales. This is a good performance, taking the falling market into consideration.
I would expect candidates to be able to interpret the variances and reach the above conclusions. So, if you are given the following information:

• sales price variance $105,600 adv
• sales volume variance $28,000 adv
• sales market size variance $140,000 adv
• sales market share variance $112,000 fav

You should be able to hypothesise as to what has happened, using the information given in the question and your understanding of the data. Adverse sales price variance must mean that sales prices have fallen. This could be the result of competitive pressure. Adverse sales volume variance means that the business hasn’t achieved its budget, which is likely to disappoint management. However, the favourable market share variance is encouraging. This shows that business has been won from the competition, and that the business has also performed well in the areas that it can control.
The adverse market size variance shows a difficult trading environment, which is probably outside the control of the business. Performance should be assessed by taking into account the environment in which a business operates and separating the controllable from the uncontrollable. Note the link between adverse market size and adverse sales price. In the shrinking market of paper diaries (the product in the question), it is likely that the sales prices will fall as sellers scramble to retain as much share as possible.

KEY LEARNING POINTS

In summary: a ratio alone is not enough use the background information given (such as financial data, variances, or narrative) hypothesise as to possible causes and be prepared to select the most likely be brave and express your opinion do not ‘opt out’ and suggest that management 
Written by a member of the Paper F5 examining team

Linear programming

Decision making is an important aspect of the Paper F5 syllabus, and questions on this topic will be common. The range of possible questions is considerable, but this article will focus on only one: linear programming
The ideas presented in this article are based on a simple example. Suppose a profit-seeking firm has two constraints: labour, limited to 16,000 hours, and materials, limited to 15,000kg. The firm manufactures and sells two products, X and Y. To make X, the firm uses 3kg of material and four hours of labour, whereas to make Y, the firm uses 5kg of material and four hours of labour. The contributions made by each product are $30 for X and $40 for Y. The cost of materials is normally $8 per kg, and the labour rate is $10 per hour.
The first step in any linear programming problem is to produce the equations for constraints and the contribution function, which should not be difficult at this level.
In our example, the materials constraint will be 3X + 5Y ≤ 15,000, and the labour constraint will be 4X + 4Y ≤ 16,000. You should not forget the non-negativity constraint, if needed, of X,Y ≥ 0.
The contribution function is 30X + 40Y = C
Figure 1: Optimal production plan

Plotting the resulting graph (Figure 1, the optimal production plan) will show that by pushing out the contribution function, the optimal solution will be at point B – the intersection of materials and labour constraints.
The optimal point is X = 2,500 and Y = 1,500, which generates $135,000 in contribution. Check this for yourself (see Working 1). The ability to solve simultaneous equations is assumed in this article.
The point of this calculation is to provide management with a target production plan in order to maximise contribution and therefore profit. However, things can change and, in particular, constraints can relax or tighten. Management needs to know the financial implications of such changes. For example, if new materials are offered, how much should be paid for them? And how much should be bought? These dynamics are important.
Suppose the shadow price of materials is $5 per kg (this is verifiable by calculation – see Working 2). The important point is, what does this mean? If management is offered more materials it should be prepared to pay no more than $5 per kg over the normal price. Paying less than $13 ($5 + $8) per kg to obtain more materials will make the firm better off financially. Paying more than $13 per kg would render it worse off in terms of contribution gained. Management needs to understand this.
There may, of course, be a good reason to buy ‘expensive’ extra materials (those costing more than $13 per kg). It might enable the business to satisfy the demands of an important customer who might, in turn, buy more products later. The firm might have to meet a contractual obligation, and so paying ‘too much’ for more materials might be justifiable if it will prevent a penalty on the contract. The cost of this is rarely included in shadow price calculations. Equally, it might be that ‘cheap’ material, priced at under $13 per kg, is not attractive. Quality is a factor, as is reliability of supply. Accountants should recognise that ‘price’ is not everything.
How many materials to buy?
Students need to realise that as you buy more materials, then that constraint relaxes and so its line on the graph moves outwards and away from the origin. Eventually, the materials line will be totally outside the labour line on the graph and the point at which this happens is the point at which the business will cease to find buying more materials attractive (point D on the graph). Labour would then become the only constraint.
We need to find out how many materials are needed at point D on the graph, the point at which 4,000 units of Y are produced. To make 4,000 units of Y we need 20,000kg of materials. Consequently, the maximum amount of extra material required is 5,000kg (20,000 – 15,000). Note: Although interpretation is important at this level, there will still be marks available for the basic calculations.

WORKINGS

Working 1:
The optimal point is at point B, which is at the intersection of:
3X + 5Y = 15,000 and
4X + 4Y = 16,000
Multiplying the first equation by four and the second by three we get:
12X + 20Y = 60,000
12X + 12Y = 48,000
The difference in the two equations is:
8Y = 12,000, or Y = 1,500
Substituting Y = 1,500 in any of the above equations will give us the X value:
3X + 5 (1,500) = 15,000
3X = 7,500
X = 2,500
The contribution gained is (2,500 x 30) + (1,500 x 40) = $135,000
Working 2: Shadow price of materials
To find this we relax the material constraint by 1kg and resolve as follows:
3X + 5Y = 15,001 and
4X + 4Y = 16,000
Again, multiplying by four for the first equation and by three for the second produces:
12X + 20Y = 60,004
12X + 12Y = 48,000
8Y = 12,004
Y = 1,500.5
Substituting Y = 1,500.5 in any of the above equations will give us X:
3X + 5 (1,500.5) = 15,001
3X = 7,498.5
X = 2,499.5
The new level of contribution is: (2,499.5 x 30) + (1,500.5 x 40) = $135,005
The increase in contribution from the original optimal is the shadow price:
135,005 – 135,000 = $5 per kg.
Written by a member of the F5 examining team

The risks of uncertainty

This article introduces the concepts of risk and uncertainty together with the use of probabilities in calculating both expected values and measures of dispersion
Clearly, risk permeates most aspects of corporate decision-making (and life in general), and few can predict with any precision what the future holds in store.
Risk can take myriad forms – ranging from the specific risks faced by individual companies (such as financial risk, or the risk of a strike among the workforce), through the current risks faced by particular industry sectors (such as banking, car manufacturing, or construction), to more general economic risks resulting from interest rate or currency fluctuations, and, ultimately, the looming risk of recession. Risk often has negative connotations, in terms of potential loss, but the potential for greater than expected returns also often exists.
Clearly, risk is almost always a major variable in real-world corporate decision-making, and managers ignore its vagaries at their peril. Similarly, trainee accountants require an ability to identify the presence of risk and incorporate appropriate adjustments into the problem-solving and decision-making scenarios encountered in the exam hall. While it is unlikely that the precise probabilities and perfect information, which feature in exam questions can be transferred to real-world scenarios, a knowledge of the relevance and applicability of such concepts is necessary.
In this first article, the concepts of risk and uncertainty will be introduced together with the use of probabilities in calculating both expected values and measures of dispersion. In addition, the attitude to risk of the decision-maker will be examined by considering various decision-making criteria, and the usefulness of decision trees will also be discussed. In the second article, more advanced aspects of risk assessment will be addressed, namely the value of additional information when making decisions, further probability concepts, the use of data tables, and the concept of value-at-risk.
The basic definition of risk is that the final outcome of a decision, such as an investment, may differ from that which was expected when the decision was taken. We tend to distinguish between risk and uncertainty in terms of the availability of probabilities. Risk is when the probabilities of the possible outcomes are known (such as when tossing a coin or throwing a dice); uncertainty is where the randomness of outcomes cannot be expressed in terms of specific probabilities. However, it has been suggested that in the real world, it is generally not possible to allocate probabilities to potential outcomes, and therefore the concept of risk is largely redundant. In the artificial scenarios of exam questions, potential outcomes and probabilities will generally be provided, therefore a knowledge of the basic concepts of probability and their use will be expected.

PROBABILITY 

The term ‘probability’ refers to the likelihood or chance that a certain event will occur, with potential values ranging from 0 (the event will not occur) to 1 (the event will definitely occur). For example, the probability of a tail occurring when tossing a coin is 0.5, and the probability when rolling a dice that it will show a four is 1/6 (0.166). The total of all the probabilities from all the possible outcomes must equal 1, ie some outcome must occur.
A real world example could be that of a company forecasting potential future sales from the introduction of a new product in year one (Table 1).
Table 1: Probability of new product sales

Sales	$500,000	$700,000	$1,000,000	$1,250,000	$1,500,000
Probability	0.1	0.2	0.	0.2	0.1

From Table 1, it is clear that the most likely outcome is that the new product generates sales of £1,000,000, as that value has the highest probability.

INDEPENDENT AND CONDITIONAL EVENTS

An independent event occurs when the outcome does not depend on the outcome of a previous event. For example, assuming that a dice is unbiased, then the probability of throwing a five on the second throw does not depend on the outcome of the first throw.
In contrast, with a conditional event, the outcomes of two or more events are related, ie the outcome of the second event depends on the outcome of the first event. For example, in Table 1, the company is forecasting sales for the first year of the new product. If, subsequently, the company attempted to predict the sales revenue for the second year, then it is likely that the predictions made will depend on the outcome for year one. If the outcome for year one was sales of $1,500,000, then the predictions for year two are likely to be more optimistic than if the sales in year one were $500,000.
The availability of information regarding the probabilities of potential outcomes allows the calculation of both an expected value for the outcome, and a measure of the variability (or dispersion) of the potential outcomes around the expected value (most typically standard deviation). This provides us with a measure of risk which can be used to assess the likely outcome.

EXPECTED VALUES AND DISPERSION

Using the information regarding the potential outcomes and their associated probabilities, the expected value of the outcome can be calculated simply by multiplying the value associated with each potential outcome by its probability. Referring back to Table 1, regarding the sales forecast, then the expected value of the sales for year one is given by:
Expected value
= ($500,000)(0.1) + ($700,000)(0.2)
+ ($1,000,000)(0.4) + ($1,250,000)(0.2)
+ ($1,500,000)(0.1)
= $50,000 + $140,000 + $400,000
+ $250,000 + $150,000
= $990,000
In this example, the expected value is very close to the most likely outcome, but this is not necessarily always the case. Moreover, it is likely that the expected value does not correspond to any of the individual potential outcomes. For example, the average score from throwing a dice is (1 + 2 + 3 + 4 + 5 + 6) / 6 or 3.5, and the average family (in the UK) supposedly has 2.4 children. A further point regarding the use of expected values is that the probabilities are based upon the event occurring repeatedly, whereas, in reality, most events only occur once.
In addition to the expected value, it is also informative to have an idea of the risk or dispersion of the potential actual outcomes around the expected value. The most common measure of dispersion is standard deviation (the square root of the variance), which can be illustrated by the example given in Table 2, concerning the potential returns from two investments.
Table 2: Potential returns from two investments

Investment A		Investment B
Returns	Probability of return	Returns	Probability of return
8%	0.25	5%	0.25
10%	0.5	10%	0.5
12%	0.25	15%	0.25

To estimate the standard deviation, we must first calculate the expected values of each investment:
Investment A
Expected value = (8%)(0.25) + (10%)(0.5) + (12%)
(0.25) = 10%
Investment B
Expected value = (5%)(0.25) + (10%)(0.5) + (15%)
(0.25) = 10%
The calculation of standard deviation proceeds by subtracting the expected value from each of the potential outcomes, then squaring the result and multiplying by the probability. The results are then totalled to yield the variance and, finally, the square root is taken to give the standard deviation, as shown in Table 3.
Table 3: Application of standard deviation to potential returns

Investment A
Returns	Expected return	Returns minus expected returns	Squared	Probability	Column 4 x Column 5
8%	10%	-2%	4%	0.25	1%
10%	10%	0%	0%	0.5	0%
12%	10%	2%	4%	0.25	1%
				Variance	2%
				Standard deviation	1.414%

Investment B
Returns	Expected return	Returns minus expected returns	Squared	Probability	Column 4 x Column 5
5%	10%	-5%	25%	0.25	6.25%
10%	10%	0%	0%	0.5	0%
15%	10%	5%	25%	0.25	6.25%
				Variance	12.5%
				Standard deviation	3.536%

In Table 3, although investments A and B have the same expected return, investment B is shown to be more risky by exhibiting a higher standard deviation. More commonly, the expected returns and standard deviations from investments and projects are both different, but they can still be compared by using the coefficient of variation, which combines the expected return and standard deviation into a single figure.

COEFFICIENT OF VARIATION AND STANDARD ERROR

he coefficient of variation is calculated simply by dividing the standard deviation by the expected return (or mean):
Coefficient of variation = standard deviation / expected return
For example, assume that investment X has an expected return of 20% and a standard deviation of 15%, whereas investment Y has an expected return of 25% and a standard deviation of 20%. The coefficients of variation for the two investments will be:
Investment X = 15% / 20% = 0.75
Investment Y = 20% / 25% = 0.80
The interpretation of these results would be that investment X is less risky, on the basis of its lower coefficient of variation. A final statistic relating to dispersion is the standard error, which is a measure often confused with standard deviation. Standard deviation is a measure of variability of a sample, used as an estimate of the variability of the population from which the sample was drawn. When we calculate the sample mean, we are usually interested not in the mean of this particular sample, but in the mean of the population from which the sample comes. The sample mean will vary from sample to sample and the way this variation occurs is described by the ‘sampling distribution’ of the mean. We can estimate how much a sample mean will vary from the standard deviation of the sampling distribution. This is called the standard error (SE) of the estimate of the mean.
The standard error of the sample mean depends on both the standard deviation and the sample size:
SE = SD/√(sample size)
The standard error decreases as the sample size increases, because the extent of chance variation is reduced. However, a fourfold increase in sample size is necessary to reduce the standard error by 50%, due to the square root of the sample size being used. By contrast, standard deviation tends not to change as the sample size increases.

DECISION-MAKING CRITERIA 

The decision outcome resulting from the same information may vary from manager to manager as a result of their individual attitude to risk. We generally distinguish between individuals who are risk averse (dislike risk) and individuals who are risk seeking (content with risk). Similarly, the appropriate decision-making criteria used to make decisions are often determined by the individual’s attitude to risk.
To illustrate this, we shall discuss and illustrate the following criteria:
1 Maximin
2 Maximax
3 Minimax regret
An ice cream seller, when deciding how much ice cream to order (a small, medium, or large order), takes into consideration the weather forecast (cold, warm, or hot). There are nine possible combinations of order size and weather, and the payoffs for each are shown in Table 4.
Table 4: Decision-making combinations

Order/weather	Cold	Warm	Hot
Small	$250	$200	$150
Medium	$200	$500	$300
Large	$100	$300	$750

The highest payoffs for each order size occur when the order size is most appropriate for the weather, ie small order/cold weather, medium order/warm weather, large order/hot weather. Otherwise, profits are lost from either unsold ice cream or lost potential sales. We shall consider the decisions the ice cream seller has to make using each of the decision criteria previously noted (note the absence of probabilities regarding the weather outcomes).
1 Maximin
This criteria is based upon a risk-averse (cautious) approach and bases the order decision upon maximising the minimum payoff. The ice cream seller will therefore decide upon a medium order, as the lowest payoff is £200, whereas the lowest payoffs for the small and large orders are £150 and $100 respectively.
2 Maximax
This criteria is based upon a risk-seeking (optimistic) approach and bases the order decision upon maximising the maximum payoff. The ice cream seller will therefore decide upon a large order, as the highest payoff is $750, whereas the highest payoffs for the small and medium orders are $250 and $500 respectively.
3 Minimax regret
This approach attempts to minimise the regret from making the wrong decision and is based upon first identifying the optimal decision for each of the weather outcomes. If the weather is cold, then the small order yields the highest payoff, and the regret from the medium and large orders is $50 and $150 respectively. The same calculations are then performed for warm and hot weather and a table of regrets constructed (Table 5).
Table 5: Table of regrets

Order/weather	Cold	Warm	Hot
Small	$0	$300	$600
Medium	$50	$0	$450
Large	$100	$200	$0

The decision is then made on the basis of the lowest regret, which in this case is the large order with the maximum regret of $200, as opposed to $600 and $450 for the small and medium orders.

DECISION TREES

The final topic to be discussed in this first article is the use of decision trees to represent a decision problem. Decision trees provide an effective method of decision-making because they:

• clearly lay out the problem so that all options can be challenged
• allow us to fully analyse the possible consequences of a decision
• provide a framework in which to quantify the values of outcomes and the probabilities of achieving them
• help us to make the best decisions on the basis of existing information and best guesses.

A comprehensive example of a decision tree is shown in Figures 1 to 4, where a company is trying to decide whether to introduce a new product or consolidate existing products. If the company decides on a new product, then it can be developed thoroughly or rapidly. Similarly, if the consolidation decision is made then the existing products can be strengthened or reaped. In a decision tree, each decision (new product or consolidate) is represented by a square box, and each outcome (good, moderate, poor market response) by circular boxes.
The first step is to simply represent the decision to be made and the potential outcomes, without any indication of probabilities or potential payoffs, as shown in Figure 1.
The next stage is to estimate the payoffs associated with each market response and then to allocate probabilities. The payoffs and probabilities can then be added to the decision tree, as shown in Figure 2. The expected values along each branch of the decision tree are calculated by starting at the right hand side and working back towards the left recording the relevant value at each node of the tree.
These expected values are calculated using the probabilities and payoffs. For example, at the first node, when a new product is thoroughly developed, the expected payoff is:
Expected payoff = (0.4)($1,000,000) + (0.4)
($50,000) + (0.2)($2,000) = $420,400
The calculations are then completed at the other nodes, as shown in Figure 3. We have now completed the relevant calculations at the uncertain outcome modes.
We now need to include the relevant costs at each of the decision nodes for the two new product development decisions and the two consolidation decisions, as shown in Figure 4.
The payoff we previously calculated for ‘new product, thorough development’ was $420,400, and we have now estimated the future cost of this approach to be $150,000. This gives a net payoff of $270,400.
The net benefit of ‘new product, rapid development’ is $31,400. On this branch, we therefore choose the most valuable option, ‘new product, thorough development’, and allocate this value to the decision node.
The outcomes from the consolidation decision are $99,800 from strengthening the products, at a cost of $30,000, and $12,800 from reaping the products without any additional expenditure.
By applying this technique, we can see that the best option is to develop a new product. It is worth much more to us to take our time and get the product right, than to rush the product to market. And it’s better just to improve our existing products than to botch a new product, even though it costs us less.

Written by a member of the F5 examining team

INTEGRITY

Dear Colleague,

Last month we had training on Integrity as the bed rock of banking. For today, I still want talk more on Integrity as it relate to leadership.

Integrity is particularly important because those with integrity earn the respect and trust of others and they are more effective as leader. According to Jack Welch, people with integrity tells the truth and they keep their words, takes responsibility for their past actions, admit mistakes and fix them, they know the laws of the country, industries and companies both in letter and in spirit and abide by them, they play to win the right way by the rules. There is a common thing among experts who has study or written about modern leadership, that all leaders must act with integrity at all times, the reason for this is that subordinates are constantly observing the leader.

What is then the Integrity? Webster dictionary tell us that is the quality of bringing sound moral principles, uprightness, honesty & sincerity. However, a definition I found very interesting is the one attributed to bobby Johns who says integrity is what you do when no one is watching and that you do in private is who you are.

Integrity also involves the three R’s

·         Respect for yourself
·         Respect for others and;
·         Responsibilities for all your actions.

Therefore, integrity is the mirror revealing the truth about an individual or corporation. Integrity involves working the talk and not just talking it. On a personal level, Integrity involves both the part of who you are and what you do.

Integrity is measure by what individual does and does not do when no one is looking:

·         Did they own to their value and ethics?

·         Do they compromise what they believe it’s right?

·         Why at corporate level, we may want to ask, do corporate reports, filling and stakeholder communications state one thing when in reality the corporation is doing something else?

These questions are pertinent to our understanding of integrity and how it can shape the organization we work for.

According to Jack Welch, without integrity we have no organization, you have nothing, integrity is the foundation upon which you build something. Therefore to succeed in our chosen career and move the organization forward, we must do away with the do as I say not as you do attitude. We must imbibe such values that are based on moral principle of honesty, uprightness & sincerity.

Distinguish colleague, let end this by reminding us that you can preach a better sermon with your life than with your lips.

FOOD FOR THOUGHT

“Integrity without knowledge is weak and useless and knowledge without integrity is dangerous and gravely “(Samuel Johnson).

Thank you and God bless.

 

Value chains, value networks and supply chain management

This article considers writer Michael Porter’s value chain framework, which has been described as a powerful analysis tool for companies in strategic planning to create value. It also highlights the various definitions of supply chain management put forward by different writers
Sections A4, E2 and E3 of the Syllabus and Study Guide relate to value chains and value networks, and Sections E2 and E3 of the Paper P3 Syllabus and Study Guide relate to the supply chain with particular, but not exclusive, reference to the application of e-business.
Value chains and supply chains have featured explicitly in the pilot paper, December 2007, December 2009 and June 2012 exams. In addition, value chains can often be used in position analysis.

The value chain and value networks

Porter’s value chain displays groupings of all the activities that organisations carry out. The activities are divided into primary activities and secondary activities. All activities have costs and successful businesses organise and carry out their activities in such a way that value is added. It is the value added that allows revenues to exceed costs so that profits are made.

To add value, the organisation must be doing more for its customers than simply carrying out the ‘face value’ of the activities, otherwise customers would presumably carry out the activities themselves. Customers either cannot carry out the activities at all, or cannot match costs, or don’t want to carry on the activities and so are willing to pay others to carry them out instead. For example:

• knowhow – suppliers often use knowhow that customers simply don’t have

• economies of scale – suppliers often produce efficiently in huge volumes with each customer buying only a small proportion. Suppliers’ economies of scale simply cannot be replicated by each customer

• risk – suppliers might shoulder production risks that customers don’t want

• location – suppliers might be in a low-cost area while customers are in a high cost area

• flexibility – suppliers are variable costs, while doing it yourself usually entails more fixed costs.

As always, success in business arises from one of Porter’s generic strategies – cost leadership or differentiation – each with or without focus. Value chains have to underpin the chosen generic strategy. So, if cost leadership is the strategy, the value chain adds value by enabling low cost production.
Curiously, the value chain relegates procurement (the purchase of goods and non-current assets) to a support activity, yet has sales and marketing in primary activities. In modern manufacturing companies this disparity does not make a lot of sense because what is important is the complete chain from suppliers to customers. This is acknowledged in the idea of value networks:

Value networks recognise that few companies stand alone and that what is ultimately supplied to and paid for by customers depends on activities carried on by many suppliers, distributors and, indeed, logistical companies. Ultimately, customer satisfaction and value added depend on all parties working well together.

The supply chain and supply chain management

There is no generally accepted definition of the term ‘supply chain management’ and many different definitions can be found in relevant literature. For example:
‘A concept whose primary objective is to integrate and manage the sourcing, flow and control of materials using a total systems perspective across multiple functions and multiple tiers of suppliers.’ La Londe and Masters (1994)
‘The objective of managing the supply chain is to synchronise the requirements of the customer with the flow of materials from suppliers in order to effect a balance between what are often seen as conflicting goals of high customer service, low inventory management, and low unit cost.’ Stevens (1989)
‘…an integrative philosophy to manage the flow of a distribution channel from supplier to the ultimate user.’ Cooper et al (1997)
From these definitions, it can be seen that supply chain management has the following features:

• Integrating and managing the sourcing, flow and control of materials.

• Supply chain management covers the flow of materials suppliers through to customers

• Potentially many suppliers and customers.

• Synchronising of materials received, processed and despatched to customers.

• Simultaneously achieving good levels of customer service and low costs for the company.

Supply chains are often divided into upstream and downstream operations in an analogy with material floating down a river, into and then out of operations:

• Upstream – the flow of materials into the organisation.

• Downstream – the flow of materials from the organisation to the customers.

However, these terms might sometimes have to be interpreted liberally as materials can go directly from supplier to customer with the organisation itself acting as a co-ordinator of the flow.
For businesses that manufacture their own products, the upstream supply chain will be taken to consist of the following value chain activities:

• Procurement – purchasing inputs such as supplies, material and equipment.

• Inbound logistics – receiving raw materials, holding inventory and issuing to manufacturing operations as required.

Downstream supply chain will be assumed to consist of:

• outbound logistics – the storing and distribution of finished goods.
• marketing and sales – identifying customer needs and generating sales.
• services.

You will note that procurement and marketing and sales do not
themselves involve any movement of goods, but these activities initiate the flows of raw materials, components and finished products, so need to be included as part of supply chain management. Service can also be included here as certainly the supply of elements such as consumables, maintenance and training can be valuable sources of value added and need to be managed.
A useful view of supply chain management is suggested by Meyr, Wagner and Rohde (2004):

Here, in contrast to Porter:

• procurement is seen as a primary activity and will include inbound logistics, or their equivalent. Procurement is a central part of the supply chain and not merely a support function. Wise and skilled purchasing, as well as the physical movement of goods, will be capable of creating value

• customer-facing activities (previously, sales, marketing and services) are combined into sales

• ‘production’ is used instead of ‘operations’ in Porter’s value chain. This is more precise (but perhaps more restricted).

The important additional emphasis in this presentation is on collaboration between up-stream suppliers and the down-stream customers. Together, they form the value network that creates value through the appropriate operation of the whole chain to improve efficiency, delivery accuracy and times, cost reduction and inventory minimisation.
You will readily understand that collaboration can often be greatly facilitated by the use of information technology, which can integrate online orders received from customers with manufacturing inventory management and purchases of raw materials and components from suppliers.

Push/pull supply chain models

A push model of the supply chain relies on manufacturers producing according to historical demand patterns and pushing products out to distributors and customers. Inventory is held at various points as a buffer against unexpected demand or production delays. By contrast, in a pull model demand stimulates production and delivery. Essentially, just-in-time inventory control is a pull model as ordering and production are triggered by customers’ orders. No orders are raised nor production started until there is downstream demand.
Of course, pure push or pull models exist only in theory: demand for a product will never cause a supply chain to start mining iron ore and producing steel. Nor will a push model guarantee that products made will be bought. At some point, in every supply chain, demand push will meet demand pull, and inventory will accumulate there. Note that large geographical distances between suppliers and customers, or processes that take time (such as growing crops) make pull systems more difficult to organise.
However, inventory can be minimised and customer service improved if all parties in the supply chain can be better synchronised and have the ability to react quickly. For example, a traditional model of replenishing inventory in supermarkets would rely on each supermarket issuing an order to suppliers, probably by electronic data interchange (EDI), once inventory falls below reorder level. However, orders then arrive ‘out-of-the-blue’ at suppliers, who either have to have sufficient production capacity or who have to hold inventories to respond quickly. A better way is to give suppliers access to supermarkets’ inventory records through an extranet so that inventory levels and rates of change can be monitored. Supplies can be dispatched even without having to wait for an order. In this way, suppliers will be much better able to anticipate demand and produce accordingly. Better synchronisation and lower inventory levels have been achieved.
Information technology is of great assistance in moving towards a pull model as it influences the downstream supply chain through the 6I’s of e-business:

• Intelligence – for example, internet sites can track user activity and from that analyse which products are growing or falling in popularity. Information can be fed directly into a data warehouse for subsequent analysis and data mining.

• Interactivity – internet customers can customise their purchases. For example, some computer companies build to order allowing different combinations of hardware and software to be chosen.

• Integration – following on from interactivity, once an order has been placed, the pull process can begin by scheduling component ordering, production and despatch.

• Individualisation – for example, relevant offers can be made to each customer. If someone has bought a particular printer, then subsequently offers can be made to sell ink or toner cartridges.

• Independence (from location) – the location of the supplier is largely irrelevant provided a good procurement and distribution system is in place. This is covered further below under logistics.

• Industry (structure) – fast responses to customer demand is liable to affect industry structure as it will often favour larger, better-organised companies who make use of sophisticated ordering and delivery solutions. There are fewer and fewer places in which poor performers can hide.

Supply chain choices

Supply chain pathways can be complex:

As with many other functions, outsourcing is increasingly used in supply chain management. Logistics companies can perform many supply chain functions more efficiently and economically than they can be done in-house, and we will see some examples below.
Some of the main choices to be made in supply chain pathways are as follows.
(1) Who transports the goods? The main solutions are:

• the buyer transfers them using own transport
• the seller transfers them using own transport
• a logistics company transfers them

(2) What delivery pathways are best?
(3) Who stores the goods? The organisation, the supplier, or a logistics company.
(4) Which manufacturing, packaging, labelling, kitting, or completion tasks are carried out by the organisation and which by other parties? (Kitting relates to processes such as adding batteries).
(5) Who is responsible for quality assurance and proper handling of the goods?
(6) How should returns be handled?
(7) How can fast and responsive deliveries by arranged?
(8) Who handles customs clearance?

Supply chain examples

Pharmaceutical: Many pharmaceuticals, such as insulin and flu vaccines, are temperature-sensitive and have to be stored below, say, 5°C to maintain their efficacy and safety. Manufacturers therefore need ensure that their worldwide distribution, by air and road, to hospitals and pharmacies can be guaranteed to have complied with the storage required and that this can be verified and demonstrated. It is not realistic for pharmaceutical companies to carry out such specialised distribution themselves on a worldwide basis, as this would imply refrigerated warehouses, air freight and transportation in every country supplied. Many logistics companies offer suitable services.
Packaging: Transporting packaging is wasteful, adding both weight and volume to products. Therefore, an efficient distribution solution can be to export the basic products and then package those locally with using language-specific packaging. Once again, it can be inefficient for manufacturers to do this and frequently logistics companies carry out locally the packaging, printing instructions and labelling.
Customs clearance: Each country tends to have its own import regulations and tariffs. Navigating through these requires considerable local expertise and logistics companies are often used to facilitate the efficient international movement of goods.
Distribution: Imagine you distribute a product throughout Europe and customers need stock replenished frequently and quickly. One solution would be to set up your own warehouses and distribution vehicles in every country. However, you will realise that this would require vast resources. Almost certainly it would be better to outsource this to a logistics company as that is likely to enjoy great economies of scale. The logistics company can both warehouse the goods locally and provide transport to customers allowing a more just-in-time approach to be taken.
Ken Garrett is a freelance lecturer and author

Information Technology

INFORMATION TECHNOLOGY 
1. Principles of information technology 
(a) Advise on the basic hardware and software infrastructure required to support business information systems.
(b) Identify and analyse general information technology controls and application controls required for effective accounting information systems.
(c) Analyse the adequacy of general information technology controls and application controls for relevant application systems.
(d) Evaluate controls over the safeguarding of information technology assets to ensure the organisational ability to meet business objectives.
In particular, in (a) above, knowledge and skills relating to hardware and software infrastructure have expanded from a focus on e-business to more general business information systems. (b), (c) and (d) above all relate to controls which were not mentioned at all in earlier syllabuses or study guides.

Infrastructures to support business
information systems

Very large companies began to use of computers in the 1960s. The first applications were for wages and salaries processing, the production of sales invoices and receivables ledger accounting. These applications automated existing operations allowing greater accuracy, more speed and cheaper processing. At this time the IT operations would have been called ‘data processing’.
Once transactions are processed by computer it is easy to analyse those transactions to produce information that could be useful for management. For example, once the sales ledger is computerised it is easy to produce aged receivables listings. These additional management reports became common in the 1970s (and are still important) and IT operations became known as ‘management information systems’ (MIS). The systems could also be programmed to make simple decisions such as comparing inventory levels to production plans to enable automatic stock ordering. The simple decisions are known as programmable or structured decisions, meaning that there is a well-defined way of getting to the correct answer. MIS primarily allows companies to keep their costs down, helping them to move towards cost leadership, through a combination of automation and rationalisation.
At the beginning of the 1980s, spreadsheets were invented and this allowed computers to be used to help managers make unstructured (non-programmable) decisions. For these decisions there is no definitively right answer. For example, what should next year’s budget look like? At what price should a new product be launched? Financial models on spreadsheets allow managers to try out 'what if?' experiments where they try out different combinations of assumptions and try to home in on a credible answer. These systems are known ‘decision support systems’ (DSS): they do not make the decision but help managers make decisions.
More sophisticated DSS systems can combine, for example, computer aided design and computer aided manufacturing systems to enable new products to be brought to market more quickly: data warehousing (recording historical transaction data) and data mining (trawling through that data to learn more about customers’ preferences and buying patterns). Both of these techniques can help with differentiation and focus strategies.
Somewhat later, around the 1990s, executive information systems were developed. These were of particular use to senior managers and they have a particular emphasis on giving access to external information that is needed for operational and strategic planning. It was, of course, in the 1990s that the Internet began to expand rapidly and much more external information became available. Executive information systems also emphasise flexibility so that executives can see company data in a wide variety of ways. Typically, such systems would initially present sales for the group, but upon double-clicking on that figure, it would split into sales by division. Double-clicking on one of those figures might show the sales to the division’s 10 key customers, compared to the comparable period last year. This process is known as drilling down.
Databases are by far the preferred way to hold data. Databases allow a wide range of users and applications to use the data flexibly and to update it. Each user can be given a unique, personalised and relevant view of the data which they can easily search and manipulate.
The increasing reliance on computers by all levels within a company requires careful design of the information technology (IT) infrastructure. IT usually refers to the hardware: computers, connections, disk storage.

Networks

Only the very smallest of businesses will have stand-alone computers, computers not connected to other computers. Even in small businesses employees need to share data and very soon after personal computers were invented networks of computers were introduced. There are two main types:

• Local area network (LAN): Here the network extends over only a relatively small area, such as an office, a university campus or a hospital. The small area means that these networks use specially installed wiring to connect the machines. 
• Wide area networks (WAN): Here the network can extend between several cities and countries. Each office would have its LAN, but that connects to LANs in other offices and countries using commercial, public communications systems. At one time this would have been done by the organisation leasing telephone lines for their private use to transmit data from office to office. However, this is expensive and inflexible and the common system now used is known as a virtual private network (VPN)  

VPN’s allow data to be transmitted securely over the internet between any two locations. For example, an employee working from home or a hotel can access the company system as though being in the office. Information will pass over many different circuits and connections but the system gives the impression that you are operating over a dedicated, private communications link. Hence, the name: virtual private network. Because data is being transmitted over public systems it is particularly vulnerable to interception and it is very important that adequate security measures are in place to safeguard the data. There are three essential steps in the security measures:

1. Access control and authentication – this ensures that unauthorised users do not access the system. Typically this will be accomplished through a log-in procedure. Many organisations, such as banks, may require a password, answers to security questions (such as ‘What is the fourth letter of your secret word?’), and also a code number generated by a security device that has been issued to the user. Use of the latter technique means that anyone logging on has both to know a password and to be in possession of the security device.
2. Confidentiality – this ensures that data cannot be intercepted and read by a third party whilst being transmitted. This is achieved using encryption.
3. Data integrity – this ensures that the data has not been altered or distorted whilst in transit. To ensure this, the message could have special check digits added to ensure that the data complies with a mathematical rule.

Centralised and decentralised (distributed) architectures

Consider an office local area network. There are three main ways in which the data and processing can be arranged: centralised, decentralised (distributed) and hybrid.
Centralised systems
In these systems there is a powerful central computer which holds the data and which carries out the processing. The main advantages of such systems are:

• Security: all data can be stored in a secure data centre so that, for example, access to the data and back-up routines are easier to control.
• One copy of the data: all users see the same version of the data.
• Lower capital and operational costs: minimal hardware is needed at each site. There is also less administrative overhead.
• The central computer can be very powerful:  this will suit in processing-intensive applications.
• They allow a centralised approach to management. For example, a chain of shops needs to keep track of inventory in each shop and to transfer it as needed. There is little point in a shop that is running low ordering more of a product if another branch already has a surplus of that product.

The main disadvantages of such systems are:

• Highly dependent on links to the centralised processing facility. If that machine fails or communication is disrupted then all users are affected.
• Processing speed: will decrease as more users log-on
• Lack of flexibility: local offices are dependent on suitable software and data being loaded centrally.

Decentralised (distributed) systems
In these systems, each user has local processing power and will hold data locally.
The main advantages of such systems are:

• Resilience: if one machine breaks down, others are unaffected.
• Easy expansion: simply add another computer.
• Flexibility: local users can decide which programs and software should be installed to meet local needs.
• They are more useful where each location can operate more or less separately from others.

The main disadvantages are:

• More difficult to control: data storage and processing are in many locations and correct access, processing and back-up of data are more difficult to enforce.
• Multiple versions of data: users might have their own version of data that should be uniform.
• Potentially higher costs: each local computer has to have sufficient processing power and each location might require an IT expert.

Hybrid systems
In these systems some data and processing are local and some are centralised. For example, web-browsing and word-processing might be local but critical business applications might be centralised.

Client-server and peer-to-peer systems

These concepts are similar to centralised and decentralised, but are not quite identical.
In a client-server arrangement, a powerful computer (the server) is dedicated to providing a service to other computers in the network (the clients). Typical services provided are:

• File storage (file servers)
• Handling printing (print server)
• Handling the sending and receiving of emails (mail servers).

There is an element of centralisation here, but although files might be held centrally on the server they will often be processed locally. For example, a report will be held on the server, but when it is being edited it is downloaded to the user’s local machine (client). The edited version will be saved back to the server where other users can then access it. Obviously there will be great disruption if the server fails. Access rights to files are set centrally and typically enforced by users’ log-on information.
Traditionally, in client server networks each client would have had a copy of, say, Word for Windows. Documents would have been downloaded from the server for local editing then saved back to the server. The disadvantage of this is that each machine in the network needs a copy of Word and if the company was upgrading its software all copies of the program would have to be changed. Providing the software initially for all machines and its subsequent management is very expensive. With cloud computing, this approach has changed. There is only one copy of the software on the server within a web-based interface. Users log into the web system and their processing is then carried out on the server or a ‘cloud’ of servers. It appears to each user that they have a local version of the software, but what they are really seeing is the program operating in the server. Client machines can be ‘thin-clients’ which are not very powerful as they do not have to store much data and software nor do they have to carry out much processing. Hardware, software and maintenance costs are greatly reduced, though the system is vulnerable to service disruption.
Hotmail and Gmail provide examples of this approach. Whenever you want to write an email you log into the web email account and the processing is carried by the system’s computer cloud – not your computer. All it has to do is to handle the interface.
In peer-to-peer networks, two or more computers are connected directly without the need for a server. Access rights to files are given by individual users to specified other users. This is a simpler system to set-up, requiring no specialist operating system or specialist staff and many home systems are like this. It is a much more distributed system than client server systems and therefore has back-up and security issues.

Controls in IT systems

IT poses particular risks to organisations’ internal control and information systems. This can lead to their operations being severely disrupted and subsequently to lost sales, increased costs, incorrect decisions and reputational damage.
Risks include:

• Reliance on systems or programs that are inaccurately processing data, processing inaccurate data, reporting inaccurate, misleading results - or all three.
• Unauthorised access to data leading to destruction of data, improper changes to data, or inaccurate recording of transactions.
• Particular risks may arise where multiple users access a common database on which everyone in the organisation relies.
• The possibility of IT personnel gaining access privileges beyond those necessary to perform their assigned duties.
• Unauthorised changes to data in master files. For example, changing a selling price or credit limit.
• Unauthorised changes to systems or programs so that they no longer operate correctly and reliably.
• Failure to make necessary changes to systems or programs to keep them up-to-date and in line with legal and business requirements.
• Potential loss of data or inability to access data as required. This could prevent, for example, the processing of internet sales.

Controls in computer systems can be categorised as general controls and application controls.

General controls

These are policies and procedures that relate to the computer environment and which are therefore relevant to all applications. They support the effective functioning of application controls by helping to ensure the continued proper operation of information systems. General IT controls that maintain the integrity of information and security of data commonly include controls over the following:

• Data centre and network operations. A data centre is a central repository of data and it is important that controls there include back-up procedures, anti-virus software and firewalls to prevent hackers gaining access. Organisations should also have disaster recovery plans in place to minimise damage caused by events such as floods, fire and terrorist activities. Where IT is critical to an operation’s business these plans might include having a parallel system operating at a remote location that can be switched to immediately.
• System software acquisition, change and maintenance. System software refers to operating systems, such as Windows or Apple’s OS. These systems often undergo updates as problems and vulnerabilities are identified and it is important for updates to be implemented promptly.
• Access security. Physical access to file servers should be carefully controlled. This is where the company keeps it data and it is essential that this is safeguarded: data will usually endow companies with competitive advantage. Access to processing should also be restricted, typically through the use of log-on procedures and passwords.
• Application system acquisition, development, and maintenance. Applications systems are programs that carry out specific operations needed by the company – such as calculating wages and invoices and forecasting inventory usage. Just as much damage can be done by the incorrect operation of software as by inputting incorrect data. For example, think of the damage that could be done if sales analyses were incorrectly calculated and presented. Management could be led to withdraw products that are in fact very popular. All software amendments must be carefully specified and tested before implementation.

Example: Royal Bank of Scotland
A software update was applied on 19 June 2012 to RBS's system which controls its payment processing. The update had been corrupted by RBS technical staff so that customers' wages, payments and other transactions were disrupted. Many customers were unable to withdraw cash using automatic teller machines and were not able to see their bank account details. Others faced fines and surcharges for late payment of bills because the system could not process direct debits. For many customers the disruption lasted for around a week.

Application controls 

Application controls are manual or automated procedures that typically operate at a business process level, such as the processing of sales orders, wages and payments to suppliers.
These controls help ensure that transactions are authorised, and are completely and accurately recorded, processed and reported. Examples include:
Edit checks of input data
Checks on input data are very important because once data has been input it is often automatically processed thereafter without the further chance of human scrutiny. Methods include:

• Range tests can be applied to reject data outside an allowed range. For example, when accepting orders through a website, the system could be programmed to prevent, or at least query, unusually large quantities being ordered.
• Format checks ensure that data is input in the correct format (credit card numbers should be 12 digits long).
• Dependency checks, where one piece of data implies something about another (you have probably had a travel booking rejected because you inadvertently had a return date earlier than the outward date).
• Check digits, where a number, such as an account number, is specially constructed to comply with mathematical rules. For example, UK and European VAT numbers use this method:

VAT number = GB 2457193 48 (the last two digits, here 48, are the check digits)

The first seven numbers are multiplied by the weighting factors 8, 7, 6, 5, 4, 3, 2:

So 2 x 8 + 4 x 7 + 5 x 6 + 7 x 5 + 1 x 4 + 9 x 3 + 3 x 2 = 146

Subtract 97 until the result is zero or negative:

146 – 97 – 97 = -48

The resulting number is the check digit. The chances of someone incorrectly typing in a VAT number which accidentally followed these rules are very small.

• Numerical sequence checks to ensure that all accountable documents, such as cheques, have been processed.
• Drop down menus which constrain choices and ensure only allowable entries can be made. For example, constraining delivery choices to ordinary post or express delivery, or presenting a list of allowable account codes.
• Batch total checks. Here, the data is first added up to create a control total, which is subsequently compared to the total of the data actually submitted.

Online, real time systems can pose particular risks because any number of employees could be authorised to process certain transactions. Anonymity raises the prospect of both carelessness and fraud so it is important to be able to trace all transactions to their originator. This can be done by requiring users to log-on and then tagging each transaction with the identity of the person responsible. Logging on should require passwords and it is important that members of staff keep these confidential. Many business systems enforce a rule that requires passwords to be changed every few months. This is fine in theory, but to remember their changing passwords many users start to write them down – a potential breach in security. Increasingly, biometric measurement, such as fingerprint or retina recognition, can be used to control access.
Log-in security, whether through passwords or biometrics, also helps to control both processing and access to data. Each user is provided with tailored rights that allow them to see only certain data, change only certain data and to carry out only specified processing.

Conclusion

This article has mentioned encryption, firewalls authentication and access controls. It is important to realise that even with these measures in place that organisations can be damaged by lapses in computer security. For example:

• November to early December 2013, Target Corporation (turnover around $70bn) announced that data from around 70 million credit and debit cards was stolen.
• April 2011, Sony experienced a data breach within their Playstation Network that the information of 77 million users was compromised.
• May 2014, Ebay announced that three months earlier that information (including passwords, email addresses, birth dates, mailing addresses and other personal information) relating to 145 million users had been stolen. Ebay states that the information was encrypted and there is no evidence that is has been decrypted (yet).

Cyber-espionage is also a growing threat. Governments, competitors and criminals attempt to steal intellectual property or information about customers and contracts. Quite obviously the theft of valuable know-how will undermine a company’s competitive advantage and it is essential that for organisations to defend themselves as far as possible against these threats.
Ken Garrett is a freelance lecturer and writer

Public sector governance – part 2

Relevant to Paper P1 from December 2014
In this, the second of two articles considering the new content in the Paper P1 Study Guide on public sector governance, the final three outcomes are discussed. These are all from Study Guide section A9.
b) Describe, compare and contrast the different types of public sector organisations at subnational, national and supranational level.

Public sector organisations – those involved in delivering state services that cannot always be effectively delivered by the private sector – can exist at several different levels. Perhaps we usually think of these at the national level. National government is usually based in the national capital city and is divided into central government departments (all examples of national-level public sector organisations). The names given to these departments vary by country but most governments have a treasury, an interior department, a foreign office, a defence department, a health service, education, social services, etc. In many cases, these departments are led by a political minister from the governing political party. This is important in democratic countries because the policies adopted by these departments affect many people and it is important that they are subject to political change if the electorate changes a government at an election (this being a part of the social contract between the government and the governed).
In addition, national government policy is configured and coordinated centrally to ensure that strategic policies are pursued and that departments work together to ensure this. The head of government (not to be confused with the head of state) is responsible for national government policy and in a democracy, he or she can be re-elected or defeated based on his or her performance in the role.
In terms of governance, national government departments are nominally headed by a minister from the governing political party. This means that he or she issues instructions on how the department should formulate and implement policy to help achieve the government’s overall strategic objectives. There is also, however, a substantial structure of permanent government employees (sometimes called ‘civil servants’ or similar) whose role it is to advise the minister and help him or her to implement policy in the relevant department.
In addition to national government, public sector organisations also exist at the supranational and subnational levels. Below national level (‘subnational’), some countries are organised or subdivided into regional authorities, variously called regional assemblies, states, cantons, departments, municipalities, local authorities or similar. Some selected powers are devolved down to these subnational bodies by national government in the belief that these selected powers are either best handled by local people or that service delivery to the regions will be more efficient or cost effective if done so. Typical powers devolved down to the subnational level include planning (such as roads and new housing permissions), utilities (such as energy and water), local schools, housing, support of vulnerable communities, rubbish collection, etc. In many countries, for example, children’s education is one of the tasks devolved to local authorities. This is because local authorities are usually in possession of the particular statistics and needs analyses that are necessary for effective planning of education services. So if a large new housing project is planned, it will be typically be the local authority that ensures that a school is located nearby for children in that area to attend. Similarly, local demographic trends and particular educational needs may be better understood by subnational authorities than by national government. In such cases, individual schools must report to the local authority on selected metrics, which might include budgetary compliance, teaching quality and exam results.
In many cases, subnational public sector organisations are led by elected representatives in a similar way to national governments. These are supported by permanent officials in a similar manner to civil servants in national governments.
Supranational bodies are a little more complicated. When national governments form supranational bodies, they do so for a shared purpose and they are often subject to significant pressures as a result. This is often because national governments do not agree with each other, as each one is subject to pressure from its own people to prefer one outcome to another in the supranational organisation. Many European countries, for example, are members of the European Union, with offices in Strasbourg and Brussels, whilst similar bodies exist elsewhere in the world. The United Nations (UN), based in New York, expresses the collective opinion of many countries in different parts of the world, on a range of international issues. The UN employs many thousands of people both at its headquarters in New York and around the world through its various agencies (eg in the World Health Organisation, in its refugee agency, environment programme, etc). Similarly, the World Trade Organisation (WTO, formerly the General Agreement on Tariffs and Trade) meets every few years (in ‘rounds’ named after the city they meet in) in order to help with reducing barriers to international trade in terms of reducing or removing tariffs (import taxes) and quotas (limits on imports of certain goods and services).
c) Assess and evaluate the strategic objectives, leadership and governance arrangements specific to public sector organisations as contrasted with private sector.

In the previous article in this series, the issues of the nature of public sector organisations and their stakeholders were raised and discussed. Because of their nature and the ways they are funded, there are major differences between public and private sector organisations.

Strategic objectives

While most private sector organisations are independent in that they are ‘stand alone’ companies answerable to their shareholders, most public sector organisations are part of a larger public sector structure. A defence force, such as an army, cannot act alone and as it sees fit. Rather, it is funded by government and is tightly controlled in what it is asked to do and how it achieves its aims. Likewise, a school in the public sector will rarely have the freedom to do as it likes in terms of what and how it teaches, who it appoints and where it locates itself. In each case, the public sector organisation is helping to achieve and implement a set of higher government policy objectives.
This is not to say that individual public sector organisations do not have strategic objectives, however. Each one must work out how it will achieve what it is asked to do but the autonomy given to individual organisations varies. The ‘three Es’ framework encountered in the previous article is of help in understanding this. Each public sector organisation must be strategically effective in that it must achieve the objectives established for it in carrying out government policy. Because they are funded by public money, they must also be efficient and make the most of whatever resources they are provided with. Finally, they must also be economical in that they must work within specified budget and deliver desired outputs within that budget. Accordingly, there is an emphasis on value for money and service delivery. When public sector organisations are occasionally criticised in the media, it is usually because they have either overspent, underperformed, or both.

Governance arrangements

There is no single way in which public sector organisations are governed. Accountability is gained in part by having a system or reporting and oversight of one body over others. Because there is no market mechanism of monitoring performance (as there is with listed companies, for example), other ways must be found to ensure that organisations achieve the objectives and service delivery targets established for them.
In some cases, then, a head of service or a board of directors must report to an external body of oversight. The oversight body may be a board of governors, a council of reference, a board of trustees, an oversight board or similar. In each case, its role is to hold the management of the service to account for the delivery of the public service and to ensure that the organisation is run for the benefit of the service users. Because public sector organisations are not held to account by shareholders as with business companies, the oversight body is often put in place as a means of holding the management to account. In this respect, oversight bodies are acting in the interests of service funders (usually taxpayers) in making public sector organisations accountable.
Typical (and general) roles of oversight bodies include the following, although their roles do vary substantially depending on jurisdiction and government policy. Firstly, they are there to comply with government rules on whichever public sector governance applies. So a school may have a board of governors in order to comply with the local authority or education department rules on school governance. A hospital’s management may, likewise report to a superordinate body possibly overseeing several other hospitals at the same time.
Second, it is their role to ensure the organisation is well-run and meets the performance targets established for it by higher levels of government. It may receive internal or external audit reports to help achieve this or make visits and other interventions to ensure that the organisation is performing to expectation. Third, the oversight body may be involved in budget negotiations and then in monitoring performance against budget and any number of other agreed financial measures in a similar way that a management accountant might in a conventional business.
Fourth, it is likely to be involved in making senior appointments to the public sector body and in monitoring the performance of management on an ongoing basis. In many cases, boards of governors in schools or universities, for example, have the power to remove a senior manager (perhaps a head teacher) if they believe he or she is underperforming and not delivering the quality of services required. Finally, they are sometimes required to report upwards, perhaps to local or central authorities, on the organisations they have oversight over.
There is an increasing move in some situations to run some public services along similar lines to private companies. This means they may have an executive board and also some non-executive membership on the board also.
d) Discuss and assess the nature of democratic control, political influence and policy implementation in public sector organisations including the contestable nature of public sector policy'
One of the curious and fascinating features about public sector organisations is that there is sometimes a debate about how they should be operated and even whether they should exist at all. Because, in many democratic countries, public policy is debated in the public arena, there is a public debate about how the state sector should be constituted. This includes debates over the size of the state and the role of its institutions.
In a democracy, political parties argue over the nature of public policy and they do so from a particular set of underlying assumptions. Some of these underlying assumptions influence the way they argue for particular outcomes and the way in which they guide a government when they achieve political power. It tends to be the case (with exceptions) that left-leaning governments prefer a larger state sector, with more state spending and more public sector employment, while right-leaning governments prefer more to be achieved in the private sector and less by government.
In addition, changing policy objectives mean that some public sector organisations are required to change over time, both in size and in what they are asked to do. As governments change, some public sector organisations grow in size and become more important, and others become small and less important.
The debate is often intense and enduring. In the case of health services, for example, some believe that health should always be entirely within the public sector and entirely funded by the taxpayer. This means that, for the service user (the patient), everything is free at the point of use. Others strongly believe that this is a misuse of public funds and that people should pay for health services in other ways, such as through an insurance or subscription scheme. Likewise with university education: some believe it should be paid for by the state and others believe that students should pay. In each case, debates are complicated. If there were easy and convincing answers, there would be less debate, but public opinion is split on most areas of public debate and this fuels political debate and, in turn, how public sector organisations are configured in line with particular political influences.
One of the ways in which some countries have restructured their economies in recent years, is through the process of privatisation. This means taking a service that was previously delivered through public sector organisations and then allowing it to be provided by private sector organisations. In some cases, the previous public sector monopoly supplier of a service is transferred into the private sector by making it into a public listed company so that people can buy shares in it. Those in favour of privatisation tend to argue that services can be delivered more efficiently in the private sector where management have a profit motive and competition. This, in turn, delivers better value to the customer.
This process is not without its critics, however. Opponents of privatisation sometimes argue that some strategic services, such as utilities, water, etc, are too important to be subject to the market forces of private enterprise. Others believe, perhaps from a position of personal ideology, that the state should control much more of the economy rather than less. So transport and airlines should also be under state control, perhaps.
Privatised businesses, once transferred from the state sector, are often subject to a great deal of internal change including changes in culture, structure, and governance. Some Paper P1 questions have used privatised businesses as a case study, focusing in particular on issues of changing governance. In any event, however, we can see that changes in opinion influence public sector organisations in many ways.
These changes to the Paper P1 Study Guide represent a broadening of the study of governance into a wider range of organisations than previously. The public sector shares some features of governance with the private sector in terms of the need for strategic leadership, clear thinking and effective strategy implementation. The governance arrangements often differ, however, and it is important to study these in preparation for future Paper P1 exams.
Written by a member of the Paper P1 examining team