A consultation issued by the Director General of Telecommunications on a methodology for measuring consumer savings in telecoms services.

Contents

Executive summary

Chapter 1 - Introduction and Background

Chapter 2 - Determining Consumer Rationality

Chapter 3 - Competitive context

Chapter 4 - Results of application to residential mobile and fixed markets

Chapter 5 - Interpretation and application

Chapter 6 - Consultation

Appendix A - Detailed methodology for assessing savings in the UK consumer mobile market

Appendix B - Methodology for preliminary assessment of savings in the UK residential fixed telecoms market

Appendix C - Summary of questionnaire used in mobile survey, October 2001

Appendix D – Summary of questionnaire used in fixed study, March/April 2003

S1 Well-informed consumers is one of Oftel’s key objectives. This document presents a methodology aimed at measuring progress towards this objective. This methodology will also help Oftel and, going forward, Ofcom to decide whether action is required and, if so, to properly target future regulation in this area.

S2 Well informed consumers means that they are able to exercise choice and receive the services that suit them best at prices they can afford. The focus here is in choosing the right price package which is not the sole consideration in selecting the best deal, but is probably the single most important element.

S3 In its simplest form, the methodology calculates the savings telecoms consumers could make by switching from their current tariff to the cheapest available tariff. The document suggests that the resulting estimate can be used as a proxy measure for the level of useful consumer information in any given market. However the document also suggests that factors such as switching costs and the premiums consumers are willing to spend, either for higher quality service or merely to avoid switching, must also be considered.

S4 The document applies the methodology to the UK consumer mobile market and a segment of the fixed residential market and presents some preliminary results which can be interpreted as showing that, once switching costs and premium levels are considered, the remaining savings available to relevant consumers appear relatively small. However there may be some groups of consumers who could make more significant savings and could possibly benefit from additional information.

S5 Subject to comments from stakeholders Oftel plans to extend the methodology to all relevant markets. Oftel believes that the methodology can be a key tool in helping Oftel and Ofcom determinate a proportionate level of intervention in relation to reducing the level of additional consumer expenditure.

  Chapter 1

Introduction and background

Well informed consumers

1.1 Well informed consumers is a key objective of Oftel’s strategic aim of the best deal for the consumers in terms of choice, quality and value for money.

1.2 Oftel regularly monitors progress towards meeting this objective, primarily through its consumer research programme by measuring, for example, the proportion of consumers aware of the various choices available to them.

1.3 But these measures do not consider the extent to which consumers are losing out through inadequate levels of information. An assessment of consumer detriment is essential in ensuring that future regulation in the consumer information area remains proportionate.

1.4 Such an assessment can assist Oftel in better focussing and prioritising its resources. It is not clear, for example, when the level of consumer information becomes sufficient to effectively stimulate competition. A key question for Oftel to address is when it can stop intervening in this area. This question will also need to be addresses by Ofcom.

1.5 Oftel’s Consumer Information Strategy is designed to ensure that consumer information is capable of changing consumer behaviour and that the effects of any regulatory action can be measured. But the Information Strategy recognises that even in competitive markets, there may be issues that need to be resolved by improving consumer information. For example, a misunderstanding of consumer rights may lead to some level of detriment.

1.6 The OFT Research Paper 11 ‘Consumer Detriment under Conditions of Imperfect Information’ (published 1997) defined three main ways in which consumer detriment may occur

i. consumers may not buy the product or service at the cheapest price available to them - 'pay too much';
ii. consumers may not buy the most appropriate product, given their tastes and preferences - 'buy the wrong product'; and
iii. consumers may purchase a product or service which is not the quality they assumed ex ante - "are let down by product".

1.7 This paper sets out an approach to determining the adequacy of existing consumer information by determining the level of consumer detriment in terms of additional expenditure – type (i). While (ii) and (iii) should be of concern to regulators Oftel believes that the existence of a clear inability to choose appropriate price packages is most likely to require some form of additional regulatory action. Therefore some assessment of whether this is the case is an important consideration in meeting Oftel’s goal of achieving the best possible deal for consumers.

1.8 There are also practical reasons why Oftel has focussed on this particular area. Essentially they reflect the availability of data which assists in quantification. But Oftel is also interested to determine the extent to which stakeholders believe other aspects of consumer detriment in telecoms markets are a concern and whether it is possible to quantify them.

Regulatory Implications

1.9 This approach has a number of regulatory implications and the issues involved require careful consideration. Simple measures of additional expenditure are not realistic measures of detriment simply because price is only one of a complex of factors in making purchasing decisions.

1.10 It is possible to consider other factors underlying consumer purchasing behaviour to deliver a more realistic assessment but a number of further issues need to be borne in mind in assessing the need for regulatory action.

1.11 First, consumer detriment resulting from consumers paying more than the cheapest available price should not be confused with welfare loss associated with non-competitive markets in which prices are above the competitive level. As noted in paragraph 1.5, even in competitive markets, consumers may pay more than the cheapest available price.

1.12 While this may be reflected in higher profits for suppliers it is also possible that high prices or opaque information may restrict consumer demand. It is not clear the extent to which suppliers benefit from consumers being on the wrong tariff or whether, if customers were on a more appropriate tariff, increases in usage would more than offset lower prices. These issues are important considerations in a policy context as in the latter case co-regulation may be an appropriate response.

1.13 Second, while overall there may be a relatively high level of information in any market and a low overall level of additional expenditure, there may be particular groups of consumers who are less informed and who lose out on the cheapest deal as a result. Or indeed there may be a small number of consumers who are paying high prices which contribute to an overall high level of additional expenditure. Where regulatory action is deemed necessary, targeted information initiatives may be the appropriate response.

1.14 Third, regulation must remain proportionate. Additional expenditure may occur through the deliberate action of suppliers to prevent consumers switching to a cheaper alternative. On the other hand additional expenditure may simply be the result of a low level of information. The former example is likely to require a more direct regulatory response.

1.15 Nor is it straightforward to determine the feasibility and cost effectiveness of any improvements to the level of consumer information available. It is difficult to determine the scale of any problem, and therefore the need for regulatory action, without comparable data from other retail markets. But it seems unlikely that all consumers need to be fully informed to benefit from competition.

1.16 Oftel’s consumer profile work also suggests that a significant minority of consumers can be described as active in terms of telecoms purchasing behaviour. In some markets this minority may be sufficient to drive competition, if they are, for example, a particularly profitable group.

1.17 Figure 1.1 provides a summary of the decision process. This document discusses a possible approach to tackling these issues, based on a detailed assessment of the mobile market and a preliminary assessment of a segment of the residential fixed market.

1.18 Oftel has developed the methodology described in this paper with a view to helping it assess the scale of one of the main potential disadvantages suffered by consumers due to factors other than a lack of effective competition. But Oftel is also keen to establish the extent to which the methodology can itself be used as an indicator of effective competition.

1.19 Subject to feedback from stakeholders, Oftel intends to apply the methodology to other telecoms market sectors to allow it to better focus its and Ofcom's work and to continue to look out for any developments in assessing equivalent types and levels of consumer disadvantage in other non-telecoms markets.

1.20 But Oftel is also keen to establish the degree to which stakeholders are concerned about other types of detriment which may arise through imperfect information and, if so, how a similar methodology may be developed to assist its measurement.

Questions

Do stakeholders agree that an assessment of detriment is an appropriate measure of the adequacy of consumer information?

Do stakeholders agree that additional expenditure is the most likely form of detriment arising from imperfect information in telecoms markets?

To what extent do stakeholders believe that there exist other examples of detriment arising from imperfect information which should be a regulatory concern? If so, stakeholders describe whether and how these other kinds of detriment can be measured?

Figure 1.1: Deciding on appropriate level of intervention

  Chapter 2

Determining Consumer Rationality

2.1 Although it is conceptually simple to measure the difference between the actual prices paid and the cheapest price available there are a number of factors to consider before determining the precise level of additional expenditure in a given market.

2.2 In any market consumers will have the choice of a range of prices or tariffs. Differences in price will reflect different user preferences such as quality features or payment mechanisms. Consequently it is unrealistic to expect all consumers to pay the cheapest available tariff.

2.3 Similarly, markets often display elements of voluntary inertia towards migrating to a cheaper alternative product or service. For example, consumers may be less inclined to switch in a general environment of declining prices and/or if expenditure levels are a relatively low proportion of overall income. Many consumers will also factor in search costs in determining whether it is worthwhile switching to a cheaper deal.

2.4 There will also be a natural lag period between price changes and consumer switching whilst consumers consider the merits of different offerings. So instantaneous adjustment to price changes by consumers is unlikely.

2.5 While there are reasons why a consumer would pay something other than the cheapest available price it is not straightforward to measure the value of any benefits obtained from doing so. The OFT paper also acknowledged that it is unrealistic to expect all consumers to pay an optimal price but rather a ‘rational’ price – that is one based on information collected after a rational search process.

2.6 Taking account of these points it is possible to construct an approach to assessing consumer detriment on the basis of estimating levels of additional expenditure, defined as expenditure over and above the optimal amount.

Measurement issues

2.7 As noted in paragraph 2.1 it is straightforward to measure the level of additional expenditure in a given market simply by comparing actual expenditure levels with the minimum prices available for a particular good or service. Actual expenditure levels are easy to establish, either from consumer surveys or industry revenue data. And in general it is also easy to establish the lowest prices available for particular goods or services, through price surveys.

2.8 There are, however, a number of factors which make the calculation of ‘optimal’ telecoms prices less straightforward and a fuller discussion of the relevant issues is presented in Appendix A. Indeed this relative complexity is often cited as a reason for a need for improved consumer information on telecoms tariffs. Nevertheless the principle of comparing actual and optimal prices appears a reasonable starting point for an assessment of consumer detriment.

2.9 As shown in Figure 1.1, a low level of additional expenditure (or a large number of customers paying optimal prices) is likely to be indicative of a high level of consumer information. What is less clear, however, is the extent to which a high level of additional expenditure (or a low number of customers paying optimal prices) is indicative of consumers being poorly informed.

2.10 What is also required is a measure of the extent to which consumers are actually making purchasing decisions on price alone. For example, many consumers will ‘trade-off’ price with specific quality features of individual goods or services. In some cases consumers will rank certain quality factors above all aspects of price. It is necessary to exclude these consumers from any calculation of additional expenditure.

2.11 Even where consumers do value price it is possible that savings may not be achievable given that actual costs can be incurred when switching supplier. This consultation does not intend to address the issue of whether switching costs are fair or reasonable. But the proposed methodology does attempt to consider these costs in the calculation of additional expenditure.

2.12 It is also necessary to consider those factors which although largely independent of the market in question may influence purchasing behaviour within it. It seems likely, for example, that if where the relative level of expenditure in a given service is low the desire to achieve any additional savings will also be low. This is particularly true if additional switching costs are to be incurred in moving to a cheaper service. 

Figure 2.1: Elements of average household expenditure

Source: ONS, Expenditure and Food Survey, 2001-02 © Crown copyright 2003

2.13 Figure 2.1 shows that in total, all fixed and mobile telecoms expenditure represents around 2.5 per cent of overall household expenditure or less than £10 a week on average. Of course, telecoms expenditure is more important for some groups of consumers, in particular low income consumers. But it is interesting to note that telecoms expenditure is less than 4 per cent of total expenditure for even the lowest income decile households.

Assessing the need for regulatory action

2.14 But while it is likely that overall expenditure and income levels are likely to be an important determinant of customers’ likelihood to seek out a cheaper deal it is also important to determine the level to which consumer inertia arises through a lack of information or confusion. For example, consumers may decide that the difficulty in working out the cheapest available service is too great and will settle for ‘any’ service irrespective of price.

2.15 Where such confusion is identified regulators must also consider the extent to which this is the result of deliberate action by suppliers. This may require a regulatory remedy other than improved consumer information. But it also important for regulators to acknowledge that many supplier actions to discourage switching can be regarded as positive effects, reflecting genuine competitive pressures, e.g. by providing a high level of customer service, timely fault repair etc.

2.16 Oftel has used a consumer survey approach to determine consumers attitudes to switching. Oftel accepts that such an approach does have some weaknesses in that survey responses do not necessarily reflect real life experience. For example, while a consumer may suggest in response to a survey question that he or she would be willing to switch for a saving of, say, 10 per cent a saving of 15 per cent might actually be required to encourage the switching to take place. On the other hand, it could be that switching thresholds given in response to consumer surveys, may be artificially high if there is a misconceived perception of switching costs.

2.17 Similarly Oftel is aware of the difficulties in quantifying the precise level of price-quality trade-off but is unaware of any real alternatives to a survey based approach. But Oftel is aware that survey design in this area can be considered an iterative process. For example Oftel has made what it believes to be improvements in question design for its current study in the fixed telecoms market based on its experience during the mobile study carried out in late 2001.

2.18 Notwithstanding potential improvements to questionnaire design, Figure 2.1 develops the process summarised in Figure 1.1 and provides a broad framework for measuring both the number of consumers losing out through a lack of information and the level of savings which could be achieved based on measuring additional expenditures given levels of existing prices and consumption patterns.

2.19 Chapter 4 provides a summary of the practical application of the methodology described in Figure 2.2 to the UK consumer mobile market. To help assess the applicability of its methodology across other telecoms markets Oftel has also undertaken a smaller scale study of a segment of the residential fixed voice telephony market. But while these results can help to focus efforts in the respective markets there is a need for better comparators from other industries to assess the relative position of all telecoms customers.

Questions

Do stakeholders agree that, in principle, it is important to measure the degree to which consumers base their telecoms purchasing decisions on a range of factors other than price?

Do stakeholders support Oftel’s approach to the assessment of rationality? Are there any alternatives? 

Figure 2.2 : Generic approach to assessing available consumer savings

Chapter 3

Competitive context

3.1 Prior to undertaking any assessment of additional expenditure in any market it is important to understand the context of the existing level of competition which is itself likely to have some bearing on consumer behaviour.

3.2 Increased competition in all telecoms markets has led to falling prices for all services and for residential customers prices generally compare favourably with those abroad. This has contributed to increased levels of use and take-up of new services. Overall, consumer satisfaction levels are high. This is important in considering the likely impact of any improved consumer initiatives.

Figure 3.1 Real price changes in fixed and mobile telecoms 1998-2002

3.3 Furthermore, as noted in paragraph 1.16, Oftel's consumer research has identified a range of typical profiles which are important in better understanding consumer behaviour. These suggest that only a proportion of consumers can be considered active participants in telecoms markets. It may be, therefore, that the proportion of consumers who need to be well informed to properly stimulate competition is rather less than total.

3.4 There are also particular characteristics of each of the markets under consideration which need to be borne in mind. 

Mobile

3.5 First, as Oftel recognises, the UK retail mobile market is prospectively competitive. At the simplest level this is demonstrated by the transformation of mobile phones into a mass consumer product. Competition has been the spur for companies to drive down prices, widen their customer base and provide new services which consumers want to buy and use. Each of the existing four UK networks have a broadly equal share of subscribers together with some service provider competition.

3.6 The level of switching in the UK mobile market is significantly greater than that in the fixed market and is broadly comparable to those in gas and electricity. The level of network churn is over five per cent per quarter and there is also a large amount of movement between packages within networks.

3.7 It is also important to remember that in the UK, and other mobile markets, the majority of customers are pre-pay subscribers. For these customers mobile service can be considered a frequent repeat purchase. Also, for these customers there are no contract tie-ins. It can be argued that, together, these factors lead to greater levels of information and switching opportunity.

3.8 The average level of household expenditure on mobile services has increased as penetration levels have increased, although strictly speaking mobile should be seen as an individual rather than a household good. No comparable figures on the proportion of individual expenditure on mobile telephony are available. But it is worth pointing out that data collected from each of the four main mobile network operators suggest that average pre-pay spend (relevant for around two-thirds of all residential mobile users) is around £8.50 per month. This does not appear to be particularly large and the levels of savings available are not likely to be high in monetary terms.

3.9 While post-pay spend levels are considerably higher there are also various non-price factors particular to the mobile market which are likely to influence these consumers’ purchasing behaviour. Oftel research shows that a majority of contract customers consider coverage, line quality, network and customer service, and handset choice important factors in choosing a mobile service. Indeed these factors are also important for a large number of pre-paid consumers. 

Figure 3.2 Factors considered important when purchasing mobile service

Fixed

3.10 The level of competition in the fixed market is somewhat different to that in the mobile market. BT retains the vast majority of residential access lines and also has a large share of all call types. While cable providers have been relatively successful in growing market share in their franchise areas the take-up of indirect access providers by residential consumers is considered by many to be disappointing.

3.11 The lower level of competition in the fixed market relative to the mobile market might lead one to conclude that there is a lower level of information in the fixed market and consequently a greater risk of excess consumer expenditure.

3.12 However it is worth bearing in mind that through a combination of regulation and competition, prices continue to fall. The average proportion of household expenditure on fixed telecoms has remained stable at around 1.5 per cent for over a decade despite a large increase in both voice and data use. The following chart attempts to illustrate how much more consumers are getting for their money by comparing spend at 92/93 usage levels with actual usage levels. 

Figure 3.3 Household expenditure on fixed telecoms services

3.13 Figure 3.3 also shows that a significant proportion of fixed telecoms expenditure is accounted for by line rental. Indeed the picture is rather skewed by the use of an average figure. The proportion of consumers for whom the majority of fixed telephony expenditure is spent on line rental is likely to be close to half. Notwithstanding bundling of other services, currently there is little difference in access costs between alternative providers. Based on the approach adopted here, there is likely to be relatively little additional consumer expenditure on access.

3.14 Most savings are likely to be made in call costs. However the largest differences on call prices exist for international calls which are not relevant for a large proportion of consumers. Oftel research shows, for example, that only a quarter of households make international calls at least once a months.

3.15 Some savings are available for other call types but the level of savings particularly when taken relative to overall call spend data suggest that the incentives for consumer switching are likely to be reduced.

3.16 Oftel continues to promote competition in the fixed telecoms market. Recently its most notable action has been the requirement for BT to provide a wholesale line rental product. Preliminary forecasts suggest that this may have a significant effect in encouraging switching among consumers and appropriately targeted consumer information may have a role to play here.

3.17 But the discussion presented above does seem to suggest that currently there is likely to be a relatively low level of savings available to consumers. And in practice the actual level is a complex interaction between, not just, calls and access prices but other bundled elements such as TV, Internet and, increasingly, non-communications services.

Questions

Do stakeholders agree that prima facie evidence points to a reasonable level of information about tariffs in the consumer fixed and mobile markets?

Do stakeholders agree that the relative level of spend on a good or service is a key determinant of consumers propensity to switch?

Do stakeholders agree that not all consumers need to be fully informed in order for competition to be effective?

Chapter 4

Results of application to residential mobile and fixed markets 

4.1 While Oftel has interest in measuring consumer over-spend in all telecoms markets work to date has concentrated on the mobile market, primarily as a result of the finding in its 2001 mobile market review that lack of consumer awareness of different prices and tariffs was cause for concern. The OFT also identified mobile telephony as one area where consumer over-spend was likely to occur.

4.2 But there are also good practical reasons for testing the methodology in the mobile market. The market structure means that the small number of operators with relatively homogeneous products makes it straightforward to ensure fair and complete coverage of the majority of relevant tariffs in the sector. Oftel’s mobile price monitoring model is also well-established and was straightforward to adapt to use in this area.

4.3 Even given these useful building blocks there remain some complex issues to resolve before producing an accurate assessment of the level of available consumer savings. This complexity has also lead Oftel to expose the methodology to a number of industry and consumer experts prior to formal consultation. Oftel has also applied the methodology to a segment of the fixed telecoms markets to further test its application. Consequently Oftel believes the broad methodology to be robust but is keen to investigate whether there are any additional improvements which can be made.

4.4 However it is important to note that the primary purpose of this section is to present a practical example of how the proposed methodology can be applied. As the discussion below demonstrates the results remain subject to some degree of assumption and approximation. Stakeholders are asked to focus responses primarily on the methodology itself rather than focussing too closely on the results presented here, which, in any case, are made more difficult to interpret in the absence of suitable benchmarks from other industries.

Mobile

Data sources and outline methodology

4.5 In October 2001 Oftel conducted a detailed study of 3000 mobile consumers which asked a wide range of questions about their mobile usage and spend patterns. The survey questionnaire is reproduced at Appendix C.

4.6 The survey questionnaire also asked a range of questions about purchasing behaviour and from these it was possible to identify those customers who considered factors other than price to be important in selecting a mobile service. Respondents were also asked the percentage level of savings which they would require to switch to a cheaper supplier. Together this information was used to determine the proportion of customers who could be considered to be making a rational decision not to be on the cheapest available tariff.

4.7 The usage information was used to construct individual optimal spend estimates tailored to each customer’s call profile. Spend estimates were calculated using an identical method to that used in Oftel’s mobile price monitoring model and international benchmarking work.

4.8 As noted in paragraph 4.4, there remains some degree of approximation when using a survey approach to determining actual consumer spend and usage levels. For example, as described in Appendix A, survey estimates of average pre-pay spend are significantly higher than those derived from data submitted by mobile operators as part of Oftel’s market information. As the vast majority of pre-pay consumers will be residential customers the operator figures are likely to provide a good test of the accuracy of survey estimates of spend and usage

4.9 Appendix A also shows how the discrepancy in consumer and operator spend estimates can in part be explained by the difficulty consumers face in converting an irregular pattern of voucher purchase to a regular monthly spend. Spend estimates for pre-pay customers were thus re-calculated using additional information collected regarding last voucher spend and frequency of purchase.

4.10 Nevertheless there remains some degree of disparity between operator and survey estimates. For example, some customers also reported levels of usage which inferred a spend level outside the range of plausible maximum and minimum estimates generated by the price model. Appendix A also explains how the data were further cleaned prior to analysis.

4.11 Despite these adjustments the spend and usage estimates used in determining the final level of available savings could still be regarded as being subject to a large degree of approximation. Oftel believes, for example that the margin of error attached to actual and optimal spend estimates is at least 50p pence per month due to the rounding of individual spend estimates to the nearest pound. Headline results are presented on this basis but to provide some assessment of the level of confidence which can be attached to the results presented here results are also presented using for a range of other possible margins of error.

Estimating switching costs

4.12 A further consideration, however, is the extent to which switching costs should be taken into account when calculating available savings. While in some cases the costs from switching from one network to another may be zero in many cases there is likely to be a cost incurred, for example through SIM unlocking (the process through which an existing phone becomes useable on another network), number portability or the need to purchase a new handset.

4.13 The approach taken has been to assume that the average cost of switching to a new network is equivalent to an additional £1 a month. This is thought to reasonably reflect the average cost of switching to a new network amortised over the duration of a tariff although results were also calculated on the basis of zero cost and a £2 a month cost. (See Tables A3a and A3b in Appendix A.)

4.14 In practice, however, the issues surrounding handset costs are more complex. In many cases a consumer’s original purchase decision will be made on the basis of the features available on the handset. This should be reflected in the final assessment of available savings.

4.15 In general this issue is relevant primarily for post-pay customers as the choice of pre-pay handset is more limited and pre-pay customers are more concerned about price than other quality features. Additional research conducted by Oftel in October 2002 asked post-pay consumers whether they would switch to a cheaper pre-pay package if they could retain all other aspects of their existing package. Only two thirds of these consumers claimed they would.

4.16 However, it is unlikely that these consumers would be able to retain all aspects of their existing service when switching to pre-pay without some additional cost. It seems likely that suppliers would wish to recoup any handset subsidy for example. Consequently the savings available to these consumers have been estimated by recalculating the optimal pre-pay spend by adding an estimate of the handset subsidy. This is estimated to be £5.94 per month based on an average handset price of £107 and an average duration of 18 months, figures which are consistent with those used in Oftel’s last international benchmarking report.

4.17 For those respondents who claimed they would not switch to pre-pay in any circumstances, Oftel has used the cheapest available post-pay tariff as a more suitable benchmark than the cheapest overall tariff for these customers.

Lag effects

4.18 It must also be recognised that consumers are unlikely to switch immediately as soon as a cheaper tariff becomes available. There is thus likely to be a lag level of additional expenditure in this, or indeed any, market.

4.19 First, some consumers will be prevented from switching to a cheaper tariff if they are tied in to an existing contract. To account for this effect Oftel has assumed that, on average, customers have six months remaining on existing 12 month contracts. Consequently the savings available for these consumers in any given year should be reduced by half. This issue is assumed not to be relevant for pre-pay although in practice it is unrealistic to expect consumers to change packages every time a cheaper one becomes available.

4.20 Indeed generally it is not realistic to expect consumers to move immediately. The main results have assumed that on average it takes consumers one month to switch to a cheaper package with full information, and the estimate of annual savings has been reduced by a twelfth.

4.21 Finally, when the survey was carried out around 10 per cent of customers subscribed to so-called all-in-one packages which involved an up-front payment with the purchase of the handset for an entitlement to a set volume of calls. These types of package are not modelled in the price monitoring work and have now largely been discontinued. For the purposes of this exercise prices for these customers were modelled using pre-pay prices. The relatively small proportion of customers on these packages, however, meant that this assumption had a negligible effect on the overall results.

Summary of Results

4.22 Table 4.1 and Figure 4.2 present summary results. The full range of sensitivity analyses is presented in Appendix A. The estimate for the proportion of customers on precisely the correct tariff is somewhat sensitive to the assumptions regarding the margin of error on the model spend estimates. While this is a useful indicator of the level of consumer awareness in the UK mobile market Oftel believes that the more important result is the proportion of consumers who could make savings given their individual preferences. This result is most sensitive to the assumptions made about switching costs. The shaded area in Table 4.1 presents what Oftel believes to be its best estimate of the level of available consumer savings in the UK mobile market.

4.23 Based on data for October 2001 Oftel estimates around 50 per cent of mobile customers could be considered as being on the cheapest tariff relative to their usage profile.

Table 4.1: Available savings in UK mobile market, showing effects of various assumptions

¹ Total savings based on estimate of 34 million adult mobile subscribers

4.24 Further analysis shows that a further eight per cent of mobile consumers can be considered as making a non-price choice in relation to their decision not to switch. This group includes both those consumers who consider non-price factors to be more important (three per cent) and those who would not switch for any saving (five per cent).

Figure 4.2: Summary results for UK mobile market

4.25 This suggests that any improved consumer price information is likely to benefit at most 42 per cent of all mobile customers. As outlined in Figure 2.1, however, there also exists a group of consumers who even though they consider price to be important and are not on the cheapest deal the costs they attach to switching are greater than the savings available. Notwithstanding the difficulties associated with measuring the actual savings consumers would require to switch, the research suggests that just over half of the remaining group would not switch for the available savings. The remaining 16 per cent of mobile customers (5.3 million) may be able to benefit from improved information.

Post-pay and pre-pay

4.26 Table 4.2 shows how these consumers are split between post-pay and pre-pay. Note that as described in paragraph 4.15 estimates of the proportion of post-pay customers who would switch to pre-pay have been derived from another survey. Technically it is possible to produce individual spend estimates for these customers by matching the two surveys but this is unlikely to add significantly to the precision of the estimates. It is likely, however, that the average spend estimates will be at least slightly different for the two groups of post-pay customers. The pre-pay estimate is unaffected. 

Table 4.2 Savings for pre-pay and post-pay subscribers

4.27 While the group of customers who could make savings is split fairly equally between pre-pay and post-pay subscribers, given the much larger proportion of pre-pay subscribers overall it is clear that that just around 10 per cent of all pre-pay customers could benefit from improved information. This seemingly low figure is not altogether surprising given the different characteristics of pre-pay such as low levels of use and a relatively limited set of tariffs to choose from. These factors coupled with the repeat nature of purchase and lack of contract tie in would seem to suggest a lower likelihood of pre-pay consumers paying large additional amounts for their service.

4.28 Those pre-pay customers who may be able to benefit from improved information spend, on average, just over £10 per month and could save, on average over £3 per month.

4.29 In contrast, around 40 per cent (2.6 million) post-pay customers may be able to benefit from improved information although the precise figure is difficult to quantify given the difficulties in calculating the additional quality premium customers are willing to pay for post-pay packages.

4.30 Through a process of model calculation and plausible reasoning, further outlined in Appendix A Oftel estimates that on average post-pay customers who are interested in making savings spend around £30 per month but could save on average around £9 a month. Taking into account remaining contract tie-in period and lag effects gives an estimated annual saving of £122m.

4.31 Together the savings available to pre-pay and post-pay customers amount to £235 million per annum which represents under five per cent of all revenues from adult mobile customers. In addition, it is important to recognise that the level of savings available to the remaining customers will still be affected by factors other than price, for example, preferences for post- or pre-pay packages.

4.32 In addition it appears that there is little evidence to point to the group who could possibly benefit from improved information being concentrated in a particular demographic profile. There is some evidence that men, those aged 45-64, and higher income households are more likely to be able to realise their required savings there is no real evidence that particularly vulnerable groups, such as lower income households, appear to be disproportionately affected by a lack of useful information.

Table 4.3 Profile of group who could make savings compared to profile of population

Fixed

4.33 In order to inform the consultation on general methodology Oftel commissioned a small-scale study in January 2003 to provide a preliminary estimate of the level of savings available in the fixed market. Oftel has commissioned a more detailed survey on the fixed market, the results of which will be used in conjunction with response to this consultation, to inform a statement on how Oftel will apply the methodology in the future.

4.34 It is important to note that many of the issues in the fixed market are rather more complex than in the mobile market which make it more difficult to model optimal price estimates. For example:

• Non-universal coverage of all providers (cable operators);
• Bundling of services (Internet, TV, broadband);
• Additional lines; and
• Indirect access: mix and match options for different call types and destinations.

4.35 Given the complexity of these issues and the limited scope of the preliminary survey it has not been possible to properly consider all of these factors and the results can be considered purely indicative at this stage.

4.36 To remove some of the uncertainty the analysis has focussed on calculating a level of savings for a subset of customers with relatively simple patterns of fixed telecoms usage. ie single line homes without Internet and (non-cable) pay-TV. The survey showed that this subset constitutes around 10.8 million homes, just under half (47 per cent) of all fixed households and the spend of this group represents around £3.1bn per year or around 40 per cent fixed telephony spend.

4.37 In addition, this group of households is likely to be disproportionately represented by lower income households who could be considered more ‘at risk’ from a lack of adequate consumer information. The analysis can also be considered more directly comparable to the mobile results, focussing solely on issues of fixed telephony access and calls being largely independent of bundled services (TV, Internet) effects. On average, these customers make relatively few calls and less than a quarter make international calls more than once a month.

4.38 The results should be considered subject to a greater degree of approximation than the mobile results due as quarterly spend estimates were collected in £10 bands only. In addition less detailed information was collected on usage and so the optimal spend estimates will also be more approximate. On the other hand, comparisons between market research and market information data suggest that consumers are better able to provide more accurate fixed spend information than, say, pre-pay mobile expenditure. More precise information is being collected in the current survey.

4.39 Finally due to the huge number of indirect access offers available these were not modelled individually. Instead, an estimated spend figure was calculated using by applying a percentage discount to BT’s standard tariff which was thought to be representative of the typical level of savings. These assumptions are outlined in Appendix B but a key point to note is that, generally, the subset of consumers considered make relatively few calls, particularly to international destinations, and the assumptions are not thought to have a material effect on the results.

4.40 In addition, as for the mobile analysis, the key result of the proportion of consumers who could make savings and would consider switching is generally independent of the assumptions.

4.41 In summary, notwithstanding the greater level of assumption the results appear to be broadly similar to those for mobile.

• Between 30-50 per cent of fixed households appear to be on the cheapest deal for their particular usage pattern;
• Of the remainder the majority could not realise their required level of savings leaving between 14-20 per cent who may benefit from improved information; and
• In total these households could save around £20 per quarter; this is equivalent to around £150m per annum or about five per cent of the spend of the analysis group (single line homes without Internet and (non-cable) pay-TV).

4.42 While the five per cent savings level is similar to the equivalent mobile figure it is worth noting that the subset of fixed telephony consumers studied here is rather less advanced in its telecoms use. It is possible that the greater level of telecoms use in the other half of the population may mean that there are greater savings available there.

4.43 On the other hand, a large proportion of the mobile savings figure can be explained by large differences in post-pay and pre-pay prices. With fixed telecoms a large proportion of every consumer’s bill is the access charge which is broadly similar for BT and cable and so the overall bill variation is rather less than for mobile.

4.44 On this basis the results seem plausible but it is important to reiterate that the results presented here are very much preliminary findings and there a number of factors which have not been considered.

4.45 This analysis does not attempt to measure the quality premium which fixed telecoms users place on their existing service. Nor does it attempt to quantify the monetary costs attached to switching such as connection charges. Similarly, the effects of contract tie-in periods and the lag effects of consumers not immediately switching to a cheaper tariff were not measured. Each of these factors will lower the actual level of savings available to fixed consumers.

4.46 The relatively small sample size also means that it is not possible to make any firm assessment of the demographic profile of the group who may be able to benefit from additional information. But, as shown in Table B1, Appendix B, the study group (‘basic’ telephone users) is more concentrated among older, lower income households.

4.47 The limited scope of the January survey means that Oftel was not able to provide a full assessment of these effects although these issues will be dealt with in the more detailed survey and discussed in the final statement on the methodology later in the year.

Questions

Do stakeholders have any practical suggestions for improving the precision of the optimal spend estimate?

Is the way Oftel has taken into account switching costs and quality/inertia premium reasonable?

Are the results of the application of the methodology a) plausible, b) in line with expectations?

Chapter 5

Interpretation and application

5.1 At a broad level the findings of both the mobile and fixed analyses could be interpreted as showing that consumers are relatively well informed. Around half of all consumers in both markets appear to be paying close to the cheapest available price.

5.2 While it is not possible to determine how many of these consumers were on the ‘correct’ tariff through well-informed choice and how many by chance it is straightforward to demonstrate that the probability 50 per cent of customers selecting the correct option by chance is negligibly small. For example, at the simplest level in the mobile market, a choice of four networks and a post and pre-pay option gives each customer a one in eight chance of selecting the correct tariff. This could be regarded as consistent with a reasonably high level of consumer information.

5.3 In addition, there is evidence that the majority of the remaining customers in both markets appear to be making a rational choice in their decision not to migrate to a cheaper package.

5.4 Furthermore, the results suggest that while the level of total savings available to those customers who could make savings is high in aggregate terms, it is small in terms of overall household expenditure. Indeed, this could be a factor in determining why the average ‘switching premium’ appears to be relatively high.

5.5 Also, as noted in paragraph 4.26 consumers will not immediately migrate to a cheaper offer as soon as one becomes available. There will always be some degree of lag. Similarly, price differences will be present in any competitive market and some of the apparent level of available savings will reflect quality differentials between networks or suppliers.

5.6 These conclusions might lead to a conclusion that there is little need for additional consumer information. But it is possible to take an alternative view.

5.7 First the available level of savings is high in monetary terms. For the mobile market the figure is £235m. The savings available in the segment of fixed market studied is similar as a proportion of overall revenues (five per cent) which might suggest a total level of savings of some £400m if grossed to the total population. This might suggest some level of excess operator profit and could lead to overall welfare loss if excessive pricing was restricting demand.

5.8 It is also possible that while the proportion of customers who appear to be suffering some level of detriment through inadequate information is relatively low, these customers share similar demographic characteristics. This would lead to more concern if such customers could be identified as a particularly ‘vulnerable’, for example, low-income group.

5.9 While this does not appear to be the case in the mobile analysis it is worth noting that any concentration of detriment among a particular group could facilitate a properly targeted approach to new information initiatives which could help deliver consumer benefits at a relatively small cost.

5.10 On a more technical level, it should be noted that the results presented in Chapter 4 were based on consumers switching to the cheapest deal available on any network. But it is possible that some consumers may be able to make some level of savings, if not the full amount, by remaining with their existing supplier. This is of interest as one possible regulatory solution to reducing the level of overall expenditure would be to ensure that suppliers took steps to ensure that all of their customers were on the cheapest available tariff.

5.11 The full extent of the level of savings which consumers could make without switching supplier is difficult to measure. For example, in the mobile market, most low use customers on post-pay packages could make significant savings by switching to pre-pay but some consumers may still prefer the convenience of post-pay even if the savings are pointed out to them. And there is no incentive for suppliers to move customers from post- to pre- pay as they lose the advantage of customer tie-in. Consequently it is likely that suppliers could not offer existing pre-pay tariffs to existing post-pay customers without some attempt to recoup the handset subsidy generally given with post-pay packages.

5.12 In any case it is difficult to recommend any ‘supplier optimisation’ on the result of a snapshot survey. Suppliers will require a longer time period over which to assess the precise nature of a customer’s calling pattern before they can decide on a more appropriate tariff. Indeed, to properly validate the methodology and the results it will be necessary to carry out some assessment of additional expenditure over time.

5.13 A related point is that some additional expenditure may arise where changes to consumers’ typical usage patterns result in unexpectedly high bills. Improved consumer information could be used to minimise this risk, although it is less clear how the total level of additional expenditure arising from such events can be measured without continuous monitoring.

Establishing a benchmark

5.14 On balance Oftel believes that the results from the fixed and mobile analyses show that, generally, there is a substantial level of consumer understanding in relation to tariffs. While there may be pockets of consumers who are less aware, the overall level of awareness does not appear to be at a sufficiently low level to materially affect the behaviour of a majority of customers. This conclusion, however, can only be considered tentative until recognised benchmarks from other industries become available.

5.15 In addition it is likely that a traditional cost-benefit analysis which considers the costs to Oftel and/or suppliers of improved information initiatives against the reduction in savings made by consumers as a result is always likely to demonstrate the need for additional action. But this approach has a number of flaws.

5.16 First, it can be argued that a proper regulatory cost-benefit analysis should consider overall welfare loss rather than pure consumer detriment. This is important when prioritising regulatory objectives.

5.17 Second, it is rather harder to target information initiatives effectively to deliver all of the identified benefits. It is probable that some law of diminishing returns applies in the case of consumer information ie not all savings will be realised immediately and that progressively greater targeting initiatives will be required to ensure that all additional expenditure is removed. The level of consumer awareness in any market is also likely to increase naturally in any case. So a portion of the apparent benefit cannot be attributed directly to any regulatory intervention.

5.18 Consider, for example, a more direct regulatory intervention such as a price cap. While it is probable that the regulatory resource required to determine the appropriate level of a cap is likely to be higher than developing a consumer information campaign, the actual costs in both cases are likely to be significantly lower than the benefits. Yet as noted in the previous paragraph, the ability of a consumer information campaign to deliver all of the required benefits is limited. This effect is illustrated in the following diagram.

Figure 5.1 Comparative effects of price cap regulation and consumer information initiatives

5.19 Given that Oftel does not have - and Ofcom will not have - unlimited resource, what is required is a formal mechanism to allow it to properly set priorities and better focus regulation. Oftel proposes that the methodology outlined in this document is an appropriate tool to assist it in meeting this goal.

5.20 Although the main use of this methodology is likely to be in helping to better target future regulation Oftel is also keen to explore the extent to which the methodology can be used as an indicator of competition. For example, given suitable benchmarks, a ‘low’ level of additional expenditure may be indicative of a high level of consumer information which in turn could be taken to be evidence of effective competition.

5.21 How far the methodology can actually be used in this context does, however, appear limited given the preliminary results presented in Chapter 4. Estimates of additional expenditure and the proportion of customers on the correct tariff from the fixed and mobile are broadly similar yet the extent of competition is markedly different.

5.22 In summary, the issues raised here are extremely complex and interpretation is further impeded by the absence of suitable comparators from other industries. It is probable that additional expenditure occurs in other industries – both regulated and otherwise. In order to ensure that any additional intervention on the basis of an identified level of available consumer savings remains proportionate Oftel will monitor research in other industries.

5.23 In the meantime Oftel is clear that the methodology outlined here does have a role in helping its understanding of consumer behaviour and allowing it to better dimension the scale of any problems in the consumer information field. It is important to identify if consumers are in fact losing out or, conversely, to what extent they are making well informed choices based on factors other than price. This work will also have a key role in allowing Oftel to better target future resource in its consumer information area.

5.24 There are also clear links with the methodology and the principles outlined in Oftel’s consumer protection policy review guidelines, and more generally, in the regulatory option appraisal process.

5.25 Oftel proposes that the future application of this methodology is primarily in determining the need for improved information in markets where there is already a degree of competition. It is likely that the benefits of information in such markets are likely to be less than for markets where competition is not yet effective. But it is also possible to use the methodology to target groups of consumers who are, for whatever reason, not benefiting fully from competition. In summary, therefore, Oftel believes that the methodology will be an important tool in prioritising future regulatory action. 

Figure 5.2: Possible application

Questions

Do stakeholders agree with Oftel’s assessment that the general level of savings available in fixed and mobile markets does not give cause for concern?

Do stakeholders agree that the methodology proposed will be best used in improving the targeting of future information initiatives?

Are there other markets in which stakeholders believe Oftel should attempt to measure the level of savings available? Do stakeholders foresee any practical difficulties in doing so?

Can stakeholders provide any suitable benchmarks from other industries which can assist Oftel in determining whether the level of consumer detriment in telecoms markets is sufficiently high to justify regulatory intervention?

Do stakeholders believe that the level of additional expenditure in any market can be used as an indicator of effective competition?

Chapter 6

Consultation

How and when to comment

6.1 Oftel invites comments from interested parties on the contents of this consultation document by 30 June 2003. Oftel is interested in responses from all stakeholders on the subject areas discussed in this document. Oftel is particularly keen to learn of any similar research in other industries which will assist it in developing a suitable benchmark for telecoms service. Oftel would also welcome any additional data which suppliers or others may be able to supply which would enable it to better quantify the level of savings available to consumers.

6.2 Comments on the proposals should be made in writing or in electronic form and sent to:

Kenny Osborne

Oftel
50 Ludgate Hill
London