| Conflicts in data collection for global investment appraisal: A case study in telecoms |
I.Executive Summary
Strategic finance decision making theories like agency conflict, moral hazard and information asymmetry have commonly been examined within the realms of external markets, capital structure, and options pricing. However they are equally, if not more, applicable to the dynamics of every day decision making processes in multinational companies; especially in those flatter organisational structures with hub and spoke configurations.The data collected to calculate return on investment is often subject to a variety of conflicts, but the quality of this data can be easily improved – resulting in a significant impact on the bottom line - by following some simple countermeasures.
II.Investment Appraisal applied within the telecoms and technology
Within the telecoms and technology space, profitable opportunities come in the guise of two types:
- Revenue generating
- Cost efficiency
Whilst revenue generating propositions will concentrate on how profitable changes to existing channel mixes, products, services, tariffs and network capabilities will be, a cost efficiency proposition looks to compare existing implementations with more cost effective solutions. These can examine anything from customer network rationalisation to internal IT systems and supply chain operations. Many larger organisations will be able to take advantage of economies of scale either by consolidating technology and network and rationalising associated processes or by leveraging their buyer power to negotiate better deals with suppliers for promises of larger volumes of traffic. Caveat venditor!
Although revenue generating propositions are certainly eligible for central rationalisation – for example, a volume based contract for outsourced mobile content delivery, much of the accountability for revenue generation resides within the local operating company. Revenue generating propositions tend to be driven by local market conditions and local subsidiary initiatives. These are therefore less common and can less effectively be driven from the centre[1] than those focusing on cost efficiency. This article will use an example of a global cost efficiency initiative to illustrate conflicts in data collection even though the behavioural principles described below can also apply to revenue generating propositions.
III.Case Study: “PhoneHome’s next generation voice mail”
As telecoms and technology sectors converge, so back end systems become more and more capable of supporting additional services. Operators who started by providing voice services, now provide access to data services ranging from video streaming to internet browsing and multi-media messaging (MMS).
In our example multinational operator “PhoneHome” is examining the possibility of investing in a global platform situated in Eastern Europe that will host and store voice mail, email and video mail. Most of its current system can only support voice mail and is soon due to be replaced, although three of its ten subsidiaries already have invested in separate video mail hosting capabilities.
The scenario examined is the following:
All cost efficiency propositions should be compared to a business as usual (BaU) baseline (also known as no-go or as-is scenario) as their success can only be measured against a “business as usual” baseline resulting in a comparative variance in Net Present Value impact. As such, the reliability of the results is largely dependant on the quality of the data which contribute to the compilation of the baseline. In our example local subsidiaries are required to submit the following information:
- Current & forecast voice, e- and video mail volume
- Current & forecast operating expenditure
- Current & forecast capital expenditure with predicted end of life for systems
Decision makers expect that with the new global platform there will be a reduction in operating costs mainly through headcount reduction and partially through maintenance and support as well as a savings in capex avoidance through consolidation of the technology and discounts with the supplier. There may also be an increase in revenue due to the new services available.
IV.Agency conflict between global headquarters and local subsidiaries
Local subsidiaries are held accountable for their own financial performance. Senior management is responsible for driving performance, increasing revenues and decreasing costs where possible. Indeed most of them are extrinsically incentivised by bonus payouts linked to performance to align their interests with that of the company’s. Their financial statements are published to their own markets and especially where there is joint shareholding, local filing and reporting is very important. This accountability and alignment is beneficial as a general rule but creates a conflict of interest between global headquarters and local subsidiaries when the local subsidiary perceives that it has divergent objectives and loss of control or accountability over decision making.In this example the conflict will occur over the following elements:
- Centrally decided capital expenditure for global systems
- Centrally decided Opex or depreciation recharge to subsidiaries for global systems
- Associated implementation/hidden or unacknowledged running costs for subsidiaries
- Required reduction in workforce in local subsidiaries
- Lack of foresight on overall financial impact
- Centrally preferred vendors and/or technology perceived as incompatible with local market
- Quality of customer service provision associated with replacement systems
- Write off costs for current local assets
- Regulations for depreciation recharge or foreign owned assets generating local services
- Responsibility for local capacity requirements; current and future
V.Explicit Moral hazard in data collection
Given this agency conflict present between Global and Local parties due to disparate objectives and different risk aversion profiles regarding return on investment, submission of data may well be undermined by moral hazard.This means that local subsidiaries having more information about their data and more knowledge about its strategic intentions may have the incentive to submit an incorrect assessment of its current/forecast volumes and operating costs. Where the local subsidiary decides that they do not want to opt for the global solution, the submissions will be characterised by:
- Underestimation of relevant operations costs for voice mail which will lead to a highly competitive Business as Usual scenario
- Overestimation of volume data which will lead to an inflated cost global solution assessment in the “New” scenario
- Overestimation of existing local capital expenditure and or extended end of life dates which will lead to artificially high write-off values in the “New” scenario
Moral hazard can lead to the inverse data submission where the local subsidiary decides that it is in their interests to transfer responsibility for a particular service to central management for reasons other than purely financial. In this example it may occur where local management prefers to avoid full responsibilities for the revenue generated by voice, e- and video mail and would take the opportunity to shift blame to the central function for a decline in profits. However this case is less common since most organisations prefer to retain control over their Profit and Loss account.
VI.General Information Asymmetry in data collection
In many cases lack of alignment between technical and financial stakeholders in local subsidiaries means although migration to newer local voice mail systems may be planned for a certain year by technical departments, the financial forecasts do not reflect this thinking. Because the financial function is commonly regarded as a support function, they tend to be the last to know about capacity planning and may unknowingly attribute common depreciation schedules to assets which do not correspond to their correct economic life.
Local submissions may be characterised therefore by disparate financial and technical forecasts. Since the technical department forecasts on the basis of volume and obsolescence and financial teams forecast on the basis of flat or cost plus/target expenditure, the two will not be aligned unless the two teams have already worked together.
Due to the fact that the global business case tends to be built in a substantial part, by taking the desires of the local parties into consideration as well as trusting that those concerned will have performed the necessary analyses in order to optimize their migration time and improve their Opex position, the scenario planning is subject not only to the moral hazard described above but also to a fundamental information asymmetry within the local entity.
Yet another effect of information asymmetry concerns reduction in headcount which occurs between global and local entities. A common error in multinationals occurs around a lack of knowledge regarding local labour laws. It is often assumed that human resources are expendable and can be restructured if necessary for cost efficiency purposes. This is rarely the case especially in countries where union power is high. This will lead to an underestimation in redundancy costs and/or overestimation in headcount savings in the “New” scenario.
Discrepancies in language (where terms are not exactly translatable or are used to defined different accounts and sub-accounts) and different data warehousing capabilities may simply mean that the data requested to assess the volumes and or attributable costs for certain services is not available. In the worst case, these cultural differences may be used by either party to intentionally misinform.
VI.Financial inaccuracies in data collection
And last but not least. In many cases a poor understanding of basic management accounting and decision theory will lead the contributors to misstate the actual costs attributable to a particular platform. A lack of knowledge concerning marginal, absorbed or activity based methodologies leads to the partial declaration of allocable or relevant costs for technologies resulting in an inaccurate estimation of replacement systems and business as usual running costs.
VII.5 recommendations to combat these problems
Though it is acknowledged that an appraisal is a pure simulation of future discounted Cashflows and by no means a guarantee of financial outcome, the forces undermining the integrity of the composite data, are almost enough to discourage even the most ardent of financial modellers. If the outcome is simply an estimate, what purpose does it serve if even the input data is not accurate? Whilst no solution is foolproof, there are several measures that one can take to counteract the effects of inaccurate data.
- Investment Appraisal analysis
Remember that the purpose of the appraisal is not the production of an accurate NPV since such an event will never occur! Its purpose is to understand the likelihood of the estimated NPV and the risks and consequences of not attaining this. It is a fallacy widely held that the calculation of an NPV (or IRR) is the last step in an appraisal. Whilst a positive NPV will add value to the company, the accuracy of such estimation in a technologically complex multinational is questionable. Whilst every effort should be made to calculate an accurate result, it is more important to build a good model which can test the result for robustness. Both sensitivity analyses and cost structure analyses are of crucial importance in highlighting break even points and influential cost drivers. If you know these before launch, then you will be prompted to question the data accuracy of the stronger drivers in advance.
- Ratio analysis
When comparing the data of 10 different operating companies for the same service, it presents an opportunity to do a little simple ratio analysis. If operator A is the same size as B, their volumes and costs must also be comparable. If not, there is cause for worry. Horizontal (like for like) comparisons are useful to benchmark one against the other. Similarly vertical ratio analysis (asset efficiency – volume over capex) will highlight the more unlikely scenarios. Is it really possible that Operator C is supporting large volumes of traffic at very little cost? If they are – perhaps they should teach the rest of the company!
- Restructuring of executive remuneration
Probably beyond the scope of the strategic finance team, but certainly worth a recommendation! Where managers’ interests are aligned only with local profit and loss statements, there will never be any incentive for them to take responsibility for the group P&L. For those propositions which take power and control away from local management, organisations should consider additional alignment with those accounts which consolidate into the group statements. For example if bonuses were aligned with asset turnover ratios as well as operating costs, then the onus would be on managers to opt for economies of scale measures whilst leaving them to concentrate on better promoting these centrally provided services in their local market.
- Aligning team communication
Data collection from operating companies needs to be signed off by both financial and technical contributors. Although tradition states that written sign off is best, often getting all parties on the phone to discuss the discrepancies in financial forecasts versus traffic volumes eliminates much of the original disparity. This information asymmetry is not intentional and usually is simply a result of lack of interdepartmental communication.On the same calls or separately you can take the opportunity to examine the financial calculation behind the costs to assess which costing methodologies have been used.
- Building proxies
If in the final analysis, the data is not forthcoming or there are too many inconsistencies, it is always possible to use weighted averages in order to approximate the necessary data. Many multinationals, comprised of small, medium and large subsidiaries, can easily use one of each to represent others which will allow a speedier and more comprehensive data collection from fewer counterparts. This also may encourage a more accurate submission from a subsidiary if they are aware that a proxy developed by the global entity will be used to represent them and their needs. And as all appraisals are self defeating if they take too much time to develop, using proxies ensures a quicker implementation.Indeed if all the data is subject to the sensitivity and cost structure analyses that are stipulated in recommendation number 1, a proxy may be quite sufficient to make a reasonable forecast, thus achieving the ultimate goal – a decision on whether or not to implement!
This article builds on thinking from Ackerlof, Spence & Stiglitz on Information Asymmetry.
[1] Reasons not examined in this article |
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