Operations leaders often struggle to present the full strategic values of their operating model alternatives to their respective CXOs. This challenge is common across service and support operations, from banking processing to finance and accounting and beyond. Assessing advanced operations’ roles solely through the lens of baseline-cost reductions biases CEOs’ enterprise choices, since the choice of alternatives benefits from a more sophisticated value-modeling approach that accounts for the financial impact of execution uncertainty and market volatility. The same challenge exists when choosing between alternative organizational models, such as internal shared services, BPO, hybrid and global business services. This paper provides executives with the analytics to robustly estimate the full values of these models (taking into account the financial significance of risk, time, and additional quantifiable factors) and to properly evaluate alternative organizational models.
Many leaders struggle to assess and present the value of strategic transformations of their operations. Within functions like financial planning and analysis, industrial operations, acquisitions and spinoffs, where sophisticated business case modeling is prevalent, data benchmarks are easily accessible and strategy consultants are readily available. In these cases, sophisticated business cases are routinely built by specialized analysts (including very experienced top managers) and consumed by senior management.
Service operations, on the other hand, be they the core services of a bank, the services of a finance and accounting function, or the services of a sales or even an R&D organization, often struggle to produce the same CEO-grade strategy materials and don’t account for the full values and risks of their strategic options.
The end result is too often the creation of documents that include only transactional cost reductions, and even these are often represented in only a partial way, with a bias towards aspects that are well known. The consequence is that CEO and the board are likely to discount the strategic values of these plans.
Building a rigorous business case requires two steps
These challenges are surmountable, but they require greater combined operational and financial efforts than they typically attract. Two steps can help operational leaders do justice to their plans and retain the attention of the top management.
- First, determine the Total Cost of Ownership (TCO). Understand the cost structure of advanced operations in detail and map the drivers of these cost structures in order to understand how to harness the respective economics and to quantify the risk of falling short of financial targets.
- Second,clarify the full value envelope, including costs that occur in the event of volatility or enterprise discontinuities, such as fast growth.
In both steps, the impact of alternative operating structures on these drivers must be rigorously modeled. This document provides the analytical tools to do so.
Step 1: What’s the TC O? Understand the cost structure of advanced operations in detail
Map out cost drivers to understand how to harness the respective economics to forecast financial outcomes more precisely.
a). The determinants of a real-world shared organization’s cost structure
It is commonly understood that a business case requires an analysis of the initial setup, ongoing operations, and, potentially, wind-up options. What is not as well understood is the set of economic levers that determines the financial outcomes of each of those phases. For example, while the “production” cost at scale may be similar across different scenarios, significant variability is often observed in the initial phase due to significant variance in agent productivity – variance that mature operations, staffed by experienced operators, can gradually control. The speed of reduction of this variance is a large determinant of the spread in financial outcomes and needs to be accounted for, starting with an understanding of what factors (e.g., waste and rework) provoke the variance in the first place. Consequently, the considerations on the next pages, which variably impact the inception, steady-state, and model windup/change (e.g., through sale or merger) of such operations, should be modeled accurately for each of these stages.
As shown in Figure 1, two sets of levers exist. Very often, only the first lever (or only a part of it – the direct FTE cost of the associates) is taken fully into account. However, in our experience, much of the variance in operation cost effectiveness is explained by the other levers and their variances.
The four main cost categories (i.e., FTE, Infra, IT, and G&A) must be further broken down for us to better understand their dynamics, the levers that can influence them, and the design principles that an organization may or may not be able to respect (each described in the examples of Figure 2).
The inability to pull some of those levers – whether due to scale, to process optimization capabilities, or to access to cost-effective pools – can radically alter these costs. The team responsible for the business case should be able to model the effects of some of the key variables, as well as the impact of a failure to achieve them.
To clarify why such an analysis is required, the example in Figure 3 illustrates the magnitude of a possible impact. Understanding the effect of scale, for example, is often something that individual companies struggle with, unless they have significant experience in transforming and sharing operations. If the requisite scale is not achieved because, for instance, the lines-of-business units don’t release the necessary scope or because of limited process standardization, even a large organization’s cost structure might behave like a collection of small companies and the target cost by a significant amount.
To provide practical modeling guidance, the following chart, Figure 4, gives an approximate indication of the materiality of each lever and shows what enhances our ability to harness them. For example, some of the levers and respective sub-components, such as bench levels, benefit greatly from economies of scale or from increased scope, which enable, for example, the pooling of resources and the spreading of fixed costs. Other levers, such as associate compensation, respond well to global delivery. Failing the ability to use these levers, process improvements can still generate benefits; however, these improvements typically have a greater impact when combined with other levers.
Shared-service centers (SSC), business process outsourcing (BPO), and modern global business service (GBS) structures can impact these cost structures with varying degrees of certainty, and the business cases for alternatives must be built appropriately. In other words, it is necessary to account for the different likely financial risk profiles of each of these structures and to ensure very robust modeling of the alternatives, since the risk is borne by the client organization.
b). The cost effectiveness of different models rests on their respective abilities to harness the drivers of cost
The theoretical outcomes of the various options (SSC, BPO and GBS – typically with hybrid models) depend mainly on three things: The size that the client’s operations can reach by themselves for the functions in scope; the client’s ability to optimize processes; and the client’s access to labor pools that that it can realistically obtain and maintain. Clients that score well and feel that they have little risk in execution are the best candidates to optimize their financial profiles by retaining greater scope in-house. While the results are highly situational, a more granular analysis shows that high-level estimates can be readily made. Figure 5 shows the design choices of different organizational models, as well as their typical ability to drive results.
More sophisticated shared organizations, which are often structured as GBS (in which a part of the scope is typically outsourced) have the potential to deliver more material results. These considerations must be taken into account by those responsible for the business case and reflected in sensitivity analyses.
From the analysis above, it is clear why the practical result depends on the theoretical “economic fundamentals” of each alternative model (which are sometime reflected in business cases), but also, importantly, on the sheer execution excellence applied to these fundamentals. Creating these organizational constructs is a nontrivial implementation effort, and a robust business case must take this aspect into account when performing sensitivity analyses for various alternatives. The following are considerations that aren’t often modeled appropriately in business cases.
c). Accounting for real-world leakage and assessing possible deviations from the plan
Attribute a value to uncertainty. While proper investment valuation takes uncertainty into account and discounts outcomes accordingly, business cases for shared services and other operational constructs do so very rarely. This is a mistake because the alternative options carry different levels of financial risk, and management should be given this information as part of its decision-making process. Specifically, the parameters described in the first section of this paper have material financial impacts, but the ability of an organization’s business planners to estimate them well varies significantly. This is especially true when estimating risks for internal shared services, in which all of the modeling, as well as the risk of deviation from the financial plan, falls completely on the shoulders of the client. Specifically, the typical budgeting and financial controls for internal shared services often don’t act as good stabilizers for initial budget overruns (an effect known as “burning through the money”). Instead, they tend to incentivize underinvestment (e.g., in talent, infrastructure) in order to keep short-term costs under control, which, in turn, may perpetuate cost issues and lead to vicious circles. The business case for top management should explicitly reflect a wider range of possible outcomes, since the expected results may be more “noisy” 1 than those of process outsourcing (in which the modeling is based on systematic experience and observations and the risk is borne more fully by the provider).
Understand what degree of financial risk your company assumes. The possibility of a miscalculation is significant, and not just when your organization is new to these endeavors. Importantly, the probability of a mistake - and the severity of its consequences - varies widely:
1. In the case of a BPO agreement, the consequences will be less severe if the service provider has done appropriate due diligence and if the contract protects the buyer from part or all of the price level pressure that may derive from a cost calculation that is revised upwards. That said, outsourcing relationships in which the cost has been underestimated do exist and are potential sources of instability (hence, the importance of ensuring that the service provider has enough data points to make an accurate assessment of the outsourced organization and to enable an estimate of the cost of the retained organization).
2. In an in-house shared service transformation, the benchmark data available to the modelers are typically sparse and not easy to relate to the new situation. For example, how should a company model the actual cost of hiring people at scale in an offshore location? Moreover, what will the actual level of attrition be for key employees when the job market becomes more competitive, given the actual attractiveness of the client’s brand and the actual opportunities for job advancement in the actual scope of the captive?
The sensitivity analysis of the business case needs to account for the differential risks of the various alternatives: A BPO provider will often assume the most risk, a mature shared service organization will be able to estimate and manage these variables to a certain extent, and a new team in a firm that is new to internal shared services will have the highest level of risk.
Very often, these analyses are simply not performed – or, if they are, the potential deviation is applied uniformly across alternatives. Both of these approaches are inappropriate.
Avoid blind spots. Business cases often only use known costs, without seeking a proper understanding of all the related costs that should be included in the new organizational structure. Some such costs may be embedded – sometime invisibly – in other G&A or business-line cost structures. There is frequently little clarity regarding how those costs may vary in the future, whether in the “heat of the transformation battle,” during steady-state operations that expose the business to pressures due to new environmental conditions (e.g., offshore labor markets), or when the business is affected by new internal ecosystem requests (e.g., governance, service level agreements, customer satisfaction, etc.).
d). Benchmark results confirm the model
It will not come as a surprise that benchmark studies2 demonstrate that the levels of these cost categories vary significantly between best-in-class and “median” organizations – and, most likely, so do the variances of the original business cases.
The analysis uses historical data for rule-based decision-making (of the sort that is often considered a candidate for in-house operations). Even in these situations, the best captives can have, for example, a lower fully loaded cost per FTE than that of the best BPO providers;3 however, the median captive is roughly 40% more expensive than the median service provider.
The same pattern is visible when comparing the significant determinants of the cost structure, such as the number of support staff per productive FTE, the facilities cost, or the spare capacity for business continuity.
In general, service providers and the very best captives enjoy structural advantages, such as better opportunities to spread fixed costs, lower costs of acquisition of resources and greater attention to indirect costs and process improvements. In addition, several unquantifiable aspects negatively impact the business case for the worst performing captives over longer time horizons. Examples include the opportunity cost of management attention to remote operations; fewer career development opportunities for staff (leading to higher retention costs); and a limited ability to develop leading practice thinking. Clearly, the best in-house captives are great performers, and the probability of reaching such performance should be accounted for in the related business case.
Step 2: Clarify the full value envelope
Today, most business cases for shared services or BPOs are constituted by efficiency and cost measures, and even these are not fully accounted for. Instead, multiple factors should be part of a robust analysis, and their cumulated effect should be brought to the attention of top management.
a). Resilience to inflation
The impact of “production” resources’ cost inflation is often not considered, although it affects the alternative operating models (e.g., SSC, BPO) differently, and, consequently, is a source of bias between options.
Specifically, the cost of in-house, fragmented operations, which represents the “baseline” (as shown in Figure 6), is very rarely a steady cost. Instead, it tends to increase over time, and to increase even more rapidly in the event of additional compliance requirements or when additional investments are needed to improve effectiveness. In contrast, the baseline used as a comparison to alternative delivery models is often kept artificially flat, obfuscating a non-negligible source of savings or, at a minimum, predictability.
Outsourcing contracts also typically stipulate cost of living adjustment clauses that shift the risk of unforeseen inflation to the provider. Like all “future” financial options, these are particularly valuable in times of volatility or when the client doesn’t control future costs very well.
b). Account for the time-value of money
The speed of the realization of benefits isn’t the same across models. This is true in initial phases, when the ability to access pre-existing knowledge and infrastructure (for example, of existing centers or of a partner) makes a material difference in the cost and investment curve of the first 24 months. As an illustrative example, an advanced 500-person global-delivery operation can save well in excess of $5 to $10 million per year, which translates to around $100,000 to 200,000 per week. If two alternative delivery models take significantly different times to reach steady-state savings, the savings differential in the first three years will be significant. Interestingly, the same applies to the end-of-cycle situation, when the client wants to evolve the operating model and, for example, merge it with other operations or turn it over to a service provider. The value of time spent preparing for these transitions is rarely accounted for, but it can be material.
c). Reduce the time-to-market of business initiatives
While the analysis above only took into account those savings related to the value of time, such savings represent only one part of the full value equation. The ability to deploy support operations quickly or to scale them up to accommodate fast growth is of particular importance in times when developing markets represent growth potential for corporate portfolios and emerging clientele segments may require setups for different types of operations.
The inability of support operations to keep pace with demand (or with the sales force) can have a variety of implications: Demand is left unaddressed, resulting in a loss of revenue and EBIT; demand is addressed, but at a higher SG&A cost, resulting in EBIT dilution; demand is addressed, but at the wrong conditions (for instance, such that the sales force cannot use accurate cost-to-serve or discount or credit policies because the supporting operations cannot provide such information in a timely and precise manner); or demand is addressed, but at the risk of non-compliance with local or international regulations.
All of these are situations that can expose firms and individual managers to increasingly dangerous liabilities. Again, these scenarios are very rarely quantified. Figure 7 provides a schematic simulation of the analyses that should be run in a robust business case.
d). Flexible cost structure aligned to demand
In addition to having better ramp-up capacities, advanced operational models can typically better handle the (up and down) fluctuations of demand.
For instance, they may be able to pool resources better across businesses or to implement more sophisticated staffing forecasts and resourcing mechanisms. They also tend to make workforces more fungible, such as by cross-training people or by redesigning processes so that different employees can perform different parts of the jobs at hand. Figure 8 describes this concept and compares the differential performances of alternative operating models.
e). Evaluating the overall impact
These aspects can materially alter the business case (as shown in the simulation below in Figure 9) based on real-world assumptions4, which compare the cost differential of an internal SSC operation and a tightly-run BPO operation.
The comparison between like-for-like savings is only one part of the cost envelope. The rest, which often involves even more significant monetary impacts, is explained by some of the factors we discussed earlier: Protection from inflation, taking into account the baseline cost increase; continuous improvement, thanks to mature business process reengineering capabilities, often syndicated across clients; the value of a flexible cost structure that better accommodates the volatility of demand; and the returns from being able to ramp up to demand more promptly.
The difference between in-house fragmented operations and advanced operations is even more pronounced.
f). Combining harder-to-quantify, yet “not intangible” items
The analysis above, while significantly deeper than the analysis that is typically performed, still has not fully taken into account other qualitative, but still very tangible, factors. While a more thorough examination of these aspects is beyond the scope of this document, the following chart attempts to do justice to some of them.
Choices should be made based on realistic expectations, not best-case scenarios. Different delivery models provide different benefits across parameters, such as ease of setup, integration into business and intellectual property provisions, and compliance and control. It is important to note that we observe significant variability in the actual achievement of those benefits, not just because service providers and in-house shared services vary in how tightly they run these operations, but also because the scope of work that is delivered may not be appropriate or may differ from the planned scope. For example, an in-house captive may be built with the intention of delivering high-end and highly proprietary work and of acquiring resources accordingly. However, it is common for leaders of captive operations, while operationally strong, to lack the “salesmanship” capabilities necessary to convince internal clients to migrate the work for which the captive was conceived. When this happens, the expected financial results will not be realized, the captive may be destabilized (for instance, the best staff will quit) and it will become clear that the initial operating model choice should have been different.
A simple scorecard can be a valuable summary tool for executive discussions. Figure 10 provides a synopsis of many of the concepts described so far. It highlights that the values created by the different operating models are commensurate with their abilities to harness three economic “fundamentals” (i.e., labor arbitrage, economies of scale, and process optimization) and shows that different delivery models vary in their abilities to do so. The chart then summarizes what benefits, both quantitative and qualitative, can be derived from these models. While relatively superficial, such an analysis can help in the formation of a strategic options scorecard and in the discussion of alternatives with executives. For instance, it shows that parameters relying on business integration and cultural affinity, if they are important, militate in favor of in-house centers, while benefits that depend on scale and labor arbitrage typically favor offshore captives or service providers with significant scale and global delivery capabilities. Nuances abound: Cultural affinity may not be relevant for all parts of the scope of an in-house operation, and, similarly, there may be areas of high-volume processing that require proprietary technology or know-how. Such areas, hence, may benefit from being kept in-house. In general, though, experience shows that, too often, these qualitative factors aren’t evaluated dispassionately or in sufficient detail , which means that top management members (who can be cold about important choices) and middle management members (who understand the granular functioning) must find a way to jointly solve problems.
Finally, while an analysis of the impact of choices between models is not part of the scope of this paper, market evidence hints at why an increasing number of advanced operations adopt hybrid models and at why operations should encourage executives to test a larger number of alternatives, each simulating different delivery models for various parts of the functions in scope.
Toward more robust business cases and decision-making for advanced operations
The ability of many operations teams to create robust and sophisticated business cases is limited. Consequently, many decisions regarding advanced operating models are either biased or stalled for the wrong reasons. It is important that the determinants of the business case be understood and modeled and that a full value equation be established, including a proper accounting for volatility and other uncertain scenarios.
While all the expertise necessary to achieve such a thorough planning exercise may not exist in-house, significant experience has been accumulated in the almost two decades since the emergence of the first captives and the widespread use of process reengineering in service-type operations. This experience is accessible in an ecosystem of potential partners and is worth accessing in order to do justice to the decision-making processes of advanced operations.
In doing so, operation leaders (as well as the CFOs, CIOs, and COOs to whom they report) will be able to present more strategic, transformative cases to their CEOs.
- Definition of noise in financial terms as dispersion of actual results around expected or trend-line results
- McKinsey P360 data
- Inclusive of the provider’s EBIT
- Multi-year cost savings projected over five years; Volatility in demand assumed as +/- 20% of the average; Fixed vs. variable costs for client at a ratio of 70:30; Cost-of-flex capacity 20% higher than the base (fixed) capacity; Installed capacity of client’s operations equal to the average demand serviced; In-house SSC: Client capacity can only be adjusted with flex/temp resources by a maximum of 20% and with a three-month lag; Outsourced operation capacity assumed to adjust ~90% with a one-month lag