Christian Fournier

Christian Fournier, (French) chartered accountant studies completed by the HEC EMBA, he has been in various finance director positions in global telecom and services companies. He researched and participated to several globalisation experiences from which he wrote a book “Globalisation – adapter l’organisation de son entreprise face à la mondialisation”.

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Watch Your FP&A Processes

By Christian FOURNIER, former Head of Finance Europe at Orange Business Services

Tools and processes used by finance and FP&A (commercial management, billing, accounting, operational statistics, competitive intelligence, planning, budget, forecast, variance analysis, reporting) needs to be customized in order to achieve both efficiency and relevance. There is nothing like on the shelf tools. Company’s industries, size, profile and positioning, geographic reach, product reach, etc. … constitute “forces” that needs to be understood in order to build a relevant and efficient set of tools.

There are debates about the relevance of (some of) these tools. Such as, is so call “traditional” budget or variance analysis still relevant? or beyond budget supporters or what granularity for chart of accounts, etc... These are based on (supposed) opinion that CFO’s and/or managers are not satisfied with the results of their own processes or tools.

In fact, such opinions are generally developing from

  • effectiveness issues in FP&A processes
  • and/or in the ways objectives, bonuses and evaluations are articulated
  • not to mention potential cultural issues either in the finance function or in the management team concerned.

Prior reinventing the wheel, I would strongly suggest to thoroughly analyze these three “causes” and to take necessary actions.

First, look at the two last areas then concentrate on the process built and organization. Obviously, there are interacting but it is still important and more easy to analyze them separately.

1 - A wide range of potential issues can be originated from culture:

From a finance perspective,

  • It can come from a “statutory” vision that may impact/reduce/tint the whole finance output to the detriment of a “business” vision. This would transpire in the way the chart of account is built, the way the data flow are captured and reported, the reporting is made, etc.… There is a definitively need for both vision!
  • It can come from an ownership issue. In other words, up to what point finance (FP&A in particular) is an active business partner to the other functions or only a “bean counter” and “reporter” of other’s performances.
  • Finance set the truth! No, unfortunately, it would be too easy! Our tools are limited and not perfect. We will see how to build an effective set later but still at end the business variables and realities may be quite more complex and uncertain that what we may think.

From a management perspective,

  • Power struggle! Planning, budget, forecasting, reporting are definitively among the “battle fields” of internal politics and power struggle. Let’s face it (rather than unnecessarily criticizing those processes).
  • Ownership issuese. Up to what point managers buy in the plan, budgets,…
  • Reality perceptione. Up to what point managers understand their internal and external environment and face it effectively. The “reality country” is different and far more demanding than the “theory country”.

These cultural issues impact the image of the finance outputs and needs to be assessed and considered as such.

2 - The ways objectives, bonuses and evaluations are articulated have also a major impact on the perceptions of the finance output. Obviously, managers (and employees) like and want to be considered as successful and to receive the financial and other elements of recognition that goes with it. As such the tools used for definitions and measurement, are subject to a lot of pressure, in particular when the environment is difficult or aggressive and when results are not in line with expectations. Questions about validity of the objectives definition or on the way performance is measured will for sure be raised and may be valid. This is a complex issue and I am afraid that no simple and single response exists.

I would still advocate the fact that plan, budget and forecast shall be set as per the best understanding on the business conditions and environment and shall not be polluted by “aggressive” or “defensive” individuals objectives and targets settings. This suppose a certain level of disconnect between the two set of tools.

3 - The relevance and effectiveness of the finance processes is definitely a finance responsibility but involve inputs from all parties. Over the statutory and tax obligations, finance processes must be design in order to give company management the best chances to take necessary decisions in a timely manner. This brings us to the first “dimension” that needs to be looked at: the time dimension.

The competitive or market intelligence is the next dimension to be analyzed i.e. the markets with its different components:

  • The geographic reach,
  • The company profile,
  • The customers or customer profile(s)
  • The products
  • And their trends (development stage, volume, price, competition…)

The external and internal resources are the next dimension to be analyzed with its different components:

  • Inputs (raw materials, components, services)
  • Structures (factories, premises, …)
  • Equipment (manufacturing equipment, IT, …)
  • Staff
  • Financing
  • And for each component, they are elements with different degree of strategic importance for the business.

The time dimension

The “statutory time” tends to naturally drive the finances processes. Accounting would be the prime example and it may be satisfactory for certain business or industries. The calendar month/quarter/year will drive the different finance activities (commercial and operational statistics, accounting, planning, budget and forecast, reporting…).

Still, some industries or business type require a different way to “respire” and then it is essential to take this in consideration in the design of the overall process. Some industries have a material seasonality, some have a very short order to revenue time (immediate to few days) where for others it is month(s) potentially year(s). This needs to be correctly assessed and integrated in the whole time table i.e. from order reporting to forecasting and reporting both in terms of timing/delay and in terms of periodicity.

A further aspect of timing to be integrated into the processes is the “time… to”. Time from proposal to order, time from order to revenue, time from contract to orders, time from launch to delivery, just in time ... depending on industry and company there are always a certain number of key “time to” which needs to be managed and which are critical for the accuracy of the forecasting exercises and in the explanation of the variances. Their identification, measurement and proper application are in most case vital to the quality of the overall process.

In certain business you may want to report and analyze revenues on a daily basis considering weekends and public holidays (distribution, restaurants…). At opposite in others, the contract or order to revenue cycle is such that even monthly reporting and analysis is too short to properly integrate any meaningful changes in trends.  A material change or delay may impacts your revenues and revenue forecast. Optimistic or aggressing views may very well impacts the quality of your forecast.

Market dimension:

The market dimension and its components are keys that need to be properly integrated within the design of the overall finance processed (end to end). 

  • Geographic reach will set constraints that depend both on markets and company size. For purely local markets and companies, this element is not so important and statutory may prevail. Still for international and global markets it becomes an essential element of analysis, from a purely geographic point of view but also from a currency perspective. The statutory entity dimensions (country/currency) needs then to be complemented by the delivery country and the pricing/billing currency in order to correctly capture, analyze, forecast the evolutions.
  • Company profile, The legal structure in large companies do not reflex accurately the actual business organization (center of excellence, production, call or logistic centers, cross border teams,…). It is then of utmost importance that the organization is properly represented in the way the whole data structure and flows are organized. Over detailed it may be heavy to manage, too “simple” i.e. simplistic, it may lose relevance.
  • The customer profile(s), needs to be carefully taken in consideration while building the process. From few customers to a very large/diversified customer base, from direct to indirect sales, the overall process needs to keep track of the fundamental characteristic of your customer base. It may be more or less easy and there is always a cost benefit ratio to be considered, still at end, you need to ensure that you have a meaningful end to end customer (or customer profile) tracking and management.
  • Products or services need also an end to end tracking and management. Like for customers, this may correspond to data amplitude that can range from few to millions. So similarly, through a proper cost benefit ratio the product dimension shall be organized and followed in a way that is both manageable and relevant for the business.

Those data dimensions will obviously combine on a dynamic way. This shall permit to capture and measure accurately (in the most extended configuration) (i) who sell what to whom in which currency per country destination at order processing level (ii) the revenue generation and associated Cost of sales in the same data configuration (billing/accounting) (iii) in order to compare to past periods and to budget and/or reforecast made along the same lines. This end to end chain is essential.

Effectiveness and relevance will get reduced each time the chain is ”broken” (or oversimplified). One “traditional” place is when information existing at order and billing level are “aggregated” at accounting level whereas budget/reforecast would be supposedly prepared based on business drivers that “miss” some of the dimension. Example with currency, if the pricing and billing currency information is lost when converted to statutory currency in accounting and if budget/reforecast is build using the latest revenue trend from accounting, any chance to accurately and efficiently understand, report and forecast incidences of currency fluctuation is lost. Similar issues can be met if the customer (or customer profiles) is lost along the process or if the product granularity is oversimplified.    

  • Key trends such as development stage, volume, price, competition… of markets needs to be gathered and structured in order to understand, report and forecast. Each company needs to understand which combination products/customers/geography is meaningful in terms of market evolution and competition, and to develop/implement competitive intelligence along those lines. Prices and volumes are the most common; those depend more generally on the development stage of the market (developing/mature/declining markets and/or investment versus replacement markets) and level of competition. Competitor’s movement and major product change/innovation are also key and must be tracked.

Whereas finance may consolidate all information, sales and marketing shall be key contributors. Company objectives/targets (budget/reforecast) shall be logical with the market trends, correspond to a clear set of strategical and tactical options/hypothesis and performance shall be “benchmarked” to these options/hypothesis. Most of these options/hypothesis represent real decisions rather than simple “forecast”. Over the quality of the process, this is the quality of these decisions that is key to the final result. It means a necessary and material involvement of the management structure all along the process. Those decisions must be captured / embedded in the final output. They shall be tested with reality at end. If in any forecast there is a part of mechanical data gathering, there is also a fair amount of managerial pro-forma decisions and it should definitively avoid all form of wishful thinking.

Without those elements the relevance and effectiveness of the planning, budget and forecast processes thus reporting are questionable as well as individual objectives setting and evaluations. This is the main source of the uneasiness with those processes.

The challenge in there is in two folds:

  • Access to market data, evaluation and analysis (market or competitive intelligence). Difficulty here covers a wide range of possibility and complexity. A reasonable effort shall be made but it shall be understood that it may not be perfect or with a large degree of accuracy.
  • Capture and analysis of equivalent data for the company shall be more easy and manageable provided a proper organization is put in place. Rather than educated guess, capturing and analyzing the volume and price evolutions (including the specific incidences of currency variances) for each meaningful products/customers/geography combination with reasonable accuracy from past to present shall not be such an issue, nor forecasting (budget/reforecast). The total volume and the unit price may well not be sufficient. For example, the order/delivery size might be a key component of the effective price billed (discounts/regressive prices), in such case this analysis must be structured in the process (actual/forecast/variance analysis).

External and internal resources

In each category, the degree of importance may largely vary from strategic to common/easily exchangeable. This may be linked to the importance in terms of costs, to the scarcity or uniqueness of such resources or any other industry specific reason. The whole process shall then attach more attention to those resources than to the more common one. Data structure decisions are not just technical  decisions, they are key fundamental decisions impacting business.   

  • Costs of sales (raw materials, components, services). Those will largely follow the analysis of the revenues in terms of overall “volume” variances. Still they may also have their own particular element to be tracked and analyzed. Currency may be one of them (i.e. when the buying currency is different from the selling currency) creating potential variance in margin. Price evolution may not be linked or similar to the one of the related products sold…

Whereas in the “theory country” evolution of costs shall reflex in the prices of product sold, in the “reality country” it is far to be so simple and automatic. Something very similar and parallel to revenue must then be design and implemented for the goods / suppliers / geography combination (at least for all strategic ones). Purchasing shall be a key contributor in-there.

The combination of revenue and cost of sales processes shall permit to understand and forecast margin on cost of sales evolution. In most business, the revenue, cost of sales and margin constitute the major business challenge and thus the area where effort in analysis and forecast shall be concentrated.

The other costs and investments will be captured, analyzed and forecasted following the company organization structure using enough granularities to have a detail breakdown covering every process of the company and matching it to the management structure. Certain non-strategic functions can be profitably outsourced to more specialized firms.

  • Structures (factories, premises, …) and
  • Equipment (manufacturing equipment, IT, …)

Again depending on industries and company those can represent quite a different challenge. Over the traditional analysis of the costs and investments it represents, it’s their productivity and utilization rate that must be measured, analyzed and forecasted.

Depending on business type, the weight of staff and associated costs can largely vary in percentage of revenue or even of the margin on Cost of sale. Services industries would concentrate large percentages in staff costs whereas manufacturing or extraction industries will concentrate a far lower percentage.

The head count by ranks and the statutory costs by function are largely insufficient. It shall be complemented by a true qualitative analysis in particular for the key competencies. Associated costs such as training, recruitment, redundancy,… shall also be substantiated over and above the “traditional” statistical trend.  

  • Financing and treasury.

A company cannot survive without proper financing. It supposes a dedicated / structured follow up and forecasting (that is a subject in itself).

Finally, keep an eye on your communication. Efficiently gathering and analyzing data, furthermore producing relevant synthesis represents probably 90% of finance work. Still, what may make the difference is the last 10% i.e. the way those are communicated internally and externally. 

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FP&A Analytics and Simpson’s Paradox

By Christian FOURNIER, former Head of Finance Europe at Orange Business Services

Are your KPIs, Scoreboards and other metrics safe from the Simpson's paradox?

“Simpson’s paradox or Yule-Simpson effect is a paradox in probability and statistics, in which a trend appears in different groups of data but disappears or reverses when these groups are combined. It is sometimes given the descriptive title reversal paradox or amalgamation paradox”. (Extract from Wikipedia)

KPI, dashboard, other types of analytics that finance and FP&A use for communication may include or generate such paradox polluting the decision making process. Typically, those tools aggregate i.e. combine data in the perspective to give simpler and quicker ways to manage and communicate performance and take decisions. The general trend in management practices is to highly recommend limitation of indicators’ number, and as such to increase the aggregation level. It more or less focuses the attention of top and middle management depending on company culture and on rewards and recognition systems.

It is then highly possible for such aggregation to induce directly or indirectly “false” understanding or certitudes just like Simpson’s paradox would do. It should then be FP&A role to find and to fight such occurrence.

Still, we hardly hear or see mention of this concept during professional studies and life. 
Practically, teaching and promotion of such tools includes few recommendations that would potentially exclude dropping in that trap but without formally researching or verifying whether it exists or not.

Example

A sales director is looking at the ratio of commercial contact turned into sales in order to follow the performance of two teams and (among few other things) reward them on this basis. 

Team 2 had better rewards periods after periods.  

Frustrated Team 1 leader ask their FP&A to analyze in more details and feedback is 
“Sorry, Simpson paradox!! Here is a better view of the relative performance! In fact, the two teams had the same performance over last 6 periods“ 

Of course, here I forced the figures to a ridiculously simplistic example to illustrate my point and make it easy to understand. 

In real life, it is generally far more complex to identify such issue. My example is a reversal case (or nearly) which is more easy to spot. Still, in many cases it will not be so extreme, it will only hide (make disappear) the real evolution or performance. 

The paradox appears thanks to few main causes:

  1. Dependent variables are hidden through the aggregation of data,
  2. Difference of distribution in time (the example is it),
  3. Difference of size between the data groups entering in the calculation.

Similar examples can be found with return on investments, any given type of expenses (say marketing) versus revenues, product lines revenue distribution or growth, etc.… (In fact, many of the widely known ratios or indicators may very well include or generate such effects if not properly customized and tested).   

This brings few questions:

  1. Up to what point this paradox is known (as such or in another form)?
  2. How is it reflected in the definition and implementation of the company tools and processes?
  3. How is the verification done?

In my example, FP&A should have to make sure the KPI was not reduced (aggregated) to such a level and demonstrate that a more comprehensive set of figures needs to be considered, this should have been made during the set-up of the company systems and FP&A should have “tell the story” behind those figures all along the process in such a way that recognition should have been more in line with performance. A period to date indicator (or a weighted indicator) would have been more representative e.g.

In this example, it is highly intuitive, i.e. even without knowing about the paradox, a reasonably able person shall have made it happen. Still, reality can be far more complex and intuitive reasoning might not be sufficient to identify and adopt the right approach in each and every case, in particular, when the context is strongly oriented towards limiting the number of KPI, Indicators,… used by management. Who has not heard a manager saying “This is too much detail/figures, I just need to know (i.e. my compensation is only based on) these x indicators”. 

Obviously, this brings into picture a different subject i.e. the reward and recognition based on KPI, scoreboard and other metrics. Still, is it really different, if the metrics can reveal to be paradoxical?!

Knowing (be conscious of) this paradox and systematically making sure to avoid its trap is then a key role for FP&A (i) when elaborating the systems and process that will be used (ii) when analyzing and commenting the ongoing results. 
 
We may try to draw a list of a potential common case but it remains a high-level approach that cannot exempt from doing effectively the exercise. 

  • Volume vs price evolution i.e. where your Revenue Indicators may hide more or less important shift in the price and/or volumes. Similar for external expenditures.
  • Regional differences, RI covering wide geographic reach may hide major evolutions in the respective areas,
  • Customer profiles differences, RI covering wide customers profiles may hide customer profile shift,
  • Product or market maturity phase, RI covering wide range may hide product or market maturity shift,
  • Currency effect, in particular when pricing currency is different from the entities currency and from the consolidation currency. Indicators expressed in consolidation currency will aggregate and then hide any currency effects and shift. This also applies to most costs.
  • Risk assessment or indicators,
  • Quality indicators,
  • Productivity indicators, 

Those applicable to revenues (but not only) may very well combine all together. 

A very simple  example would be a global company management concentrating on an overall revenue indicator mixing revenues from different geographic areas with product and markets in different maturity phase where customer profiles are evolving rapidly and where business is done in few pricing currencies but over a large number of legal entities (with different currencies then) and consolidating their results in its home currency. Such a global revenue indicator would mix so many effects and potentials evolutions that it may reveal paradoxical. Even more dangerous, as it may not have been a problem for few years i.e. whereas the potential of an issue was there but the reality of the markets was not challenging (activating) it. 

We could bet in such a case that the information systems will “lose” the pricing currency within the consolidation process, potentially shortcut the entity currency to consolidation currency effect too; will aggregate the product into a few product lines historically driving the company development, will probably lose track of the customers profiles among few other “simplifications” justified by the necessity to keep things more effective. Furthermore, the FP&A people may be located in a limited number of shared service centers loosening the contact with local reality. The end result would be that the whole organization IS and processes, (probably culture) are cut from reality thanks to a basic misconception (lack of understanding/verification) during the process of defining and implementing tools.  

FP&A peoples do not need to know all the mathematics about this paradox. They still need to understand the concept, recognize that it may “slip in” when defining their tools and processes, KPI, Scoreboard and other metrics and then make sure it is not the case.  

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Forecast Accuracy

By Christian FOURNIER, former Head of Finance Europe at Orange Business Services

Forecast, AnalysisForecast accuracy is often a subject of discussion. What are the issues met that can generate such level of discussion? 

Evidently, the first question is whether a forecast needs to be accurate (or not) or more exactly what level of inaccuracy can be tolerated? In other words, what is in this context the definition of an accurate forecast. Let's take a few somewhat divergent views that I met in my carrier.

  • The forecast is accurate if the actuals tend to match the forecast within “small” variances. It would mean that we define small but let that issue aside for the moment.
  • The forecast is accurate when all the assumptions and decisions are sound, correctly captured, sized and timed to. This definition accepts that actuals are different due to assumptions or decisions that failed, are not implemented or achieved or with wrong timing.  
  • The forecast is accurate when it effectively captures all the “negotiated” objectives of the divisions, departments and their management. This tends to “personalise” the variances.
  • The forecast is accurate when its structure constitutes a sound suite of assumptions and decisions to achieve a given strategy. 

Rather than trying to decide what is right and wrong, more precisely what creates or is the result of positive and negative behaviours inherent to human nature, let us look at the “values” underlining each definition. 

  • The forecast is accurate if the actuals tend to match the forecast within “small” variances. Obviously, this gives “easy” time to management by giving visibility and predictability.

It minimizes surprises and the needs for corrective actions (which does not mean that it does not include changes and challenges). 

  • The forecast is accurate when all the assumptions and decisions are sound, correctly captured, sized and timed to. A “technical” view of the forecast that insists on confidence and consistency on the forecast. 
  • The forecast is accurate when it effectively captured all the “negotiated” objectives of the divisions, departments and their management. That view insists on ownership throughout the organization.
  • The forecast is accurate when its structure constitutes a sound suite of assumptions and decisions to achieve a given strategy. That one insists the overall vision and goals of the company. 

If we accept all of those are valid then the forecast needs to be a tool that helps the company to achieve its overall goals through ownership thanks to a sound technical process that give visibility and predictability based on a set of assumptions and decisions.

This is probably not achieved in one but rather by a set of tools covering the short, the medium and the long-term (accepting that term has a different meaning depending on the industry or business type). The overall goals would be the domain of the plan, the ownership would be through budget (budget and reforecast), the visibility and predictability would be help through “forecasts” all those been supported by a coherent and consistent process. Each tool would have its own level of precision and as such its own set of variances.

Such should eliminate or limit the number of “inaccuracies” not to say errors, but not all. It shall permit a clear analysis of the variances and lead to decision making. Variances and variance analysis then become a true asset (i.e. not the forecast accuracy) and set the basis for decisions.

For more details you may want to refer to my previous articles:

Still, all this is based on the perception of the environment and its evolution. These “externalities” that will impact the accuracy of the whole process which depends on the quality of the business and competitive intelligence of the company. “Business is a democracy”, customers, competitors and few others have their say and a lot of the assumptions are based on those (in particular for the revenues and cost of sales which generally drive the rest).

At any moment or over a period of time, one or several of those externalities can generate variances or deviances that endanger more or less your forecasts. This is not inaccuracy as such, this is a lack of business and competitive intelligence. The issue is not in the forecast process it is in the intelligence gathering domain and shall be looked at and treated as such i.e. no point in looking at your forecast process, you must look at your intelligence gathering process. Obviously, if the intelligence was there but not integrated into the forecast that brings us back to the internal process. 

There may even not be a clear solution at that level. This brings us to the flexibility and agility necessary in the forecast process. It is not directly an accuracy issue (except if the accuracy issue is linked to lack of agility). 

In summary, forecast accuracy is not the important item and not worth the debate (as long as you have a sound process). Variance analysis is the key

It shall permit to identify precisely whether those variances are linked to:

  • Understanding / interpretation of the environment and the competitive situation,
    • Prices evolution, currency impact, customers financial situation, economic trend changes, anything that impacts volume and price or profitability, etc…  
  • Externalities not perceived at the time of the forecast,
    • New entrant, competitor product or technologic breakthrough or evolution, etc…
  • Management ownership issues,
    • Productivity, program success or failures, things links to management decisions or lack of decisions, etc… 
  • “Internalities” I.e. other not management issues. 

It shall drive to corrective or adaptive actions i.e. … one new forecast. 

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Business Cases: A Key Decision-Making Tool for FP&A

By Christian FOURNIER, former Head of Finance Europe at Orange Business Services

FP&A Tags: 

Decision making requires a formal process to ensure that sound bases are taken into consideration and to ensure accountability and control. It is applicable to the different types of (material) decisions i.e. investments, developments, catalogue or contract pricing, reorganisation, etc. It is more flexible and specific than the forecast methodology (budget, rolling forecast, etc.). 

Why a formal process?

There are decisions that engage the company future and cannot just be managed through the company forecast process and need a more in-depth and specific approach. Furthermore, many of those decisions need proper coordination between different functions. 

A formal process permits then to have a standard way to organise the decision making with a clear set of deliverables and responsibilities. 

Business case is such a tool which help management to determine the value-added and profitability of each material project.

FP&A is a key player in managing this process. Practically, business case is just another type of forecast i.e. a forecast applied to a more specific subject and with different time scales. It then presents the same general characteristics that forecasting (methodology, potential bias, need for internal and external data, analysis and reporting, etc). FP&A shall then ensure that the same level of rigour is applied when preparing business cases.

The key business case characteristics:

  • It should precisely describe the decision’s objectives, why it is proposed (response to a threat or opportunity), the resources that would be needed and the expected results/consequences including return on investment.  
  • It should involve the different functions that will be part of or influenced by the decision. As such it should enhance inter function cooperation and is logically involving a different level of management depending on materiality levels. 
  • Its scope is different from the recurrent forecasting activities (plan, budget, rolling forecast, etc): 
    • It does not try to cover the whole company but only the areas specifically concerned by the decision,
    • Its time length is the one relevant for the decision,
    • It may cover resources that are or are not included in the current applicable forecast. It would be enacted in future forecasts when relevant.
  • It permits traceability of decisions, follow up and control. It should be part of the company governance and delegation of authority.

Company governance and delegation of authority are structural components of the company culture. It defines who can/shall decide on what type of actions / responsibilities and up to what level (materiality generally express in money terms but not only). It should be adapted to the company type, size and business. Their purpose is to improve the way of working but like all cultural elements, it can presents and/or generates bias. 

  • Too centralised, it will concentrate all decisions to the top-level (M0, M1) and can become a factor of rigidity impacting motivation and reaction time,
  • Too distributed it will dilute the decisions to the different level of management (M0, M1, M2, …, Mn). It may be a motivating factor but can also impact company coherence and complicate inter function decisions,
  • In between those two extremes, different variants exist (based either purely on management level and/or on type of decisions).

Why use the formal business case process?

The formal business case process will be the tool that put those D.o.A into practice for material decisions such as:

  • Material investments out of the business as usual (new or extension of production capabilities, M&A, Information system change, new product developments, …),
  • Material commercial decisions (pricing of large contracts, change in catalogue pricing, the opening of new agencies/countries, …),
  • Material organisation changes (in/outsourcing, changing organisation structure, …)
  • Business as usual decisions involving different functions and/or over a certain value or of a given nature.  

The formal business case process will ensure that the different stakeholders’ inputs, engagements and sign-off are taken into account and that the deliverables are clear (timing, resource allocations, …). The decision will be registered and relevant analysis and reporting be put in place to follow the business case activation. In many cases, this will be through a project structure. Defining standard format(s) and submission process is important, the substance in each business case is essential. 

FP&A professionals shall then be engaged in all those activities as partners to the business i.e. to ensure that the financials of the business case are sound, but also as D.o.A “keepers” i.e. to ensure that the decisions made through the management structure are kept in line with the D.o.A and governance. 

The business case process will challenge (probably even more than the forecast process) their abilities to exercise their influence and support the business by putting them in the operation’s business centre.

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Explaining, Reporting and Forecasting Revenues Evolutions

By Christian FOURNIER, former Head of Finance Europe at Orange Business Services

Among FP&A challenges understanding, explaining and forecasting revenues evolutions are one of the top items. It may be more or less difficult depending on the company business.

The key variables that are to be considered are:

Some variables are internal financial data that can easily be extracted from accounting and commercial data: products, quantity, prices, currencies, customers, etc. It requires proper data management and good quality as well as adapted analytics tools.

Other variables are external or result from a comparison between external and internal data: competitiveness, market, benchmark, etc. Those require proper competitive and business intelligence gathering and analysis. It is also where the dependency from other departments is the highest and where the true challenges reside for FP&A. 

It also requires adapted processes.

1. Data management and analytic tools:

Over the past decades, the attention to those elements has regularly developed, increased and thus largely improved FP&A abilities not just to understand, explain and forecast but also help in business decision making and actions. Still, there are limits to what it can achieve in the absence of proper competitive and business intelligence.

2. Competitive and business intelligence:

This is largely a new and not widely used domain. Even if some of it exists in the company (at a strategy definition level), the systematic involvement of FP&A and integration in FP&A processes hardly exist or is quite new. It is a wide domain and I will not try to cover it holistically here. I will only give some tips on how to successfully use competitive and business intelligence coming from my experience.

  • Product competitiveness is not just about price. In many cases, the default price level explanation is insufficient not to say irrelevant. The company needs to regularly perform comparative analysis (customer needs covered, our product features, main competitors' features). This analysis shall include evolution analysis (customer needs but also the competitor’s product launch and the company’s development plan).  Ideally, the analysis should help create a sound vision of the company’s ability to perform against competition and explain revenue evolutions from past to future.
  • Company competitiveness is a similar process but on a wider basis. It covers the assessment of the customer service quality, the completeness and complementarity of the product ranges, the geographic reach, etc. The assessment is done not just in absolute terms but compared to main competitors. Win/loss analysis is one of the tools relatively easy to implement. It requires FP&A involvement (at process definition and in the analysis of the data gathered).
  • Customer base and its evolution. It’s a wide subject that requires types of analysis that can be very different. If a company serves a large purchaser base, it may require a big data type analysis whereas markets involving a small number of potential customers (repetitive purchasers) will require far more personalised approaches. Key customer partners shall be inquired in even more detail. Here again, FP&A needs to get involved not just in the analysis of the business data gathered but also in the financials of key customers accounts. Ideally, the elements gathered would permit us to picture what are the overall business evolutions of those customers, their needs evolution, their financials evolution, their strategic move, etc., and then based on this information, we will be able to understand the consequences for the company.
  • Entry and exit barrier i.e. how much effort/cost is involved in changing a sourcing partner (for customers) and how much effort/cost is involved in gaining a new customer (from competition). This is another factor that should be understood by the company and FP&A in particular.

The higher (more precise) the level of competitive and business intelligence is, the better the quality of understanding, explaining and forecasting processes will be. This obviously is not only for the revenue domains. It will also impact the development and resource allocations.

3. Adapted processes:

Proper information gathering and analysis processes shall be put in place. It requires defining what information shall be researched, on what format and who shall be involved. In previous paragraph, I mention a few processes. They can take different forms, and there are others that could be looked at.  Just a few tips again:

  • The sales manager/director/CEO shall regularly meet with sales teams and customers to validate business information. Salespeople have consciously or unconsciously a lot of information as well as sales support, negotiation teams and distribution channels. In too many cases this information is kept private and not (or incompletely / occasionally) shared with the rest of the organisation. Organisation tends to be more interested in these individual’s performance than in the reasons for that performance. I would add that these individuals may hate a detailed form for reporting their activities. This needs to be taken care of. Information shall be structurally collected, controlled and analysed. 
  • Win/loss analysis needs a proper discussion with concerned customers. Why did we lose or win? What have we done correctly or wrong? Who was our competitor? Did we provide a comparative assessment of products?  To be helpful this debrief needs to be kept non-conflictual and truly informative. This is not the place to have justifications (from one part or the other) but to gain true meaningful information. The individuals initially involved in the deal are not necessarily the best to perform this customer debrief.
  • FP&A should collect and analyse financial results of large customers. The advantage of having large customers is that they publish more or less regularly financial results. The analysis should be shared with the sales team and management. This would give a perspective on their own business evolution. In the absence of such publications, annual reports should be collected.
  • Comparing products functionalities. It can be more or less easy (services). Still, in many cases purchasing samples of competitor products is feasible. Access to their advertising or exhibition is available as well as an independent assessment. Let not oversee this information, collect it and properly fed back in the organisation.

FP&A is the key actor is orchestrating changes

It is important to note that FP&A will be one of the prime users of such “educated” assessment outputs. Therefore, FP&A should be a force that promotes or pushes for such processes to be defined.

This is a two-way impact. The intelligence gathered also impacts the pure FP&A suite (analysis, reporting, forecasting). This suite will have to be organised differently depending on a number of criteria: 

  • The type of revenue (one off, recurrent/contract, project)
  • The key Time from proposals To orders To revenues (immediate, month, quarter, longer …)
  • The markets stage (developing, growing, mature, declining)
  • The type of product/services (new/innovation, new version, mature, obsolescence developing)
  • The type of market (local or multi-local, international, global)
  • The geographic reach

When major changes happen in those criteria, you need to consider circumstantial events

  • A major crisis in one customer market or with one individual customer (Thomas cook type situation, customer M&A, …)
  • A major change in the competition (new competitor, market globalisation, competitor product launch, competitor strategic move, …)
  • Large contract won or lose, …

All those elements influence both the timing and focus of analysis and reporting and the frequency/length of forecasting. FP&A is obviously the key actor in defining those changes and orchestrating the cultural changes that support it.  

The theoretical concepts exist (Plan, budget, rolling forecast, scenario or project budget/forecast, driver base forecast, etc…). Yet, there is no on the shelf solution. It is one of the prime FP&A responsibilities to choose and customise the tools appropriate for the company's competitive situation. 

The ultimate goal of this customisation is to be able to effectively and efficiently analyse, report and forecast based on the company-specific situation and through that to change from a “statistician watchdog” to a true business partner.

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