For quite some time CFOs and the finance community have been talking about transforming the finance function, becoming better business partners and focusing on the value-add, strategic activities.
At the core of that transformation is FP&A, as activities like business planning, business unit strategy, investment allocation and predictive analytics become important to fulfil finance’s new, expanded position within the company.
But to do that, FP&A itself must transform and change from its traditional flux analysis and flash reports to a much more modern and cutting edge department within the company. When starting to embark on your own FP&A Transformation journey, there are a couple of principles you need to keep in mind.
First, there isn’t a one-size fit all optimal FP&A operating model that all companies in all industries should implement. Personally, I have worked in finance in FMCG, Consumer Durables and Silicon Valley IT. It would not be possible to run the same finance operating model in all those companies at the various life-cycle and maturity stages there were in. The industries and companies were at very different levels of maturity, complexity, growth, and the technological capabilities were very different. So you need to make a proper assessment and decide on a model that is right for your specific company.
Second, you need to articulate the future operating model (see figure 1), what your new FP&A department will look like in a future state and what your key focus areas will be. If you only articulate what FP&A is not going to be doing, (for instance no flash reports, accruals, or expense reclasses) your transformation will be materially slowed down or impossible. Your team may even fear that they are losing their jobs and will actively work to resist your transformation efforts. Transforming FP&A needs to be a positive thing that will allow FP&A to take on an even more strategic role within your company.
Figure 1: FP&A Operating Models
Third, you need to work with a phased and structure approach. Transformation is difficult, time-consuming and not without risk. Your FP&A staff is very busy and working very long hours already. They are buried in basic duties and don’t have the time to undertake major transformations. Furthermore, there is operational risk involved when transforming FP&A. If you do it wrong, you could even inhibit your company’s ability to close the books timely and accurately. So you have to approach transformation in a structured way and use a phased approached to balance the workload of your team and mitigate the operational risk of the company.
Lastly, the optimal operating model evolves continuously over time, which means that finance leadership constantly must evaluate the current position and continuously transform their departments. Technology changes, your industry changes, your growth rate changes, your business complexity changes, and you need to continuously evolve and adjust your operating model to those changes. Transformation is an infinite game, not a finite game. What is cutting edge today, is probably old-fashioned tomorrow.
Interview with founder of the International FP&A Board Larysa Melnychuk
The global trend for FP&A is surprisingly singular; apparently, we all want to know how to influence and predict our financial future. At the International FP&A Boards, professionals from all over are eagerly sharing and learning about how to get there.
Three-and-a-half years ago Larysa Melnychuk left her corporate job of 18 years working as an FP&A (Financial Planning and Analysis) professional for several different large companies in the UK. At the time, the discipline, involving—roughly speaking—the use of financial data to make fast decisions based on prediction, was rapidly developing.
When Melnychuk left, she remembered a question that had fascinated her before: how do the other companies do it? It was the seed that led to the International FP&A Board, a professional discussion and debate forum for senior finance practitioners. The Board is now well established in 10 cities and 9 countries in Europe, the Middle East and Africa. Soon, it will be expanding to North America and Australia.
Why is the Board growing so fast?
People are realizing that the classical style of management accounting and financial planning and forecasting simply isn’t enough anymore. When I was a practitioner myself, we were always working on tight deadlines. But at some point, you just need to stop and look at your company from the outside—think about how others might be doing it.
That’s the main reason a lot of prominent CFO’s and Finance Directors attend our boards: to understand what’s happening around the globe. The Boards are exclusive to CFO and FD-level practitioners. We share diagnostic content and case studies, analyze the latest trends and discuss best practices. Contributing to this global exchange of knowledge really appeals to a lot of people.
Our Boards offer a non-commercial and vendor-agnostic environment to do so.
And it seems to be working?
The first Boards were organized in London. That’s where we developed the FP&A Analytics Maturity Model, Rolling forecast and the FP&A Business Partnering Models. They all received great feedback in the global FP&A community. Soon people were joining in the London boardroom through Skype or flying in from the Middle East and all over the place.
That’s when we decided to come to them. Our first International Board was held in May of last year in Stockholm. Now we're on three continents and the exposure and support we're getting are fantastic.
In the Benelux, the events are complimentary to our members thanks to the partnerships we’ve developed. One of those partners is Tagetik, a company that currently sponsors many of the international Boards, namely in the Benelux, Switzerland, Germany, UK and Sweden. Tagetik will also sponsor the launch of New York FP&A Board on the 6th of April 2017.
The Association for Financial Professional (AFP) is our educational partner. They provide the first FP&A certification in the world. We’re provided with the beautiful boardrooms we meet in by the Page Group, the global recruitment and consulting company we’re partnering with.
You've only just had a Board in Brussels and Amsterdam, how's FP&A developing in the Benelux?
Each country has its own dynamic. Even when we discuss the same case study, the results are different. During the Benelux meetings, we tried to lay the foundation for changing the FP&A Analytics Maturity Model into an operational model. It was incredibly inspiring.
Thomas Lundell was present at both meetings. He’s the FP&A director of NetApp and held a presentation about the big FP&A transformation his company is going through right now. Thomas was asked questions long after we'd finished. You could see people’s inner child being released, they were so curious.
What's interesting about the NetApp case study is that it shows that there's no single 'right way' for making the transition to a more predictive, real-time FP&A — each organization is unique, even though we broadly face many of the same challenges.
What would you say those challenges are?
We’re definitely living in the Big-Data world already. Still, there is an inability to use this data for forecasting and planning—or to distinguish key business drivers. Huge amounts of time are spent by financial analysts on cleaning data, trying to find the logic, consolidating the result. This means less space for creative, predictive analytics.
At the same time, many organizations still have not-so-consolidated processes, very dispersed and disconnected. In reality, this should be a company-wide initiative, integrated and collaborative with a simple planning process that’s easy to manage.
In terms of technology, from spreadsheets and markers, we're moving towards integrated and collaborative planning platforms, where different kinds of planning processes are harmonized.
Isn't there software to help with that?
Of course, but before you introduce the new FP&A systems you have to understand the architecture of your model. Not enough companies have predictive models that are based on key drivers that allow you to react fast enough to developments. Historically there are a lot of partially data-driven businesses — very complex and very static models — and we still continue to have that today.
We need to harness the ability the power of modern technology. Excel is still dominating the world, and because of its ease and flexibility, everyone likes it. However, it has a lot of shortcomings and limitations. As I always say, it's good to have Excel, but it's not enough.
So what's next for FP&A?
If a driver-based model is implemented in a good system properly, then organizations can have incredible results—including an agile and flexible decision-making process. But don’t forget the people. FP&A business partnering and a good communication flow are essential for those results. The right talent is increasingly hard to find. We need people to crunch incredible amounts of data, yet with the ability to communicate with decision makers.
Eventually, companies should be able to predict in real time in order to react to current changes. Leading organizations are already moving towards this. They’re utilizing best practices and trends for their analytics, as well as their forecasting and decision-making processes.
A couple of weeks ago I joined the meeting of the Amsterdam FP&A Board where we discussed the subject of the FP&A analytical transformation. In the course of the meeting the participants mentioned their current main concerns, some of which such as Data ownership, Data quality, and Business Glossary (‘Speaking the same language’). This surprised me. Why? Because these topics are ‘hot’ topics of Data Management (DM) with no common vision on the subject.
As a result I decided to write several articles on these topics for FP&A professionals. The main purpose is to share some knowledge and practical experience and to start a discussion about these subjects.
In this article I would like to talk about the following questions: How to recognize a Data owner? and What the Data owner is accountable for?
I was deeply touched when some of participants said they considered FP&A to be the owner of all data that comes to the department. The arguments were: ‘FP&A makes reports’, ‘Nobody else wants to take responsibility’. I wonder how many of you also share this vision?
To create a common opinion on the subject, let’s explore the following questions first:
- What is data and what happens to the data within an enterprise?
- Which roles are recognized in data-related areas and why?
- How to spot a Data owner?
- What are the responsibilities of a Data owner?
What is data and what happens to data within an enterprise?
Case study: an account officer of your company closed a deal with a new customer and signed a contract. He/she provides data about the customer and the contract. First the data is input in CRM system. Then the data moves to the Financial system and DWH undergoing some processing and finally the reaches FP&A department to be used in reports.
Using Data management language, Customer and Contract data (facts represented as text, numbers, graphics, images, sound, or video) went through the data life cycle (creation, transformation, and usage) through different applications. In the process the Data has been transformed, aggregated, etc. These transformations could have taken place according to different business rules. When data got into some context (in the form of a report) it turned into Information (data within a certain context and timeframe, that have a particular meaning  ). It could happen that Data lifecycle has been embedded in different business processes and went through different departments.
What kind of Data has been involved in our Case Study? Customer data is considered to be a Master data, Contract data is usually classified as Transactional data. Business rules are also some sort of data, which usually defined as Meta-data (data about data).
So, on our journey to define Data owner we need to take into consideration several contexts:
- Data ownership (taking into account its different types: Reference and Master data, Transactional Data, Metadata);
- Data lifecycle;
- Data governance;
- Data in Systems & Technology.
Which roles are recognized in data-related area and why?
You might become lost as there are plenty of Data-related roles described in different sources. I came across Data owners, stewards, users, providers etc. I was always curious: if I were a person who has to play several roles simultaneously, would I get a A4 paper with clear description what I have to do on a daily basis?
I think one of the reasons for such a variety of functions, is that the creators of these functions do not put them in the relevant context (like the four, that we have just identified above).
So, let’s us concentrate only on the context of Ownership and let’s us continue with the Customer and Contract data example.
How to spot a Data owner?
We all know that it is difficult to find volunteers within your company who would say ‘I am a Data owner’. How can you prove that somebody is actually a Data owner? Years ago, while setting up Data ownership responsibilities within a company, we developed a list of questions that helped in Data ownership recognition. Some of them are presented below:
- Who can verify the accuracy (correctness)  and completeness  of the data?
- Who runs the biggest operational risk when the data is not correct?
- Which department would act differently when data defies expectations?
- Can the ownership be directly deduced from a department’s responsibilities?
- When there is more than one department that matches in the above sketched profile, which one wins?
Now I am convinced that the solution is quite simple. There are two unambiguous ‘recognition’ criteria for a Data owner which are an ability and an authority to:
- verify accuracy and completeness of the data
- manage the data
One small detail (where the Devil is): these rules are applicable for unchanged data. As soon as data has been transformed it might change an owner.
Let’s get back to the Case Study to get a clear picture.
Customer data (name, address, country of residence etc.) stays unchanged till it reaches FP&A department. So, if you as FP&A professional discover some mismatch or finds that the data is not fully complete, what will you do? Who will be able to verify accuracy and completeness of the data and fill in gaps? As for me only one answer is possible: The Account officer is the Data owner.
Contract data, such as e.g. the contract amount might stay unchanged till it reaches FP&A department. And it still the Account officer who might verify the accuracy of the contract amount. But let’s assume that you will need to convert the amount into another currency, decide which exchange rate to apply or aggregate the data according certain rules… What does it mean? From the moment when these data transformations take place, you, FP&A professional, become the data owner. The same rule is applied for the rules that you might apply to transform data, because these rules are also data.
What is a Data owner responsible for?
I will offer some general responsibilities for your consideration, but I need to warn you that these responsibilities might vary for each company. Why? The responsibilities are dependable on the size of the organization and overlap with responsibilities of other roles that might exist (such as System owner, Business process owner etc.).
So, a Data owner is accountable (based on RACI) for:
- correct and thorough completion of a data-related deliverable or task;
- definition of Data: what information is to be brought into a system, assigning the meaning to collection of data, data definitions;
- Authorization of Access and Validation of Security;
- Maintenance of data, including managing the data input process and data quality;
- Data supply from third parties;
- Data quality, including setting up requirements and maintaining data quality;
- Management of business rules;
- Archive/ Remove/ Delete;
- The correct execution of these procedures. Execution itself can be delegated to other business functions.
I hope that the article provokes more questions and arguments that I would like to discuss with you. Feel free to contact FP&A Board and me if you want advice on how to apply these concepts within your company.
 DAMA Dictionary, p.66
 Accuracy is freedom from mistake or error, conformity to truth or to a standard, exactness, the degree of conformity of a measure to a standard or true value, DAMA Dictionary, p.12
 Completeness is the quality of being whole or perfect and having nothing missing, Cambridge Dictionary [http://dictionary.cambridge.org/dictionary/english/completeness]
For progressive and competitive organizations of all sizes, accessing smarter, leaner and faster information to drive a successful business strategy can only be achieved with real-time insights into their customer’s needs and buying behaviours.
Identifying and building ‘products of the future’, before you customers even realise the need, can mean the difference between long-term success and overnight failure – Nokia and RIM (Blackberry) are two examples of market leading companies who failed to prepare for the onset of handheld computing, Apple took the reverse approach, the rest is history.
Advances in predictive and analytical software are facilitating a huge competitive advantage for many companies who recognise the value of using big data to look into the future using ‘precognitive’ technology. But, for many organizations, FP&A analytical transformation remains out of reach for reasons including a lack of preparedness and a business culture that’s become risk adverse from the failure of historic technology investments to deliver the transparency needed to drive a successful strategy.
The World Trade Centre, Amsterdam and Cercle de Lorraine Club van Lotharingen, Brussels welcomed some of the brightest minds in Financial Planning & Analysis (FP&A) to discuss that very topic at both cities’ second FP&A Board roundtables, organized by Larysa Melnychuk (MD of the FP&A Trends Group).
Agenda for the evening:
FP&A Analytical Transformation – what does it mean for organizations and are we ready for big data analytics in finance?
Both sessions welcomed Thomas Lundell, Director of FP&A & Business Control (EMEA) at NetApp, creators of innovative storage and data management. Thomas presented NetApp case study "FP&A Transformation: Becoming Agile, Adaptable and Predictive" which detailed his personal and corporate business journey in transforming FP&A through technology investment.
I asked Thomas what he believes to be the major advantage Analytical Transformation can provide for an organization and how do senior FP&A professionals best relay that advantage when trying to secure investment buy-in from organizational heads. Thomas says:
“There are two main advantages to undertaking an Analytical Transformation for FP&A, both of which certainly will secure investment buy-in from leadership.
First, it improves the speed and quality of decision-making. Business is increasingly dynamic and fast moving. Business executives need to make large-scale, complex decisions within reduced time frames. Going through an analytical transformation will enable FP&A to provide both predictive and prescriptive analytics that will enable executives to make better and quicker business decisions.
Second, it enables FP&A to create an integrated business plan that links up all the functions within the organization and that can capture market opportunity in an efficiently coordinated way. By going through an Analytical Transformation, FP&A can move from doing traditional budgeting and forecasting, to creating integrated business plans that link investment allocation with business unit strategy.“
Discussions broached the matter of how analytical technology can tick the wish lists of many Senior FP&A professionals including:
- Fully integrated business planning
- Empowering business partners to become the real owners of their strategic inputs
- Maintaining agile and relevant projections in dynamic, fast-changing markets
- Automate traditional budgeting and forecasting process to free up resources to ‘look into the future’
- Access to real-time data around business ‘Wins’ and ‘Opportunities Lost’
- Long-term business planning
- Risk modelling & mitigation
- Zero-based budgeting
- Converting top-down planning into success
- Driving ‘Stretch’ to facilitate growth
Both groups addressed the readiness of many organizations in embracing the value-add of analytics transformation and the challenges, which continue to obstruct its advancement even within some of the largest, most successful businesses in the world.
- Lack of investment in analytics technology
- Lack of investment in professional development to help attract, develop and retain the best talent with the right mindset
- FP&A staff buried in day-to-day accounting tasks, restrained by legacy processes and systems now ripe for automation
- Rigid business thinking
- Selecting the right data from a huge pool of options
- Absence of a universal business appreciation of technological capabilities
- Encouraging business partners to ‘speak the same language’
- Turing insights into action
Regulatory changes such as the arrival of the International Financial Reporting Standards (IFRS) 9, who’s enforcement has been delayed until 1 January 2018, may also be fostering a reluctance to prepare, even if just as a resistance to the core principles of the new standard.
Access to quality data and the flexibility to make decisions quickly by utilizing that data to predict the future, remains the FP&A holy grail of business strategy.
“Advanced analytics is the extensive use of data, statistical and quantitative analysis, explanatory and predictive models and fact-based management to drive decisions and actions” Thomas H. Davenport (Professor of IT & Management, Harvard)
But analytics tools are only useful if you know where your data is coming from and there is a solid confidence in its integrity. Asking sometimes uncomfortable questions should be a prelude to any investment decision, learning from past mistakes can be illuminating.
How companies chose to use the outputs of analytical technology was another strong discussion point. Process and systems can predict an outcome but the million-dollar question is Why? By understanding why data is showing a particular trend, companies can focus on what the customer wants in the future and how best to deliver the solutions, which provide an organizational competitive edge.
Treating data as a strategic resource is vital for success, how ownership of that data is structured is no less important. Imagining a different world and reorganized business model, which can better meet the demands of a digital age, may for some organizations, prove a prerequisite to the transformation journey for FP&A.
“Part of making good decisions in business is recognizing the poor decisions you’ve made and why they were poor” Warren Buffett
All business partners should have a natural vested interest in their businesses data resources through both individual inputs and strategic output but who should be the custodian of that data? General consensus leans towards those who can apply science to the data. FP&A offers the process, financial acumen, a grounded approach to forecasting and the hard and soft skills required to maximize benefit from a ‘closed loop’ position which benefits the business at large.
Skill gaps twinned with a sometimes mañana approach to the professional development needed to attract and retain the best and brightest FP&A talent continue to hamper advanced thinking. Empowering finance professionals to think outside the box and paint a picture of tomorrow fuels the dynamism, creative thinking and collaboration required to achieve and maintain a competitive advantage.
Creating a common language and understanding through education and training is a great place to start and a critical accompaniment to change management, allowing staff to grow and develop within their new roles and business structures. After all, human collateral will remain our most valuable asset until and if, we achieve singularity!
But given the obvious advantage advanced analytics can bring to a business, I asked Amrish Shah (Snr Finance & Operations Director PvH NL & MEA at PvH Europe BV) what he feels is the main obstacle to investment in analytics technology that senior FP&A professionals are experiencing within their organizations and how do they work to overcome these obstacles:
"……….Tackling the obstacles of organization readiness and risk adverseness to technology investment, both these challenges require a far greater investment in people. With the right experience, mindset and attitude (one of learning and experimentation) both internally and externally and ensuring that information management is seen as a strategic resource that has to be planned for and tackled as such, professional development needs to be on the rolling agenda of every management team and Board".
There is no dispute analytics technology improves the speed and quality of an organization’s decision-making.
Transformational business journeys including the move to advanced analytics are evolving projects that don’t and shouldn’t have a final end point. They need to be agile and operate around new drivers for the future - one size does not fit all. It’s a very personal journey, unique to individual businesses.
FP&A is leading the charge but they should avoid any attempt to make the journey alone. The relationship between senior finance professionals, CTO’s and CIO’S must be at the heart of this process to ensure a holistic view of the business, its needs and and the task at hand. Choosing to ignore or simply delay embracing the value-add analytics technology can bring to your business and its position within the competitor landscape is a no brainer. We simply can’t ignore the march of progress.
Many thanks to sponsors and partners of the FP&A Board events: The Association for Financial Professionals (AFP), provider of international FP&A Certification and finance training. Page Group, global recruitment firm and Tagetik, leading FP&A Technology company.
Copyright © 2017 Association for Financial Professionals, Inc.
Financial Planning & Analysis (FP&A) is gaining more and more attention from business leaders. Its focus is the future of the business. It uses past and actual (big) data to effectively model or support the decision-making, and can timely impact the business focus. The FP&A professionals who work as Finance Business Partners understand basic accounting and reporting, yet their strength is in being from different ‘walks of life’.
FP&A Trends led by Larysa Melnychuk is promoting FP&A worldwide. Their partners/sponsors, PageExecutive (or here), FP&A/Association for Financial Professionals (or here) and CCH Tagetik (or here) are actively participating during presentations, which is rare but great. It demonstrates their commitment with business leaders to create a pool of knowledge and establish a network of professionals adding value to the business.
In Amsterdam, FP&A Trends and partners/sponsors organised another FP&A Board meeting, the subject: Rolling Forecast. Below is a review of a short presentation I gave at this FP&A Board meeting.
What is the purpose of a Rolling Forecast?
By presenting 3 different cases, you will get an idea of the range of possibilities a Rolling Forecast can have for the business. Since you can do anything with the financial software of today, finding a purpose of having a Rolling Forecast becomes essential for success (= implementation + adding value).
Case 1: Supply Side – Working Capital Management
The first case is about a family business, importing raw material from different countries around the globe and always selling everything they produced. They are a low-cost producer and competition is fierce. With a 24/7 production line, as soon as a machine stops, money is lost.
The Rolling Forecast was developed in 4 steps.
- Cash Management. The financial forecast was based on Account Receivables and Account Payables, making it just a treasury tool. Not insignificant, when F/X rates are volatile and inflation is 7%. However, working with a standard sales price and estimated sales discounts wasn’t telling the business story.
- Involving the Supply Chain. The finance manager started to involve procurement: lead times of 60 days, rates and dates on L/C and F/X contracts, suppliers ‘cancelling’ purchase orders because they sold the material to a higher bidder (without telling), and strikes and fiscal complexity at ports. Thorough knowledge of these operational risks improved the quality of the financial forecast, moving towards a Rolling Forecast.
- Adding the algorithm. With the warehouse being fully stacked (roughly minimum inventory level of 70%, because of unmanaged supply chain risks), an algorithm was developed to start predicting the real material usage. It was ‘discovered’ that when equipment was slowed down, the quality of the material would increase. This created a business opportunity: higher quality of output, although at a higher cost, leads to premium pricing. If inventory is running low, due to supply chain problems, machines wouldn’t have to stop producing. The algorithm and sales network made it possible to reduce the minimum inventory level to roughly 25%. Free cash!
- Involving ‘fashion’. Now, with the possibility of premium pricing, dyeing became a strategic ‘fashion’ choice. Premium products are being sold to a different segment, with a different taste in colour.
In the end, a Rolling Forecast of 3 months was updated daily. Having outsourced the dyeing of low-cost products, money was invested in new equipment for dyeing high-quality products. The equipment was placed at one of the preferred dyeing partners. This selected horizontal integration off-set various cost disadvantages (e.g. occupation rate, environmental license, lead time).
Case 2: Start-up – Funding
When the government opened the telecom market, multiple tenders were being developed. A start-up was set up by a foreign corporation. They organised an engineering team to be trained in the latest hardware from the supplier, to develop backbone technology solutions, and ‘helped’ to develop the technical specifications of the tenders (like all competitors did). The installation would be outsourced.
A start-up in a tender market has no revenues, only spend. This means either capitalisation through equity or through an (international) inter-company loan. In a turbulent political and economic environment, the latter can be preferred. The choice became more important once tenders were being won.
This start-up was winning most of the tenders. The share price of the corporation increased with each deal won. Cash needs increased rapidly since payments only occurred when specific milestones were achieved. Any delay in client approval at a milestone would result in a fine. Knowing that the profit margins on each tender were low, profit to the start-up (and the supplier) would have to come from services (post-installation) and network/capacity expansion contracts.
In the end, with each tender won, and using the milestones from the project plan, updating the Rolling Forecast of up to 1 year was easy. When the tender market ended, the start-up was sold. This for sure would have secured the IRR established by the corporation. Like most corporations, they weren't in the business of selling products, but selling businesses.
Case 3: Fortune-100 – Management Support
This corporation depended on R&D and M&A. Patents secured client loyalty. Local business units were mainly Marketing & Sales operations, functioning as ‘cash cows’. The command & control culture focused on permanent cost reductions, outsourcing, or the centralisation of functions at HQ. In recent years, several projects of FP&A had failed to capture and involve the local business units, due to being time-consuming and overly complex. In addition, there was no clear added value to spend (a lot of) time on highly detailed FP&A.
The business controller at a local business unit saw there was an information need towards the region. The ‘fear’ of losing information between HQ and local business was being managed through multiple, stand-alone reports. Local marketing managers were spending a lot of time on financial planning and monitoring the actual bookings of spend. Not their task!
The solution resulted in a single report, generating an automated SKU planning, based on current product mix%, an automated monthly, quarterly and year-to-date P&L’s, and many more, all combined into one Excel file. However, only the first sheet was ‘interactive’. It contained (among others) the following:
- Sales: Last Year; Budget; quarterly reported Estimate of Actual Year; the monthly Actuals.
- Outlook: Rolling Forecast of Actual Year, based on an algorithm from finance; Rolling Forecast (*) of Actual Year, based on the expectation of the marketing manager; short-term Risks & Opportunities (*), which included actions, impact on sales, spend and operating profit.
- Forecast: Long-term Risks & Opportunities (*), which included actions, impact on sales, spend and operating profit; multiple year sales forecast; the extended Rolling Forecast (*) of the Next Year.
(*) Discussed and adjusted monthly.
Here, the Rolling Forecast starts as a 24-month forecast. Each month the projection would be one month less. A risk or opportunity impacting Next Year figures, would automatically be processed in the Rolling Forecast, updating the business plan for the coming year. Transparency and no surprises!
In the end, setting up the Rolling Forecast and centralising the reporting through one Excel sheet (the other sheets are automated), proved to be the most efficient and effective solution. For each product line, the marketing manager would be spending only 1 or 2 hours per month on business planning and FP&A with finance. It involved an algorithm and human input, quantitative and qualitative information, backwards and forward-looking data, relevant ratio's, and detailed (SKU) and meta (P&L) data.
With a Rolling Forecast, business focus gets constantly being reviewed by management and effective action can be taken immediately. As such, a Rolling Forecast drives business change. When considering a Rolling Forecast:
Thanks, and enjoy the future!