Emmanuel Jibodu

Emmanuel sees planning, analytics and forecasting as “more about processes and people” believing that the best planning and forecasting results from a drive to understand every aspect of how a business runs – business model and how value is created for customers. Emmanuel possesses diverse experience in strategic finance planning, analytics, mergers/acquisitions and corporate finance. 

He is passionate about building FP&A teams that deploy lateral thinking to solve problems for organizations that are looking to accelerate their growth trajectory. His career experience entails adding value in publicly traded Canadian high growth software (SaaS) companies and staid industries – such as manufacturing and environmental services. He possesses an accounting degree from the Schulich School of Business at York University and an MBA from Wilfrid Laurier University.

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Does Data Science & Business Analytics Really Transform Enterprises?

By Emmanuel Jibodu, Finance Analytics @ Shred-it​

Much has been written about the preponderance of data that enterprises have access to in today's business landscape. This is the first part of a three-part series on the business value that data science and analytics can provide to enterprises.

In today's uncertain macroeconomic, geopolitical, legal, and competitive landscape, where 100-year old business models have become defunct, data represents a veritable goldmine to enterprises in their quest to grow revenues and manage their costs. Some posit that all enterprises, today, are in the technology industry because digitization is disrupting every industry whether it's retailers, taxis, tractor manufacturers, banks, insurance companies, or other staid industries.

Autophagy, a metabolic process in mammals — whereby cells dissemble and remove their dysfunctional components. As a result, it yields anti-aging effects and reduction in inflammation for the human body. This is analogous to enterprises with poorly executed strategies; ill-conceived product extensions and launches; ill-considered business models that face shakeouts in today's business environment.

Today, the Office of the Chief Financial Officer (CFO) is commonly at the forefront of leveraging the treasure trove — that is data to enable an enterprise to thrive in today's globally-linked business environment. Under this remit, within the Office of the CFO, lies the Financial Planning & Analysis (FP&A) team, which emerged in the last few years to link the executive team's strategy to financial outcomes; act as the analytics hub for the enterprise due its unique vantage point — it supports different internal groups — marketing, sales, operations, R&D, etc.; operate as a sounding board on decision making across the organization in order to ensure an enterprise follows a disciplined capital allocation strategy. In various countries across the globe, FP&A is known as corporate performance management, business performance management, finance business partnering and even business controlling.

The skill of an organization's leaders at investing the capital of its owners (shareholders or private-equity investors) can have as much influence on future returns as the economics of its assets (patents, plants, equipment, customer data). Do the leaders of an enterprise have a track record of delivering best-in-class returns from its assets, or are acquisitions, research and development activities, product launches hit-or-miss?

Data science & analytics lies at the crux of a disciplined capital allocation strategy whereby data can be harnessed to ensure that leaders execute initiatives that increase enterprise value. For publicly traded companies, it is commonplace for activist investors to have opposing ideas regarding the strategy deployed by the C-suite. A disciplined capital allocation strategy corroborated by best-in-class data science & analytics initiatives will enable CXOs confidently defend their strategies, business models, or ideas when they are questioned, or even lampooned by activist investors.

A study by MIT showed that enterprises with data-driven decision-making environments had 4% higher productivity and 6% higher profits than the competition. Over the short-term, 4% higher productivity might not appear to be significant. But over the medium-term and long-term, this productivity gains would cause significant disparities between industry participants due to the power of compounding.

Data Science and analytics involves, but is not limited to, the sub-branches identified below:

  1. Core Business Analytics
  2. Machine Learning (ML)

Core Business Analytics: This has its origins in business intelligence (BI), the use of online analytical processing (OLAP) software tools, data mining, and the analysis of multidimensional data. Analytics, simply, involves leveraging mathematical equations and algorithms, or even statistical models to understand, explain, monitor, forecast, and influence business performance. The four core areas of business analytics include: 

  • Diagnostic analytics - what happened?
  • Descriptive analytics - why did it happen?
  • Predictive analytics - what is going to happen? 
  • Prescriptive analytics - what can we do to achieve our targets or course correct? 

Machine Learning (ML). This is not a new concept — the term has been around since 1959. It involves software applications that can recognize patterns. Based on data, and algorithms, the software application recognizes patterns and produces an outcome.

Eventually, the application gets to a point where there is enough information and history that it makes changes to the algorithms automatically, without being programmed by humans. At this point, the application can infer new knowledge. That is, the ML model leverages statistical models to infer correlations, anomalies, and trends in data. Within the finance function, it can be as simple as processing things in a back office — for example, telling you whether a billing error has occurred. 

When an organization decides to apply machine learning tools in its business processes, first and foremost, it is important that process owners develop stringent evaluation criteria about how performance will be measured. Examples of machine learning tools that can be applied include regression analysis, classification, clustering algorithms and similarity algorithms.

Today, machine learning tools have become commercialized to a greater degree and can be deployed speedily by enterprises because they are available as software-as-a-service (SaaS). An example of a machine learning solution is IBM's Watson Machine Learning. 

Critics of machine learning will posit the instances of false positives that ML algorithms could provide. Of course, the larger the historical data fed into an ML model, as a sample set, initially, the lesser the chance the model will produce false positives.

Sampling data is still very important today. Because the storage of data is not free — we cannot save and process all the data relevant to a subject matter. Memory and computing power are also not free. The combination and convergence of these factors ensure that data sampling is relevant today. 

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Two Points At Which Controllership And FP&A Diverge

By Emmanuel Jibodu, Finance Analytics @ Shred-it

The inspiration for this article stems from a recent conversation on a Financial Planning & Analysis (FP&A) LinkedIn group that I'm a member of. A highly regarded FP&A professional posited that we discuss the differences between the controllership function and FP&A. This post will highlight a couple of differences from an FP&A practitioner's perspective.

CFOs, historically, cut their teeth in Controllership, FP&A, and Treasury before their ascension to the CFO role. Today, in most large corporations, the controllership function and FP&A have been bifurcated; they operate as two separate teams and have different mandates. The controllership function, nowadays, reports to the Chief Accounting Officer, while the FP&A function reports to the Chief Financial Officer (CFO). Itemized below are 2 main differences between Controllership and FP&A you will notice in the Office of Finance for most world-class organizations.

1. Ethos

•    Historical vs. Forward-Looking
•    Compliance vs. Exploratory
•    Cost Control vs. Top Line Growth

2. Data 


1. Ethos

The guiding principles of Controllership and FP&A functions can be subdivided into three categories:

Historical vs. Forward-Looking

Controllership involves the accurate preparation of financial statements based on past periodic, quarterly, and annual financial performance. Financial reports are used by senior leadership to evaluate the performance of an enterprise or business unit. Investors use financial statements to gauge the performance of senior executives and whether the strategy adopted by a company's C-suite is successful. Creditors use financial statements to determine whether an enterprise can take on additional financing or has violated debt covenants.

Although the FP&A function sometimes gets involved in the historical analysis and reporting of trends in key performance indicators (KPIs), the bread and butter of FP&A work are predictive. FP&A offers senior leaders insight into the future financial position of an organization; this is done by leveraging statistical/data analysis - for example, multiple regression, moving average methods, what-if analysis, etc., performance indicators, macroeconomic indicators, and business intelligence systems to forecast the operational and financial performance of an enterprise. The forecasts FP&A teams provide senior leaders help guide: (a) resource allocation such as personnel, capital allocations, and investments (b) the rarefied circles of Wall Street and manage "street expectations."

Compliance vs. Exploratory

Financial statements must be in compliance with tax laws, IFRS, US GAAP, Sarbanes-Oxley (SOX). The remit of the controllership function is to capture the economic reality of the company's performance to the last cent (or dollar). When capturing items such as depreciation, amortization, impairment, pension obligations, revenue, leases, research & development costs, the controllership function cannot deviate from the guidelines or rules that IFRS or US GAAP provide them.

There are certainly best practices that are adopted by most FP&A teams, however, FP&A practitioners can explore different analytics methodologies and procedures for their assignments in the areas of planning, forecasting, budgeting, and ad hoc analytics. For example, there are a couple of methods an FP&A professional can deploy when tasked with forecasting sales for a software company. Traditionally, software companies have significant forecasting risk due to their inherent high operating leverage, as a result of their significant personnel costs. To forecast revenues for the next 5 quarters, he or she could analyze the number of request for proposals (RFPs) submitted per quarter per line of business (licenses, consulting), by product line, by geography, by target market (government, health care), - then this metric is forecasted for next 5 quarters. See formulas below to determine: New License Revenues per quarter.

Hence, he or she has to explore several dimensions during the course of the analysis. It would also be prudent for FP&A to model different scenarios for the sales forecast. For example, competitive pressures could cause the company to lower prices on their products and services - causing the average dollar amount per deal to decrease in future quarters. Alternatively, to produce a sales forecast, the FP&A professional can use historical data to forecast total sales using an exponential smoothing model.

Cost Control vs. Top Line Growth

An FP&A function that does not deliver financial insights that lead to enterprise sales growth is likely not delivering the return on investment (ROI) that senior leadership expects. Sales growth, among other financial indicators, is a sign that Wall Street examines when analyzing a company's performance. I imagine the conversation between a Controller and an FP&A Director at a cocktail event would go something like this:

FP&A Director: Hi... What a great event, isn't it...How was your year, at work?
Controller: Excellent! Our team saved the company a lot of money...by controlling our expenses in admin...and direct costs as well. Our expenses came under budget for the first time in 3 years... How was your year?
FP&A Director: We had a great year as well. We provided the CFO with insight into a market entry opportunity for our company... by acquiring the #3 company in Europe for our industry. We are expecting this deal to be accretive to Cash earnings per share (EPS)...by at least 12.3% over the next 3 years...Importantly, we're anticipating revenue synergies that will enable us to be the #2 company in our industry in the next 2-4 years...in terms of global market share.

2. Data

The Controllership function mainly uses internal financial data that stems from Enterprise Resource Planning systems (ERP) to accomplish their objectives. Journal entries are posted to the General ledger system, the trial balance is prepared, adjusting entries are recorded (if needed), accounts are closed, and financial statements are prepared.

FP&A teams use both external and internal data to accomplish their objectives. For example, to develop a sales forecast for a software company whose clients are large corporations, FP&A would have to consider external macroeconomic indicators (i.e. leading indicators) that impact sales performance, as a variable. These indicators could be GDP growth and durable goods orders.

The Controllership and FP&A functions are two important components of any high performing organization, they have different mandates, however, they speak the same language, the language of numbers.
Comment below if you are a controller, member of an FP&A team, or treasurer and share your own professional experiences.

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How to be a Higher Performing FP&A Business Partner in a SaaS Enterprise

By Emmanuel Jibodu, Finance Analytics @ Shred-it​

Today, software as a service (SaaS) businesses are popular with investors, lenders and customers. Many software companies have transmuted their pricing models from perpetual license models to subscription models. 

As a result of subscription models, enterprises now possess vast troves of data (customer, operational and financial). Finance business partners, within the Office of the CFO, are charged with proactively interacting with different enterprise teams.

Finance business partners are important in subscription environments. A finance business partner’s role, in the Office of the CFO — is to be a consigliere to a leader of a function such as a sales leader, marketing leader, product leader, and, even, a business unit leader.

FP&A Business Partner needs to answer five questions

Finance is pivotal when making the right decisions in a SaaS company. Identified below are sample questions an FP&A business partner can help answer to accelerate the growth trajectory in a SaaS enterprise:

1. Is there a poor product-market fit? 

Why is this important? It is common for SaaS companies to enter a new market with a product expansion targeted for that market. However, in some cases, product expansion might be ill-suited for the new market. For example, a SaaS company that provides data integration, data management, cloud storage and integration software for large enterprise customers releases a product offering targeted at mid-sized enterprises. If sales are flailing with higher than anticipated churn rates, poor renewal rates, a finance business partner can calculate the customer acquisition cost (CAC) to acquire mid-market customers and notice that these customers are churning out four months after break-even point. As a result, customer lifetime value below optimal levels. 

Additionally, the finance business partner then triangulates with the go-to market organization or product team to assess if the reason for higher than expected churn is due to product functionality or design issues, service level agreements, pricing, or, simply poor product-market fit. By adopting a client services approach, the finance business partner provides visibility, from a unit economics standpoint, to support decisions on a go-forward basis.

2. What is an appropriate amount to charge a prospective customer for a 3-year contract?

Why is this important? With many software companies operating subscription models, the discount applied for SaaS deals in comparison to perpetual license deals are lower because software companies bear the burden for hosting in SaaS deals. Furthermore, discounts can vary based on deal size. As a result, pricing can vary based on contract lengths, product bundling and subscription levels. 

The pricing model for SaaS companies is critical because the closure of the initial deal—provides an entry point for subsequent deals, expansions, renewals, and customer lifetime value maximization. Finance business partners are instrumental in deal structures and leverage their commercial acumen to develop pricing models with a discount factor based on a deal’s specifics. 

3. How can we assess the strength of our customer relationships? 

Why is this important? It is common for SaaS companies to periodically evaluate the net promoter score (NPS) to assess the strength of their current customer relationships. NPS is an important metric widely used in many industries. However, in my experience, it does not tell the comprehensive story when a SaaS or PaaS company wants to measure customer’s delight with their products. 

A better indicator of the stickiness of a customer relationship is the evaluation of Cohort curves. A finance business partner proactively provides insights to sales and go-to-market leaders by leveraging cohort analysis. Upward sloping revenue cohort curves—annual recurring revenue for customer cohort in year 1 versus annual recurring revenue for the same customer cohort in year 2. 

Recurring revenue cohort increases from one year to another represents an excellent indicator of — great product-market fit, healthy return on investment (ROI) for sales/marketing investments and sticky customer relationships.

It is more expensive to acquire a new customer than to, upsell or cross-sell a current customer. Furthermore, from a unit economics standpoint, every incremental dollar of revenue expansion from a current customer is more profitable than incremental revenue from a newly acquired customer because of the costs (sales/marketing) incurred to acquire a new customer. 

These sales and marketing costs comprise costs to identify potential customers, nurture prospective customers through various stages in the sales funnel—from marketing qualified leads to sales qualified leads, and, finally, to deal close. For a SaaS company to circumvent making significant sales/marketing incremental investments to acquire new customers, it needs to develop a robust program that enables current customers to refer new customers. 

4. Who is the ideal customer for our product? 

Why is this important? From a unit economics perspective, it is imperative that sales and marketing investments be optimally allocated to maximize customer lifetime value. That’s why I’m a big fan of identifying an ideal customer profile for a SaaS business. 

You can always deploy qualitative frameworks for identifying an ideal customer, however, quantitative measures provide justification to this process as well. I’m passionate about leveraging data to help drive capital efficiency in this area and utilizing associative analysis, cluster analysis and other statistical methodologies to uncover the profile of an ideal customer. By leveraging data on current customers in enterprise systems and employing cohort analysis, we can perform the following:

  • Product purchases of current customers—for example, how many products did customer purchase: 1,2,3 or 5 products?
  • Product utilization—are customers using the products they purchased? If not, this provides early warning signs about renewal rates
  • Payment history of customers
  • Support tickets generated by customers—profile and volume
  • Segmentation by ARR bands

5. How do we assess the productivity of our salespeople? 

Why is this important? After the identification of strong product-market fit, SaaS enterprises employ salespeople, or account executives (AE) to facilitate the acquisition of new customers.  An enterprise’s ability to predictably determine its ability to grow and scale efficiently is inextricably tied to how quickly newly hired account executives ramp. The ramp period could be 3 months, 6 months, or 9 months, after which the new salesperson is expected to be at a certain ramp attainment rate or success point. 

If new sales hires are consistently achieving an expected ramp attainment point, it provides a feedback loop that—the product meets the need of its market better than the competition, sales enablement and marketing are working well, and hiring criteria for new sales hires is excellent. A finance business partner who is supporting the SaaS enterprise’s Head of Sales or Chief Revenue Officer (CRO) harnesses this data and provides recommendations on sales efficiency.

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Building a Financial Planning and Analysis (FP&A) 4.0 Team

By Emmanuel Jibodu, Finance Analytics @ Shred-it

We are in the 4th wave of the Industrial revolution.

My aim in this article is to proffer suggestions for assembling members of an FP&A team. This is the team that will ensure an enterprise is resilient enough to navigate competitive threats, technology disruptions, regulatory effects, and can adapt to broad market dynamics in this 4th wave of the industrial revolution. 

It is common for me to receive questions from people wondering -

  • What makes the ideal background for an FP&A professional? 
  • What skillsets will make a person successful as an FP&A professional? 

My retort most times is indefatigable curiosity

Curiosity is the underlying attribute that delineates successful FP&A practitioners from each other. Since FP&A is both an art and science, there are no specific rules or methods that can be applied to FP&A work, in contrast to accounting and its international financial reporting standards. 

In FP&A, someone who is intellectually curious will be able to ask the right questions to internal clients, be it executive or senior management. Furthermore, such an individual will be scrupulous when unearthing levers that drive business performance; analyze the root causes of performance trends, and recommend robust prescriptive and predictive insights that give rise to revenue growth and optimal allocation of finite resources.

Building an Effective FP&A Team

It is my opinion that a best-in-class FP&A team should comprise members from different disciplines. These disciplines could include Accounting, Corporate Finance, Physics, Mathematics, Social Sciences, Engineering, Biology, and Chemistry. 

This might come as a surprise to some because, traditionally, most FP&A teams are comprised of individuals with backgrounds in accounting. In the last 5 years, the Office Of Finance has been charged with playing an integral role in the strategy execution process. What excites me about the Office of Finance today is the remit that has been given to the FP&A arm. FP&A is charged with providing recommendations that serve to:

  1. Increase the enterprise value of an organization
  2. Uncover new market opportunities, for example, a new vertical or geographic market
  3. Allocate staffing and capital resources to accelerate growth trajectories
  4. Own and refine the business model or revenue model
  5. Recommend levers for executives to pull that cause the achievement of short term and long term objectives
  6. Proffer methods to increase an organization’s share of its customer’s wallet

The above-listed remit which comprises of areas that were previously reserved for marketing departments, strategy teams and even consulting firms are, now, in the purview of FP&A teams. As a result, to tackle unsolved enterprise growth/profitability problems, a best-in-class FP&A team has to be interdisciplinary. 

The Composition of an Effective FP&A Team

Listed below are traditional and unconventional backgrounds and skillsets that an effective FP&A team should comprise of:

  • Accounting. This is a traditional background for many FP&A practitioners. An accounting designation, public accounting experience in a specific industry (e.g. financial services, consumer products, healthcare, etc.) are table stakes for these professionals. Furthermore, these team members possess well-honed skills in accounting research, tax, performance measurement and management, budgeting, financial reporting, risk management and internal controls.


  • Corporate Finance. This comprises of finance professionals from corporate finance, treasury, management consulting, investment banking, and private equity backgrounds. Often armed with an MBA in finance or strategy, these individuals possess extensive experience in building financial models and providing recommendations on seismic events that impact a company’s growth trajectory – for example, an initial public offering (I.P.O.), sale of a portfolio company, or even the acquisition of a competitor.

These individuals are well-versed with understanding business models, strategy, revenue models, competitive threats, performance benchmarking, economic factors and broader market dynamics that face an enterprise. 

For example, an important part of an enterprise’s business model is the cost of acquiring a new customer. It is typically costlier for an organization to acquire a new customer than to retain an existing one. As a result, an FP&A team, for example, in a Software-as-a-service (SaaS) environment could be charged with optimizing Customer Lifetime Value (CLTV) from a customer segment.

CLTV represents the total revenue derived from a customer over the life of the relationship. There are various methods for calculating customer lifetime value, however, in sidebar #3, I have identified the fundamental calculation for CLTV.

The understanding of an enterprise’s business model also aids in the effective design of management reports. The layout of a management profit and loss statement, for example, for internal reporting purposes across an enterprise can be designed by the FP&A team based on organization’s business model. This determines the order and arrangement of revenue streams, expense line items and the selection of key performance indicators. Furthermore, as a result of developing countless proposals and presentations for executives, these professionals possess well-honed skills at presenting financial/non-financial information to meet the needs of various end-users. The ability to present financial/non-financial information to executives (CXOs), business unit leaders, and non-finance departments is an art that facilitates decision making at the strategic, operational and tactical levels.


  • Marketing Strategist. Marketing strategists are usually well-versed in the commercial side of an enterprise; typically, they come from the Office Of The Chief Marketing Officer (CMO). If these marketing strategists add skills such as model building and an analytics mindset, you have FP&A team members who can accurately define the impact of a company’s product or service roadmap in relation to its go-to-market (GTM) strategy, digital marketing strategy, sales funnel optimization, search engine marketing, and brand management. Such team members can partner with marketing and sales teams to unearth insights related to optimal customer acquisition costs (CAC). 

For example, in a SaaS enterprise, team members with marketing strategy backgrounds can possibly unearth insights from customer cohort analysis related to customer data multidimensionally by analyzing: customer trends by marketing campaign; churn trends by customer segment; customer trends by sales representative; customer trends by customer success representative to inform decision making on the optimal ratio of customer acquisition cost to customer lifetime value. The end result is better decisions on pricing model changes; product redesign; customer churn reduction; redesign of how external customers are serviced; and savvy decisions on partnerships and strategic alliances.


  • Natural Sciences. Physics, Biology, and Chemistry seek to describe the nature of the physical world and involve the study of atoms, molecules, chemical reactions and components of the universe. Natural sciences such as Physics demystify impalpable areas in the universe. In a sense, Physics is a general approach to problem-solving, but at its core, it provides a handful of basic mathematical principles that can be leveraged for a lot of situations. 

Branches in physics, such as statistical mechanics, can be leveraged by FP&A professionals that are well-versed in it for algorithm development and deployment, statistical modeling, and the underlying processes for leveraging machine learning (ML) models when forecasting revenues and expenses. Due to what is commonly termed, today, as The Fourth Industrial Revolution - the convergence of big data, artificial intelligence, ubiquitous computing power, smart factories, and robotics - the big data load for FP&A teams to leverage is multitudinous. FP&A teams that are able to design effective techniques for the governance, exploration, processing and analysis of the vast troves of data at their disposal to engender improved financial outcomes will be lauded by executives for creating value and driving competitive advantage. FP&A teams that leverage natural science principles for advanced analytics can assist executives identify the levers to pull for revenue growth, cost optimization, cash flow improvement and margin expansion.

Other disciplines that serve as suitable backgrounds for FP&A that were not expatiated upon in this article include Social Sciences, Engineering, Mathematics, and Computer Science.

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Author's Articles

March 11, 2020

Today, software as a service (SaaS) businesses are popular with investors, lenders and customers. Many software companies have transmuted their pricing models from perpetual license models to subscription models. Finance business partners are important in subscription environments. In this article, you will find sample questions an FP&A business partner can help answer to accelerate the growth trajectory in a SaaS enterprise.

October 7, 2019
FP&A Tags:

The 3rd Toronto FP&A Board meeting, with senior FP&A practitioners from industry-leading firms in staid industries — such as financial services, retail, manufacturing, mining, hospitality, consumer products, insurance; and, even, technology companies, took place on the 24th of September.

September 16, 2019

My aim in this article is to proffer suggestions for assembling members of an FP&A team. This is the team that will ensure an enterprise is resilient enough to navigate competitive threats, technology disruptions, regulatory effects, and can adapt to broad market dynamics in this 4th wave of the industrial revolution. 

April 3, 2019

The article is titled Mergers & Executions. It’s not a typo. You might think it should read Mergers & Acquisitions (M&A). However, the fact is, most M&A activities could do better with execution from the pre-acquisition to the post-acquisition stages. This work will draw on practiced methods for companies to execute value-creating, not value-destroying acquisitions, with the guidance of their Financial Planning & Analysis (FP&A) teams.