by: Ann Marie Svoboda
September 12, 2019
I’ve recently talked to various Wall Street professionals that are considering a career move into corporate finance. These capital markets savvy people asked for input. How should they approach their search? What jobs should they target? Where would they fit best?
These are interesting questions. I know a lot of smart bankers, and corporate finance teams are always in search of good talent. Such cross-pollination could prove advantageous.
I usually ask, “what is your value proposition?” to clarify expectations. Responses vary but always involve modeling skill. These financial professionals declare that, once they land their new corporate finance role, the work will revolve on financial models. I admit this theory is kind of true. But it lacks perspective, and that leads me to this blog topic.
Corporate finance is not limited to modeling.I’m not suggesting that a Wall Street type can’t break into the corporate mystique. I am instead suggesting that a capital markets practitioner will have a difficult time getting hired (into a corporate role) if they only have modeling skills to offer.
In my opinion, a management role in corporate finance requires five categories of expertise. The list includes technical finance knowledge and analytical abilities, which are competencies my Wall Street friends have. But the technical and analytical ability must be bolstered by proficiency in financial data, control environments, and collaboration. Let’s review these five categories below.
TECHNICAL FINANCIAL KNOWLEDGE
Financial aptitude most often rests on education, including degrees in accounting or finance. The collegial education is then typically supplemented by some financial certification such as the Certified Public Accountant (CPA) or Certified Management Accountant (CMA) designations. Those basics ensure fundamental competency in accounting, reporting, analysis, internal controls, and ethics.
Education is only a foundation.Some corporate finance work is very technical, though, and requires further study through specialized programs. The most prevalent specialty certifications (in the United States) are AFP’s Certified Treasury Professional (CTP) and Certified Corporate FP&A Professional (FP&A), IIA’s Certified Internal Auditor (CIA), and CFI’s Financial Modeling & Valuation Analyst Program (FMVA) credentials, among others.
Technical knowledge, including competency in generally accepted accounting principles (“GAAP”) and financial reporting, ensures a job searcher gets their foot in the door. But opportunity remains limited without experience in the other categories.
Certainly, every financial professional must understand the basics of GAAP. But when working in corporate finance, it is also important to understand the systemic organization of accounting records.
In this, financial education extends to the comprehension of system hierarchies for managing accounting data. System hierarchies include the data architectures for the general ledger and related sub-ledgers (e.g., accounts receivable, accounts payable, purchasing, etc.), all of which typically reside in an enterprise resource planning (“ERP”) environment.
Some companies will have streamlined data strategies that accommodate a singular ERP environment, ensuring a single instance of the general ledger and various sub-ledgers. Many companies, though, will have multiple ERP environments, disconnected versions of the chart of accounts, and isolated sub-ledger systems. Lucky finance professionals need only access one system instance to perform their work. But corporate teams are not often so lucky.
Understanding the ERP platform, moreover, will not sustain an extended corporate finance career. In my opinion, knowledge of the ERP system will only support work in the junior management ranks. When aspiring to an executive role, it is also important to understand the data infrastructure inherent to consolidation, tax, treasury, and management reporting. These technical, corporate perspectives involve a dimension of financial information that is material to financial strategy, forcing financial executives to comprehend the related data.
An astute corporate finance professional doesn’t only understand financial data but also data governance. Corporate infrastructures involve layers of back-office processes, system controls, and overarching policies that facilitate orderly maintenance of the financial data. Effective financial professionals must comprehensively navigate and design such processes and controls.
A company’s policy infrastructure supports a matrix of static controls, designed to govern the infrastructure of data processing and decision making, as well as dynamic rules, which may shift to support an evolving corporate strategy. The trick in effective corporate management is to design financial policies that are strict enough to ensure approved behaviors and accurate reporting yet flexible enough to shift in response to evolving operations. An example of this trick involves the development of employee goals.
Financial Policy includes effective goal setting.Goal setting is an instance of control that, when effectively written, can support the achievement of near-term strategy. Tracking the results of those goals, then, must be supported by realities of the financial data infrastructure and managed through execution of business processes in line with overarching policy.
The importance of business analytics is not limited to corporate finance, but advanced analytical prowess will help anyone land a corporate finance job. The ability to translate complex reporting and market data into informative and actionable presentations is paramount to advancing a financial career. In this, my Wall Street friends are right. Their modeling skill is valuable to a corporate environment.
But certain differences should not be overlooked. The contents and style of corporate financial analysis are different from what an external analyst would enlist.
Internal financial analysis involves more than models.One differentiator is the need to extract the appropriate data from the correct financial system(s) while ensuring that data’s accuracy within the control environment. In other words, the corporate practitioner must know where and how to get the right data, and they need to know how to reconcile it.
A further distinction is substance. While the external financial professional has limited data to analyze, the internal corporate specialist will often review activity in minutia. For example, while an external analyst may review aggregate margins across annual periods, the internal analyst will analyze pricing and costs by product and customer, sometimes across daily periods.
Distinctions in financial analysis are compounded by complexity in audience as the corporate finance professional has many audiences to consider. Primary audiences are internal, ranging from financially literate executives to process-focused operating teams. Separately, there are audiences outside the company, including shareholders, unions, and government bodies, to consider. Each audience is diverse in need and requires unique consideration from the corporate finance team.
It is in serving those audiences, moreover, that the corporate finance professional assimilates their skillsets. Advanced financial managers partner with each audience, particularly their internal colleagues, to be successful. Through collaboration, finance teams guide data strategy and system designs that support appropriate controls and expert analytics. The financial output, in turn, ensures accurate forecasts, highlights risk, and contributes to business planning. It is this cross-functional leadership that ultimately ensures strategic decision making.
Overall, corporate finance professionals work in a holistic environment. The adept financial professional structures and analyzes data to strengthen relationships and guide strategy. Although technical knowledge and modeling ability provide a solid foundation for the corporate finance career, competency in financial data, control environments, and collaboration ensure success.
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by: Ann Marie Svoboda
August 6, 2019
Advancements in business intelligence (“BI”) bring new quantities and dimensions of data to Corporate Finance. The combination of faster networks, cheaper data storage, and BI platforms such as Tableau and Microsoft Power BI offer break-through opportunities for financial presentation. It’s amazing. The speed and capacity with which we are now able to analyze massive amounts of disparate data is a game-changer.
But there are common misconceptions about this new frontier. Related marketing suggests the BI platforms are magical. BI salesmen suggest we can simply push a button to see infinite volumes of charts and graphs that solve every conceivable analytical problem. Don’t be fooled. It doesn’t work that way.
Yes, the new technologies perform calculations at lightning speed and offer expansive dimensions in data analysis. But the problem is not with the technology. The problem is with the data. Wrangling these innovative analytical opportunities is a fool’s errand without a defined financial data strategy.
A Disorganized Approach
At the base level, managing financial data has rules. Generally Accepted Accounting Principals (“GAAP”) govern the structure of accounting, and since GAAP defines the structure and content of financial reporting, there is a predefined financial data strategy. Finance teams build a standard chart of accounts (“CoA”) to support the financial reporting system. Using the CoA data structure, along with some consolidation and adjustments, it’s clear how to present the Income Statement or Balance Sheet. Problems arise, though, when considering data either behind or ancillary to the consolidated general ledger (“GL”) data.
Consider this simple example. An analyst working at Imaginary Company wants to use their new BI software to analyze the Finance function’s costs. read more
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by: Ann Marie Svoboda
May 13, 2019
Financial analysis can be a thankless job. You distribute numerous financial reports only to be asked rudimentary questions about every spreadsheet. You spend countless hours building the perfect model, but the boss swiftly ignores it. Sometimes you wonder if anyone understands your work. Is anyone listening?
The answer is yes, people are listening. There is an audience for your work. But if you are suffering such dismissive reactions to your analyses, the problem is not whether anyone is listening. The problem is whether anyone is following.
It is important to remember that, to the standard user, the output of financial analysis often seems nothing more than a mass of jumbled numbers. Even short, summary tables can be indecipherable without directions. And yet many financial analysts neglect this reality.
Financial analysis must be designed with the intended recipient in mind or it will likely be ignored.We’ve all been there. It’s a natural consequence of being an analyst. While solving a complex financial puzzle, it’s easy to forget the audience.
You find yourself digging through a massive dataset, searching for an elusive answer. Maybe you’re trying to find the key correlation in a forecast variance or the obscure error in a reconciliation. The task seems endless. You’re building variations on macros, pivot tables, and data sorts and linking categories of numbers to broader interpolations. It seems like the numbers are a bottomless pit, and the list of possible equations are a black hole. Eventually, after hours (or sometimes even days) of work, you find the solution. The final column reconciles, and the last number is right. Your relief feels like nirvana.
You sigh, sit back in your chair, and lift your head from the screen. You start looking around the office and catch the boss’s eye. It’s only then that you remember. You’ll need to explain that bottomless pit. But how do you succinctly present a black hole?
Don’t despair. Although enhanced financial presentation takes time to learn, there are some basic rules to help you get started. read more
by: Ann Marie Svoboda
March 26, 2019
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I have been teaching finance teams about Financial Approval lately. And after a few hours leading these sessions, it occurred to me that I have never personally been trained on how to process an approval. Instead, I’ve just learned by watching my bosses approve things over the years.
That approach seems very dangerous. Now that I’m in a senior role, I approve a huge portion of my company’s investments and expenses. And what if, during my years of boss observation, I hadn’t grasped the right practices? Or what if my bosses had bad habits, and I latched onto those? I could be wreaking havoc and not even know it (not to mention jeopardizing my own future employability).
Luckily, I have worked for some good bosses, and it turns out that I have done a good job controlling spend and investment over the years. Nevertheless, not everyone may be so lucky in their boss-adjacent education. So I thought Financial Review & Approval would be a good subject for a blog post.
Financial review and approval is a key component of a company’s internal control processes. Such controls typically include segregation of duties, most likely ensuring that two or more people are involved in reviewing and approving investments and expenses. In most internal control structures, the approval process is designed to supervise accuracy, communication, reliability, and compliance around the spend request and approval process. And since specific spend requests are often cross-functional and/or international, that supervision can be complicated.
This complication is why financial approvers must be adequately trained. read more
by: Ann Marie Svoboda
February 25, 2019
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If you work in corporate finance, you know it’s easy to get lost in a sea of numbers. You spend your days wading through reconciliations and mapping variances that are full of numbers. And on any given day, if you’re good at your job, your reconciliation is clear and concise. Your variance analysis may even be transformed into a walk. If you’re a great analyst, your presentation even explains why the variances exist. But only if you’re an exceptional financial professional, do you skip the obvious and get to the point.
The Point can encompass a multitude of dimensions, but those dimensions generally pivot on a few key questions. First, The Point will always answer what specific operational action (or inaction) caused the variance. I like to call this The What.
Often, though, specific operational variance descriptions are not enough. In these instances, The Point will also answer The What Else. read more