It’s 5:05pm EST. Bob, CFO of ABC Inc is on an earnings call and is reporting a 20% miss on earnings due to slower revenue growth than forecasted. Company ABC’s stock price is plummeting, down 15% in extended hour trading. The board is furious and investors demand answers on the discrepancies.
Inaccurate revenue forecast remains one of the biggest risks for CFOs. In a recent study, more than 50% of companies feel their pipeline forecast is only about 50% accurate. Projecting a $30M revenue target and coming in short $6M can leave investors and employees frustrated and feeling misguided on the growth trajectory of the company.
In the past 10 years, supply chain has become much more complex with omni-channel distribution and the increasing number of indirect participants that can influence product demand. Advertising and promotions can create an uplift in demand that spikes sales by 20% or more. In addition, different types of customers have different purchasing behavior. These behavior are driven by myriad of underlying indicators and should be modeled individually. Yet, Financial Planning and Analysis (FP&A) has not changed fundamentally despite the changing landscape in the way companies do business. The process is still largely manual and dependent on time-series estimation techniques dating back to the 1980s.
Machine learning is a new technology that uses algorithms to learn from the data and guide us in making more informed decisions. Leveraging the power of machines allow us to consider more scenarios and combine the effects of thousands of indicators to improve forecast accuracy. For revenue forecasting, machine learning excels in the following 3 areas:
1. Trend discovery from unlimited amounts of data
With the advances in big data technologies, computers can crunch through data of all types and sizes. Unlike humans, algorithms can simulate numerous scenarios and recognize patterns that keep re-emerging in the data. It is also not limited to structured data and can examine unstructured data such as emails and logs to extract meaningful indicators.
2. Granularity of forecast
Instead of looking at product line level aggregate sales values, machine learning algorithms can detect patterns at SKU, purchase order and invoice level to discover interesting relationships and dependencies. For example, algorithms may find that the demand of one product (iPhone 6) is a leading indicator of demand for another product (iPhone 6 accessories).
3. Adaptive and Dynamic
Machines can also automatically adapt and re-run forecasting scenarios to adjust to changing market conditions and consumer demands.
Companies such as Flowcast are leading the charge in introducing machine learning techniques to the finance department of organizations.
Large firms take a position of power when it comes to paying vendor invoices. They make deductions just about everywhere. Here are some key points to consider.
According to a recent study by US Bank, nearly 82 percent of all startups fail due to poor cash flow management. Sometimes, it’s not even the fault of the accounting department. Instead, cash flow problems are often the result of large clients taking their time to scrutinize and pay invoices. This rings especially true for business-to-business (B2B) companies that supply the big guys; mass merchants like supermarkets, the US government, department store retailers, drug store chains, and more.
Hiccups also occur when large firms find ways they can make “deductions” from their vendor invoices. The problem is not limited to startups and SMEs. In fact, firms of all sizes are increasingly finding themselves at a disadvantage when supplying big corporates. Not only can names like Walmart or Burger King take months to settle invoices, but when suppliers do eventually get paid, it’s often less than the amount the invoice called for. In an article that appeared in Business Credit magazine, Robert Wirengard writes:
Can you imagine what would happen if you went into a store and, after the cashier rang up your total, you said, “Take $5 off; I am deducting that amount because you were out of my creamer.” After stunned silence, your head might be spinning while security guards escort you out against a backdrop of whispers and laughter.
The anecdote sounds silly, but it’s actually what happens with corporate invoices. Compliance claims and fines are everywhere in B2B invoicing. Wirengard says debtors can claim $5 to $50 for leaving a PO number off of an invoice or sending a hard copy instead of an electronic one. Other charges can conceivably include $100 or more if the carrier was late, or $5,000 to $15,000 if the UPC scanning code for a consumer good contains errors.
The list is growing and creditors are increasingly seeing arbitrary deductions for vague reasons. It’s difficult to manage these deductions, and debtors know it. With this in mind, and in no particular order, here some key points that all business owners need to keep in mind about “deduction claims” from their clients.
- It affects nearly every B2B firm
Studies show that 5 to 15 percent of all invoices are affected by deductions from clients. This equates to between 4 and 10 percent of all open items on accounts receivable. Essentially, it means if your firm is billing big clients, you’re likely experiencing deduction problems, maybe without even knowing it. Corporates like to use the term “vendor compliance” to justify deductions.
A deduction is the hardest type of open item in accounts receivable to resolve because most departments in your company are involved to various degrees, according to the Credit Research Foundation. The customer takes the deduction based on their policy and procedures, and it’s up to you to prove they are wrong or right.
- Most deductions are valid
While the statistics for invalid deductions warrant investigation from creditors, 85 to 90 percent of them are in fact valid. This means companies must spend considerable time and resources sifting through vendor compliance claims, hunting for the bad apples, which are not easy to spot. Hundreds, sometimes thousands, of transactions must be checked to locate the few that can be returned to the customer with a demand for payment.
- But without scrutiny, revenue will be lost
It’s often tempting to just trust your big-name clients when they say the costs they are deducting are justified. After all, SMEs don’t necessarily have the time or resources to follow up on such things. Or perhaps creditors don’t want to rock the boat, considering they strive to maintain a positive rapport with each of their clients.
However, CRM Software Blog says 14 percent of deductions are usually found to be invalid. Businesses can pull in large sales and profit savings if they address invalid deductions from customers properly. If firms are not able to reconcile these amounts, significant revenue is sure to be lost.
- Invoice remittances may contain 5 to 10 separate deductions
More than 32 percent of financial transactions in the consumer products and goods industry involve deductions, according to the Grocery Manufacturers Association. Some types of deductions retailers commonly take include: costs associated with shipping terms, in-store display allowances, fees related to damaged goods, fees related to price discrepancies, fees related to discontinued products, and more.
Most companies do not approach deductions analytically, says Credit Research Foundation. Instead, deductions are often treated as distractions to the core business, rather than warning signs that something within the operation is wrong.
Companies that operate in the B2B space, and send invoices to large firms, need a fast and systematic way to evaluate “vendor compliance” checkboxes, and resolve deduction claims from their corporate clients.
Experts will tell you that outsourcing the work makes sense. There are a few reliable providers of software and services that can proactively identify root causes and invalid deduction claims for you. Doing this will save you from headaches, but also potentially save your firm hundreds of thousands of dollars in billings each year.
Cash flow is the lifeblood of most businesses. As operations grow increasingly global, today’s organizations face the increasing challenge of working capital needs. The complexity is exacerbated in cross border transactions in which trade receivables are subject to separate legal jurisdiction and payment terms tend to be longer. In this context, supply chain finance (SCF) programs could be a powerful tool to drive working capital efficiency in the supply chain, helping suppliers get cost-effective financing while allowing buyers to maintain a stable supplier base by capturing value from their payables. Indeed, SCF is now a $275bn industry, growing 30% a year . However, despite years of implementation, a growing number of buyers see SCF programs as potentially negative to their overall company debt rating. There is a growing concern that rating agencies may treat SCF programs as debt rather than trade payables. What can tilt the balance are changes in the terms of trade between the buyer and the supplier. In a report last December, Moody’s voiced its concerns about overly complex SCF programs and encouraged less enclosure when communicating engagements in SCF programs.
While SCF offers tremendous potential to dramatically improve operational and financial efficiency for organizations, debt reclassification could be the Achilles heel. It has become the top concern for CFO’s and Treasurers as they evaluate adoption of SCF within their organizations. Consider a company with $300M trade payables outstanding. A sudden reclassification of these payables would severely impact their leverage, access to additional credit and existing debt covenants. Take for example the case of the Spanish energy group Abengoa, which recently filed for bankruptcy for one of its subsidiaries. Although their large scale SCF program did not cause their decline by itself, it certainly had debt-like features and was a large contributor to their decline.
Unfortunately, the IRS has not yet addressed this issue in a satisfying manner, and existing guidelines are vague at best. IFRS rules do not fare that much better. IFRS suggests reclassification of trade payables into debt only if there is a substantial difference in the terms of the existing financial liability and the new liability. The ambiguity and subjectivity make the reclassification issue a major headache for treasury organizations considering the deployment of SCF programs, causing companies to be more conservative, slowing down the programs and making the set-up costs more expensive. 
All worries aside, we did a bit of digging and learned that there are ways to navigate the choppy waters of buyer led SCF programs. Programs that successfully have been put in place tend to have a set of recurring characteristics to comply with auditors so that transactions are kept as trade payables. First and foremost, a thorough understanding of the trade terms is required. The key question to ask: Are there any significant changes in the payables to make it look like a debt-like obligation? Trade Financing Matters provided some useful insights regarding this issue and offered the following key points:
- You should avoid a tri-party agreement between the buyer, seller and the funder. Extended payment terms for the buyer and discounted early payment for the seller should be treated as two separate events. Therefore, if the seller for some reason wants to opt out of the program, the buyer still gets his extended payment terms. The higher level of influence the buyer has in the negotiation process, the harder it becomes to convince regulators that the company is not borrowing money from a bank to pay its vendor. 
- The bank should in no way be involved in the discussions between the buyer and the supplier regarding the terms of trade. 
- The discount rate offered to the supplier should be offered by the bank and not the buyer. 
- The buyer should not guarantee payment to the bank. This point is important and in many ways the crux of the issue: If the buyer is confirming to the financial institution that it will pay on maturity regardless of any disputes or other rights of offsets it may have against the supplier, then it is giving a higher level of commitment to the bank than it gives to the supplier. As a result, the economic substance may have changed significantly as this could be constructed as a form of financing on the firm’s books. 
- The bank should not share any interest revenue from the discount with the buyer. The presence of interest is not customary in a trade payable arrangement and would suggest that the obligation is more akin to debt. 
- Peer-to-peer comparison may motivate DPO extension beyond the industry standard: Although an extension of payment terms(DPO) to better align with its peer group may not significantly change the economic substance of the arrangement, the payment terms should be consistent with other peer companies in the company’s industry. If your payment terms have extended beyond the industry standard, it may indicate that the presence of a SCF program have resulted in an obligation that is inconsistent with the customary trade payable terms and thus that the economic substance have changed. 
- Discounts are typically negotiated between the seller and buyer, and if there are disputes, the buyer normally has the ability to withhold payment. If, for any reason, the arrangement does not allow for such negotiations and abilities, the economic substance of the arrangement may have changed. This becomes relevant in cases where the vendor delivers a product defect. If the buyer is still obligated to pay the bank in full, despite the defect, then this may imply that the company no longer retains its right to negotiate terms for that specific payable. 
- Buyers should have no say in determining which party that should finance the program. 
Some buyers look towards non-bank platform providers in order to lessen the likelihood of debt reclassification. Although many successful SCF programs are orchestrated by banks, non-bank providers, (eg., PrimeRevenue), separates the buyer from the bank and do not utilize the contract between the bank and the buyer. This reduces some of the aforementioned risk, such as the tri-party agreement.
The emerging field of supply chain data science is transforming supply chains from reactive- to predictive operating models. The implications extend far beyond traditional supply chain operations. Ultimately, they will help the next generation global company – the insight driven enterprise – getting ahead of competition.
Written by August Riise, Flowcast.
*Full disclaimer: We are not auditors or accounting professionals. These are strictly based on our own research and opinion
 Is Supply Chain Finance Constricted by Accounting Rules? David Gustin, Trade Financing Matters
 Supply Chain Finance Payable Reclassification issue – dead or alive? David Gustin, Trade Financing Matters
 Dataline: A look at current financial reporting issues , No.2013-28, PwC