“Our account balance is $50,000 below the forecast — where did that money go?!”

Anybody who has worked in finance for a small or medium-sized business will likely know that sinking feeling when you realize cash that was in the forecast has failed to materialize.

It can happen in any business, especially when they are in demand and very busy. Everyone is working nonstop on lucrative projects, but bigger projects can mean extra complexity and chunkier bills. Just one large, late payment can be the source of a disaster. Revenue could be growing fast but when the cash balance in the company bank account is not what it should be, there can be serious problems.

The finance team will be responsible for answering the question as to what went wrong. It could be something as simple as that the invoices were sent out late — but ensuring that the cash flow projections are accurate, updated live and that the variance is seen and analyzed on an ongoing basis is key to a sustainable business.

Finding time to identify and plug those leaks at the same time as bailing out the ship is not easy! Here are some of the challenges that lead to those kinds of mistakes and how to solve them.

Problem #1: Getting the data is too hard

“It’s down to the sales team - they just don’t tell us what money is going to come in!”

In many businesses, it can take the finance team dozens of hours a week to simply collect the data that is required to build a revenue forecast and a cash flow projection. It is usually siloed in different software solutions or on different spreadsheets.

What new proposals are likely to be sold? What are the start dates? Are they likely to slip? That kind of information may be in the heads of the sales team and difficult to find out or check.

And what about existing customers? Will they buy more licenses or services? Can we recognize the revenue for work that is due to be completed this month? Have invoices been sent out? Do these customers tend to pay on time?

Solution: Streamline the information-gathering process

Using a financial forecasting platform that can automate some of this data collection effort can reduce the manual effort required and give the finance team more time to analyze the results,

I use the term platform specifically on this, as automating the flow of data from one stage of the financial life cycle to the next, and then being able to gather data at stages is the key to solving this.

For example, a transparent, real-time link to the sales team means that when the sales pipeline changes, so does the revenue forecast. That in turn means that the finance team can place more trust in the data and don’t have to check and double-check it.

For example — a big proposal is in the pipeline, but you don’t have to set aside time to phone the sales lead to check where it’s at. The moment the deal is agreed upon, it will automatically become a project. That means the appropriate revenue recognition rules will be applied and that data is available to billing so that it is easier to send out accurate invoices on time. This means the entire revenue cycle can be completed with much less effort from the finance team.

Problem #2: Monitoring costs with inaccurate modeling

“Oops! — looks like we under-estimated staff costs and expenses and that put a hole in the bank balance.”

The other side of the ledger is also important for predicting the financial position accurately. Staff costs are generally one of the biggest outgoings of a company. When looking to recruit new people, do you have a handle on how much they will actually cost and what the likely revenue is that they will bring in? Making these kinds of strategic decisions is complex and has implications for the business.

Failing to manage expenses is another potential source of cash leakage. What are the hidden costs that can sometimes fail to be picked up? These could be things like — software licenses for new hires, medical insurance, or bonuses.

Solution: Financial modeling with real numbers

Some systems when looking at the costs of hiring a new employee estimate a percentage of additional costs. But that can be significantly inaccurate and that error mounts up over time — modeling the projected hire with real numbers is more accurate.

There are particular costs associated with types of jobs — sales cloud license for a salesperson, for instance. When looking at expenses there is potentially a great deal of complexity — there may be different currencies and other issues to take into account. Using live connected data and process automation where possible saves time for the finance team and gives a better result.

Because you are looking further out when dealing with these kinds of costs it is helpful to have a finance platform that uses live transaction-level data that is capable of processing very large amounts of data to capture the specific costs of all expenses related to a new employee, and not just a general percentage assumption.

That gives you the best chance of making fully informed hiring decisions, and fewer nasty surprises caused by underestimating the costs. It also gives you an additional advantage of being able to manage the costs for all of these expenses, for example, you can manage your subscription licenses to not overpay for licenses you will not need or vice versa.

Problem #3: Unexpected variance

“It will take weeks to get a clear picture of what happened to that $50,000 and by then it will be too late to do much about it!”

What cash is due to arrive in your business bank account over the next few weeks and months? This is a complex picture for many businesses which have a range of different pricing models on the go. Look at this screenshot from a Salesforce presentation — all of the items on here represent different elements in the revenue stream.

Added to the complexity of input is the timeline, which is the most challenging element if you are attempting to do this manually. Forecasting revenue can be difficult but has a contractual structure. Forecasting cash is a different animal altogether, as you need your customers to process it on time and that isn’t always what happens. Creating a short-term cash flow can be fairly straightforward, but longer-term cash forecasting has to take this into account and enable you to easily adjust.

Another factor is what forecasting methodology type are you utilizing. Many companies still use a waterfall-type forecasting method, where they start with a static budget and set down predictions for the next year, perhaps utilizing the numbers from previous years.

This situation is likely to lead to a lot of unpredictable variance between the forecast and the bank balance. By the time the accounts for a period are collated and closed, and you spot that missing $50,000 — the business may have moved on. Once you have tracked down the cause, it may be too late for the business to rectify it.

Solution: A more agile approach

A finance platform that can combine the complete financial workflow is essential to improve this. The CFO can do a lot with midnight oil and heroics but over time, the right technological tools can make this a smoother process with a better result — you can spot that unexpected variance as soon as it happens and put your finger on the cause.

A platform that combines pipeline, bookings, expenses, workforce, cash balances, and reporting with live data, and that also provides flexibility and intelligence for being able to iterate and modify easily and without the IT department is the solution.

Instead of working to an annual pattern, you can bring the horizons closer. For example, you may feel you can look ahead by two months with confidence — then the platform can continually adjust to show that time window based on your pipeline and also still know how to forecast after that window. Then, when a deal in the pipeline is closed, that will be automatically reflected in the system. The proposal price will flow into the revenue forecast, create COGS expenses and commissions. It flows not only to the P&L but equally to the cash flow projections and provides the capability to manage those cash expectations.

You don’t need to do anything manually to keep rolling the forecast over — the time window continually shifts to remain two months out. This more agile approach to forecasting gives a much better chance of accuracy than using a longer, more static timescale which risks being inaccurate and out of date.

When you have this kind of platform in place, you can see immediately when variance starts to appear. Then you can drill down into the numbers to understand the source of the divergence. That gives the best possible chance of intervening while there is still time to do something about this issue.

There is more to this than replacing spreadsheets

A sophisticated financial forecasting platform that is designed to support your kind of business is essential. Select one that can handle the entire financial workflow and is built for your industry. This will give the depth of features designed for specific use cases, that can be very complex, without having to spend a fortune on customizations.

But simply attempting to replace Excel with a new tech tool won’t solve the problem by itself — you also have to be prepared to take a more forward-looking approach.

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