A DIGITAL AND AUTOMATED APPROACH TO ANNUAL BUDGETING IS A NO BRAINER

Simon Bittlestone, CEO, Metapraxis

Speak to any CFO, especially in large multi-national organisations, and they’ll tell you about the relentless challenges they face with regard to creating annual budgets and business forecasts. Why? Budgets and forecasts are still often created and delivered manually in Microsoft Excel – which is undoubtedly an excellent tool and offers numerous benefits to FP&A teams – but it isn’t designed for this activity.

The challenge of Excelbased budgeting

Typically, organisations tend to follow a similar annual budgeting process. The central finance team creates a starting point for the new year’s budget, often rolled over from the previous year, with a targets incorporated. Depending on the size of the enterprise, anywhere between 10 and 200 people will then typically input into the budget, starting with the revenue plan through to build up of costs, and the impact on cash flow and the balance sheet. The central finance team then has the unenviable task of consolidating all those inputs manually into a single Excel budget spreadsheet. This in itself is no mean feat, when you consider how complex, time-consuming and error-prone this process is.

The finance team summarises the context to reflect the assumptions such as the marketing expenditure required to achieve new product sales and so on. Following the presentation of this mammoth budget spreadsheet to the CFO and senior management, changes are inevitably needed, which in turn means that further input from many of the 200 people who originally contributed is required. This process continues until the CFO, management and the business units at large are on board with the business goals and targets for the year. The timeframe to reach this point could range from anywhere between three and six months, with numerous team members having time and headspace for little else.

The difficulty of this exercise is easy to grasp. A single misstype could break a formula or even multiply an error, the repercussions of which could potentially be catastrophic for the enterprise. Most finance teams have their war stories. A fortnight away from budget presentation D-day, whilst conducting the final checks of the annual budget, the central finance team in a US based multi-billion dollar business spotted an error, resulting in the department having to completely re-do the entire budget to ensure accurate representation when submitted to the Board. One small mistake led to the team working long into the night and weekends to meet the deadline.

Digitisation for strategic insight

In today’s predominantly digital business environment, fighting with Excel spreadsheets is a futile and wasteful exercise. A digital approach delivers the same results in a fraction of the time, saving the enterprise a significant amount of money. To illustrate a hypothetical scenario, an organisation comprising five business units, each with 10 cost centre owners, running an Excel-based manual budgeting process across revenue, cost, capex and cash flows, before a group-wide consolidation process, incurs c.370 days of effort versus under 130 days if a digital and automated methodology were used. The total cost saving in such a scenario would be c.$200,000 per year, before any of the benefits of improved accuracy and better use of time are quantified. This estimation is based on a budgeting calculator that leverages industry standards and best-practice to arrive at a cost saving calculation.

Furthermore, budgeting isn’t only about revenue and cost numbers, it’s also critically about understanding business trends in the organisation, identifying the opportunities and risks, and based on data insight, taking better decisions to achieve commercial goals.

In a digitised finance operation, adoption of automation can help exponentially shorten the time to produce the budget, freeing up FP&A teams to provide strategic insight into the business, and in doing so add value and expertise.

A large corporate’s central finance team confessed that prior to adopting an automated approach to annual budgeting, the department was spending nearly 80 percent of its budget process time inputting and sanitising the data, until they moved to a digital process which instantly brought the time down to under 20 percent.

Digitisation a foundation for analytics and AI

With the digital fundamentals in place, FP&A teams can leverage their datasets for analytics to better understand business performance, areas for growth and even the broader environment within which the organisation operates. In which business units are staff costs out of line with revenue growth? Which divisions are underperforming against their annual targets? Are there signs of customer churn brewing? Can we better predict customer demand over the next three years? Is there an opportunity to launch a new product or service? Is there the right correlation between marketing costs and revenue?, and the list goes on.

The days of Excel-based budgeting are numbered. In the next decade, large swathes of finance and accounting work is going to be automated through AI, and anyone who doesn’t believe, I dare say, is burying their head in the sand. These technologies require a robust foundation of digitised processes, and now’s the time to do it.

Open source has become one of the most recognised movements in technology in the last decade. According to Red Hat, 90% of IT leaders use enterprise open source software, and by 2026, the open source services market will be worth $50 billion. The number of open source projects and businesses based around open source has skyrocketed over the past decade.

These projects need people to support them. This takes money. Traditionally, this would come from venture capital firms that would provide funding that would go into recruiting staff, developing the community and growing a business. In today’s climate, securing funding for these kinds of businesses has dropped massively - during 2022, investment in startups dropped by 43 percent compared to the previous year according to Crunchbase. Today, venture capital firms are focusing on companies that have a clearer path to sustainable revenue operations. So how do you quantify these opportunities for them, and help them understand growth?

Cowboy Ventures shared that ‘usage’ is the number one metric investors look for when deciding on which companies to fund. The Cowboy Ventures team found that “running a project in production signals trust as it can impact end-user experiences.” Similarly, Redpoint Ventures recently published their top 25 open source infrastructure companies, which compounded the need for the rate of growth to be tied to external contributors, not stars on GitHub.

The team at Redpoint commented: “We anchor too much on total GitHub stars. In our opinion, usage is the most important metric.” For firms looking at investing in open source, this real world data is an essential guide for who to back at the beginning.

Building a business, not just software

The film Field of Dreams is best remembered for the line, “If you build it, they will come.” But wildfire open source adoption does not just happen, and it does not guarantee commercial success even if it does. Garnering millions of downloads or recruiting thousands of contributors does not equate to a capacity to monetise.

Cultivating a viable business around an open source project hinges on the company’s ability to turn anonymous usage of that software into a set of known users, and then to turn some of those known users into paying customers for a product or service around that software. To invest in such a business is to take a bet on the effectiveness of that funnel, so it’s critical for investors to understand the real number of active users and their propensity to become customers.

Contributors offer a starting point to understanding who is using the project, but typically this is an extremely limited subset of the user base. Any company that strives to commercialise its product and grow to the next level will inevitably need a more complete picture of their adoption metrics.

These metrics all exist, but - even though it is your software that you are making - not all of them will be available to you, let alone all in one place. Solving this problem will help you understand your business and provide that proof to others. You need that level of data to know that you are on the right track by getting insight into how often your software packages are downloaded, but more importantly how often those packages are put into production deployments. This information helps you track your growth with production users, demonstrating their success and providing insight for you and any potential financial backers as well.

At the same time, there is no set path to follow around what those customers will actually buy. Some companies trade on their support and skills, while others use cloud hosting as the product and run their open source project on top. It can be easier to sell cloud rather than services, as cloud is a tangible product, but it is not right for every project or market. The most important lesson here is that your business may have to change over time, based on what customers are willing to pay and what they want to buy.

Creating a sustainable business is hard. Creating that sustainable business when everyone thinks you are giving your product away for free is even harder. However, it provides a route to bigger potential markets and revenue opportunities compared to building a product and selling it on its own. To be successful, it needs that long term view. At the same time, investment in areas like open source is necessary to develop those projects that can support wider ecosystems, build companies and maintain healthy communities. For VCs, using real-world data on where projects are being used in production can show where those opportunities to invest are, leading to real returns over time.