Top Cash Forecasting Tools For Large Enterprises

What you’ll learn


If you’re looking to make cash forecasting easier for your large enterprise,
make sure you’re getting the tools you need. Check out our guide on the best cash management software. 


Why is cash forecasting important for large enterprises?

In today’s world, Cash is King. A business needs to have an ample amount of cash to pay its investors, vendors, employees and meet financial obligations. Large enterprises often have a misconception that cash flow forecasting is helpful only for cash deficit organizations. This ignorance results in poor cash flow management and planning for investments and cash reserves, and loss of potential sales opportunities. Gauging how much cash your firm has currently and how much it will gain in the coming quarter helps to make proactive(well-planned) budgeting decisions instead of reactive(last-moment) decisions. Budgetary forecasting ensures that your product and liquidity are on shelves, and serves as the lifeboat during a fiscal crisis or seasonal periods when you need to arrange loans at credit. Any delay in planning leads to plummeting sales and substandard market status. If the amount of cash flowing out is greater than the cash flowing in your books, you may end up having a spike in DSO and a drip in DPO, which means poor creditworthiness.

What are the possible repercussions of poor cash forecasting for large enterprises?

There are many negative consequences of inaccurate cash forecasting. Some of them are depicted below:

  • Mismanagement of idle cash due to low confidence

Lack of global visibility hinders decisions to manage idle cash which could be used to buy fixed assets for improving productivity, buyback stocks, and buy insurance.

  • Ineffective risk control due to improper decisions

Lack of transparent and accurate data leads to irrational hedging decisions and incorrect reporting to the CFOs and greater chances of missing tax-reducing opportunities. Staying unprepared for cash squeezes leads to higher bank fees and improper use of credit lines.

  • Misidentification of the possibility of cash surpluses

It is equally essential to identify seasonal peak times where there are spikes in sales as to identify red flags in the economy. If your business forecasting software fails to predict cash surpluses, it loses investment opportunities in the share market.

  • Underperforming staff and unprofitable hiring

Inaccurate long-term forecasts decrease the quality of your workforce. Hiring in distress means hiring in haste. You might have lower funds to hire a pool of qualified talents, or might lose good employees if your firm’s reputation is at stake.

  • Inefficient operations due to panic purchases 

Buildings, machinery, systems, and other assets are critical for success. Poor forecasting makes you unprepared for buying or maintaining your assets. Buying in hurry lowers the possibility to negotiate and you might end up spending a lot of money.

  • Jeopardized firm due to poor scenario analysis

If an organization is weak at identifying a crisis before it hits, it ends up with lesser time to ballpark revenue goals. Measuring your liquidity untimely leads to a tunnel vision, so the firm eventually runs out of money or gets penalized.

What are the main differences to consider when putting together a cash forecast for a large business compared to SMEs?

The credit access for large businesses is different from small businesses for the following reasons:

  • Large businesses have more assets that act as collateral in times of economic trouble, whereas small businesses lack assets that they can sell while facing indebtedness.
  • Well-established businesses have a long history and prominence, so investing and buying stocks becomes easier because of credibility.
  • Long chains of data can also provide a more accurate forecast, whereas upcoming SMEs struggle on this because they lack enough documentation and are still in the process of building trust rather than having a solid rapport with creditors.

The cash flow forecasts differ based on a company’s legal structure, market niche, forecasting goals, etc. Short-term forecasts are used to monitor A/P and A/R closely to predict when payment will be received and to identify risk horizons, whereas long-term forecasts help analyze “what-if” scenarios, grab investment options, run variance analysis for finding discrepancies like variance, improve business agility in terms of capital expansion, and evaluate progress towards the final target.

Top tools for large enterprises

These are some of the tools or cash forecasting software that are used widely across big firms:

  • ERP + Bank portals +  Spreadsheets

    Spreadsheets are commonly used to pull raw data from ERP/ bank portals for forecasting purposes. It is budget-friendly, user-friendly, and convenient. Historical data of sales are accounted for from accounting departments, CRM, etc. to prepare a forecast, and charts are prepared for better understanding.

    However, Excel cannot fully meet the forecasting requirements due to the following reasons:

    • It is time-consuming to locate data from different sources and teams, and export them. As complexity in data increases, it becomes difficult to report them, which leads to a lag in decision-making.
    • It is error-prone and real-time forecasting can’t be done correctly since data modification is difficult, which leads to inaccurate forecasts.
    • While preparing seasonal forecasts, it is necessary to separate data for each month, which makes the whole process tedious.
  • ERP + TMS + Spreadsheets

    The above situation can be tackled with TMS for improving the accuracy of the forecasts.

    Companies contact their associated banks to gather data for preparing time-series forecasts. ERP helps in obtaining past data to understand patterns. While, TMS manages real-time cash, hence increasing accuracy in forecasts. TMS predicts estimated annual sales, revenues, and profit/loss for different periods and frees up cash, minimizes paperwork involved in trading finance, and helps in executing payments across trading protocols.

    Although, this combination poses a risk in cash forecasting due to the following reasons:

    • Bank assets and liabilities are influenced by various factors like economic fluctuations, interest rates, static or dynamic systems. Forecast errors are probable here.
    • Decentralized TMS presents challenges in communication and oversight and makes it tough to maintain multiple treasury systems. Moreover, implementing TMS can be expensive.
    • When there are multiple ERP systems and the line items are not consolidated in one place, modeling and forecasting become hard to implement.
  • Cloud-based forecasting solution + Automated technologies

    If you need to do more quality checks and forecast more timely with utmost accuracy, flexibility, and visibility, a cloud-based solution is the right choice.

    • Cloud integration reduces bank lockbox fees and cash transfer fees, thus offering a greater rate of return on cash investments and saving time.
    • It acts as a single repository to store all the data, which helps to create models that rely on the most up-to-date financial information. This improves collaboration and cohesion among departments and enhances financial planning.
    • Artificial Intelligence provides unambiguous variance forecasts by considering scenarios to predict AR and AP pragmatically and refine forecasts with time and data.

    Yet, limited data and lack of an appropriate technical infrastructure can serve as a roadblock to adopting automation.

Since larger companies can afford robust technologies and have sufficient data to support cash forecasting, they can adopt cloud platforms and AI for enhancing their performance to reach their long-term goals through proper visualization of cash position.

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HighRadius Integrated Receivables Software Platform is the world's only end-to-end accounts receivable software platform to lower DSO and bad-debt, automate cash posting, speed-up collections, and dispute resolution, and improve team productivity. It leverages RivanaTM Artificial Intelligence for Accounts Receivable to convert receivables faster and more effectively by using machine learning for accurate decision making across both credit and receivable processes and also enables suppliers to digitally connect with buyers via the radiusOneTM network, closing the loop from the supplier accounts receivable process to the buyer accounts payable process. Integrated Receivables have been divided into 6 distinct applications: Credit Software, EIPP Software, Cash Application Software, Deductions Software, Collections Software, and ERP Payment Gateway - covering the entire gamut of credit-to-cash.