Forecast: Definition, examples and implementation with CRM software
Will your company achieve its targets? How will your business develop? Are relevant changes to be expected?
These are key questions in sales controlling. The forecast helps you to answer them. Properly structured and implemented on the basis of data, you can recognize deviations from targets at an early stage and take countermeasures. Your sales department does not need a crystal ball to look into the future, but rather a transparent, data-supported analysis basis, for example CRM software with reporting and forecasting functions. How does forecasting work and what needs to be considered? Find out more here and how you can motivate your team to centrally provide the required data in the required quality.
Author:
Hans Jürgen Eilers, Area Sales Manager
GEDYS IntraWare GmbH
Inhaltsverzeichnis
An important part of sales management is dealing correctly with trends and external influences. Incorrect assessments of future developments can have serious consequences for a company. However, since no human can predict the future, you need the most reliable machine tools possible, such as CRM software, to help you do this.
What is forecasting?
Predictions or forecasts are needed in various areas of the economy. In business administration, the short definition is something like this:
An instrument from the controlling that helps you to assess the achievement of your targets. The forecast looks at short, medium and long-term targets. It is used by business and sales management and enables precise sales management.
The basic purpose of a forecast is to evaluate certain parameters and data in such a way that a forecast for the future can be derived from them. This involves a comparison of the target and actual values. Although a simple estimate can also be created without structured data from the historical development of the company, “on instinct” so to speak, it is only with intelligent digital tools that you are able to evaluate various data and include external influences such as trends, seasonality or economic developments.
Benefits
- Creation of a central database for analyses
- Real-time evaluations enable immediate reactions
- Transparency for all employees (according to roles and rights)
- Faster problem solving and selection of measures depending on the market situation
- Better planning of personnel and budget
- Avoidance of bad investments
- More effectiveness in marketing and sales
(through effort reduction, automated data generation and workflows) - Determining the optimal times for changes
For these reasons, forecasting is of great importance in many companies. The following applies: the more data and factors the sales department includes in the diagnostic forecast , the more reliable the forecast will be. Motivate your sales team, for example by using a CRM app to provide new data and more details ad hoc – even on the move.
Overview of different forecast variants
Intervals for forecasts can be set very differently, each company must find its own rhythm. In any case, regularity is crucial in order to recognize changes over certain periods of time. Especially when important decisions are to be made, it makes sense to take a longer-term view.
Forms
- Ad hoc forecast
is the unplanned, spontaneous forecast. This allows a company to react quickly to new developments. Probably one of the most formative events that forced many companies to make an ad hoc forecast was the coronavirus pandemic in 2020. - Year-end forecast
compares certain periods of the current financial year (e.g. a quarter) with corresponding periods from previous years. This observation is repeated at certain intervals. Actual data from the previous year(s) is used; figures for future periods are calculated on this basis. Individual periods can thus be compared very easily so that measures can be taken in good time. - Rolling forecast
is usually carried out monthly and covers a fixed period of one year or one and a half years. With the help of the outlook, which is always the same length, deviations from the plan can be better recognized than on a quarterly basis. The focus is not on the current financial year, but on market developments and how the company can assert itself within the market. - Value driver-based forecasting
determines forecasts with a focus on a small number of key figures that have previously been identified and defined as business drivers. This version is suitable if driver-based planning is also used. Drivers in B2B sales can be leads, new customers, turnover or products sold, for example. - Effect-based forecast
includes the impact that new competitors have on the market and on the company’s own products or sales. A special variant that can be used as a supplement to the above.
What forecasting methods are there?
In quantitative forecasting, the more data available, the better the prediction. Both individual internal and external data and standardized mathematical formulas are used as the basis for determining certain interest values.
If little or no data is available from the past, qualitative forecasts can be used. These collect data from surveys, market studies or subjective assessments by experts, among other sources, which is why they are imprecise and time-consuming. However, they are well suited as a basis for developing new products where the needs and opinions of customers play an important role.
What technical factors influence forecasts?
In order for forecasts to be meaningful for a company and to help with planning, the following points should be taken into account:
1. Data records
As already mentioned, the more data that is fed in, the more meaningful a forecast becomes. On the one hand, the comparative data set from historical data is important in order to be able to interpret new data correctly. On the other hand, data is collected on value drivers (such as sales, earnings, balance sheets, technological innovations, company image, brands, customer relationships, order backlog or references) and effects (such as seasonality or market trends). If you want to include effects, you must include corresponding figures from external sources.
The level of detail of the data collection influences the efficiency of the evaluation. CRM software gives your team a centralized “place” to collect and detail data and helps you identify key performance indicators.
2. Automation
Company data and sales opportunities are already available in the CRM system. The resulting automated forecasts make companies’ work much easier, as there is no need to collect data from various tables. With the right software, time and resources are saved, errors are minimized and the forecast is available at all times.
How do we get meaningful data into our forecast?
Your sales team receives and compiles a lot of information every day. Provide them with a CRM system that supports the entire process from lead generation to the sales opportunity to the sale. This automatically provides you with all the data entered for forecasts. A Cloud CRM or CRM App motivates users to enter information into the CRM system as soon as they receive it, even when they are on the move. Win/win!
In addition, digital systems cover different scenarios and data consistency is more reliable than with human information processing. Once set up, the software automatically creates the desired reports on the dates you specify.
3. Artificial intelligence / machine learning (ML)
AI can help to increase the quality of your forecasts. In particular, typical human errors or shortcomings can be excluded, such as
- Overly optimistic forecasts due to overestimation
- ignoring more distant problems and the associated negative developments
- forecast distortions due to deliberate disinformation (due to hierarchy/power) or unconscious misinformation (knowledge that exists in the heads of employees and/or is distributed at various locations)
By organizing data from different sources in a central database, machine learning methods such as time series, gradient boosting, neural networks and pattern recognition can be used to create forecasts.
How does a forecast work? From theory to practice
If you want to make forecasts there are various ways to do this. Subjective experience and manual evaluations are the simplest form of prediction, usually in the form of an Excel spreadsheet. This makes perfect sense for small businesses. However, it will be difficult to get to grips with large volumes of data in this way.
A good way to create reliable forecasts is to use CRM software with corresponding functions, such as those from GEDYS IntraWare. All valuable data is collected centrally here, and evaluation and analysis can be implemented with the help of developed algorithms. If you store your targets for each product, sales employee and territory, everyone involved has an immediate overview of the current status and can recognize any differences from the target.
The data stored centrally in the CRM system, which can be analyzed for your sales team, includes
- Company and contact details
- Historical operating data
- Product interests and opportunities
- Purchased products and cross sale options
- Licenses and number of users
- Reviews of products and services
- Service data, e.g. from ticket management
- Cost/benefit comparisons
- and many more
What is the difference between forecasting and planning?
A Forecast serves as an outlook for the future and has a strong influence on the operational direction of your company. Measures to achieve targets are not part of forecasting but fall under planning. If a forecast represents the future development, planning can react to it.
Two simple examples to illustrate this: weather and school cones
Suppose you are planning your birthday party in the summer. Due to the time of year, you can expect a party with sunshine and warm temperatures. However, if the weather forecast shows deviations – in the form of rain, for example – you can react early and plan to set up a tent. Just like a company forecast, a reliable weather forecast is based on solid data.
Another example: As a manufacturer of school cones, you could easily plan years in advance, because school enrollments in Germany take place at the same time every year (fall). The more pupils there are per year group, the more bags you could theoretically sell. But what would happen if school cones went out of fashion or a competitor offered more attractive cones? Forecasts alert you to such problems and enable appropriate planning – for example, the introduction of new products or marketing measures at the right time.
Conclusion: use a CRM system with forecast in your company
CRM software with forecasting functions offers evaluations based on data-supported analyses. Automated forecast reports and dashboards are transparently available to everyone. This means that you do not use valuable resources for manual evaluation, but invest them sensibly in forecast-supported planning and ensure your business success.
Sources:
Whitepaper Best Practice Digital Forecast – Upheaval in planning, reporting and forecasting | Prof. Dr. Claus W. Gerberich (05/2019)
Application possibilities and limits of machine forecasts | News from the Digitization Center | FH Upper Austria Faculty of Business and Management (06/2021)
https://www.haufe.de/controlling/controllerpraxis/forecast-controlling/methoden-des-forecast-controlling_112_453404.html
https://www.controlling-wiki.com/de/index.php/Forecasting
https://de.wikipedia.org/wiki/Prognose