Who hasn’t experienced this: A new round of corporate planning means a lot of stress, overtime and repeated, tiring discussions about its relevance. Companies are therefore looking for ways to produce their plans and forecasts in less time, with less effort and with better results, because in a volatile market environment characterized by crises, there can no longer be “business as usual”, even in corporate planning. For many organizations, modern technology around machine learning (ML) and the cloud, as well as its growing ease of use, offer a great opportunity for optimization. In the context of corporate planning, predictive planning and forecasting, it is therefore a major trend to use predictive models based on statistical methods and ML for forecasting and thorough analysis. Predictive planning can deliver substantial benefits, especially in accelerating the building of forecasts, simulations and scenarios as well as underpinning decisions in dynamic markets with little effort.
This worldwide online study was conducted from May to June 2022. It was promoted within the BARC panel, via websites and to newsletter distribution lists. A total of 295 people took part, representing a variety of different roles, industries and sizes.
- The proportion of “doers” is increasing, so it’s time to get on board
More and more organizations are using predictive planning and forecasting to exploit the potential of ML and predictive technologies in corporate planning. One of the major challenges here is to quickly generate and update meaningful plans with little effort. This also increasingly applies to forecasts and simulations. The survey results show that 27 percent of companies are already using predictive planning productively, and 35 percent of large companies are using it at least to some extent. By comparison, only 4 percent indicated that they supported corporate planning with predictive planning in a BARC study back in 2020.
- Almost all who do it benefit from it
Of the companies that are using predictive planning, almost half are already achieving measurable benefits, and just as many expect their investments to lead to significant improvements soon. Among them, there are hardly any companies that do not expect any benefits. Nearly every organization that adopts predictive planning is likely to profit from it. This is a powerful argument to convince decision-makers to use it.
- Concerted measures help more than individual actions
While most companies achieve improvements through investing in predictive planning, those that adopt it as part of a broader transformation are more successful. Well aligned actions deliver more benefits than isolated measures alone. For the majority of organizations surveyed, initiatives to deploy predictive planning are part of a broader business transformation. The data clearly shows that more benefits are achieved when initiatives are embedded in a broader business or finance realignment, as this often encourages synergies and allows more resources to be leveraged.
- Individual models in data science and analytics tools are favored
Predictive planning and forecasting is most frequently implemented with data science tools (60 percent overall and 72 percent in larger companies). These tools are suitable for implementing a wide range of use cases that are highly individualized and sophisticated. The fact that companies do not shy away from the effort involved shows the high expectations of the potential for accelerating and optimizing planning and forecasting. Specialized planning solutions, which form the backbone of corporate planning in many organizations, are rarely used for predictive planning. Many of these tools either do not provide the functions required or their often preconfigured functionality does not offer the flexibility needed for the demanding tasks in question.
- Partial automation of forecasts is the most common use case
Most of the companies leveraging predictive planning today are deploying partially automated forecasts. These accelerate the creation of forecasts and relieve planners of repetitive tasks without taking away their responsibility. Machine forecasts extrapolate target figures on the basis of historical data and drivers but offer the possibility of manual revision and adjustments. Employees remain responsible for the figures but can incorporate important modifications into automatically generated forecasts. The fact that 70 percent of the companies surveyed believe this application still has a lot of potential is reflected in their desire to expand it further in the future.
Based on the results of the survey and our consulting experience, BARC has formulated the following recommendations to help you align forecasting and planning with predictive planning to current and future requirements:
- Identify promising use cases – beneficial pilot projects are the key to successful deployment
Use cases that are easy to implement and promise great benefits make perfect pilot project material. Evaluate the benefits for your company and use them to market the projects internally to inspire your project sponsors. Clearly defined use cases and formulated goals help to quantify the benefits and to tackle further use cases with the knowledge gained. Be aware, however, that using predictive planning is not a no-brainer: failure is still possible. Accept this and don’t let it discourage you.
- Think beyond traditional financial and results planning – there is often great potential lying dormant, especially in operational areas
Enhancing financial planning is often the main direction of predictive planning. But promising use cases can also be found in operational sub-plans. Data treasures can also be found in areas such as sales, production and personnel with sufficient historic data to be suitable for machine forecasts. Predictive planning can be particularly helpful when lots of planners are involved and existing processes are very time-consuming and resource-intensive. It is therefore worth considering options to make improvements beyond the core finance area.
- Start with your available data and its quality. Which use cases can be implemented from it? Which important key figures can you forecast from it?
A rational assessment of the possibilities, starting from existing baseline data, is essential to set adequate expectations. The potential of predictive planning is great, but the hopes associated with it are often even greater. This makes it even more important to evaluate its potential objectively. Think from the basis – the available data – to the result and not just the other way around. This avoids disappointment and frustration.
- Make sure your management supports you – predictive planning initiatives only succeed with the necessary resources and appropriate support in place
Successful and directed initiatives require sound management support. Convince managers of the potential of the approach. Managers need to approve and commit resources, but also understand the benefits and limitations of predictive models. Above all, decision-makers are the ones who sponsor projects but in the end they must trust the results of machine forecasts so that they can be used for the benefit of the company. Trustworthy decisions can only be made if the information they are based on is reliable and its origin is transparent and understood.
- Bring together sufficient and competent resources – support from external resources can massively accelerate your predictive planning project
Extensive know-how, mastery and skilled resources are the key to targeted predictive planning initiatives. Successful projects require cross-departmental collaboration between business (domain), process and IT experts to find a suitable solution for complex use cases. Invest sufficient time and resources (internal and external) to drive and accelerate your initiatives. Training your employees is of particular importance if you want to be successful with predictive planning in the long term. The use of external resources can accelerate projects to realize powerful solutions faster.
- Evaluate the right technology support for your requirements
A technological foundation and architecture that meets your requirements is crucial to providing sound support for your most demanding use cases. Check and decide carefully which tool type best covers your requirements. For example, is flexibility or ease of use more important? When selecting software, compare several tools of the type that suits you best. Pay particular attention to how they can be integrated into your existing system landscape and the likelihood of achieving initial successes quickly.
- Many companies are already using and benefiting from predictive planning – don’t waste time, jump on the bandwagon!
The results of this BARC study should encourage you to further promote the use of predictive planning and forecasting in your company. The approach is not a theory disconnected from practice but has already been successfully adopted by numerous organizations. Of the companies that use predictive planning, almost half have already achieved measurable benefits and just as many expect substantial benefits in the future. This fact should be incentive enough to evaluate predictive planning for your own company now.
Infographic of the key findings