Match your planning with future

Predictive planning in practice is nothing more than management conducting planning exercises (rolling forecasts) at regular intervals during the business year using simulation to map external developments in order to take a reliable forecast for the next period of time (whether month, quarter or year) and, based on this, to make the right decisions. However, the in-depth analysis used for strategic planning in the past has now been joined by new tools and methods such as anticipatory strategies and simulation.

THE ADVANTAGES OF Predicitve Planning

Cubeware sample image - advantages of a bi solution for the application of predictive planning
  • Extremely effective processes – also for operational planning – coupled with significant time-savings.
  • No annoying obligation to complete excessively detailed sub-plans.
  • No more gruelling attempted explanations for variations between actual and forecast planned data.
  • No fear of facing cash flow and balance sheet perspectives.
  • Less time spent on the planning process for operational planning.
  • Minimised susceptibility to errors in strategic and sales planning.
  • More precise planning data for short-term forecasting.
  • Better decisions based on sound planning.

Predictive Planning - strategic planning with methodology

The individual steps of the planning process:

  • Generate data from the past and integrate plausible future developments.
  • Use statistical methods and pattern recognition in planning software.
  • Repeat simulation to optimise the collected planning data in relation to recognized patterns in the past (rolling forecast).
  • Identify influencing factors, dependencies and cause-effect relationships.
  • Include external factors (e.g. competition, suppliers, seasonal elements) for sales planning.
  • Represent possible, realistic future scenarios.

Do you wish to use predictive planning for planning in your company? – This is how we proceed with implementation!

Working together with the experts from Axians and Cubeware, you are only 3 steps away from your own predictive planning for your strategic planning:

1. Data collection and preparation

The basis for predictive planning is formed by your company's ACTUAL reports; such data may include, for example:

  • Sales planning data and the results of campaigns that have been conducted.
  • The impact of public holidays, seasonal events and weather.
  • Sales performance as well as the behaviour and (re-)actions of competitors.
  • Stock levels and supplier lead times.
2. Analysis and model choice

Data collection is followed by an analysis of the data records relevant for predictive planning and the choice of the model best suited for producing as precise a forecast as possible in the planning software. The following are some of the models available for strategic and operational planning:

  • SARIMA time series models
  • Linear/non-linear regression models
  • Associative models
  • Support vector machines
3. Continuous application of model

Accurate and productive business planning for the next period under consideration – whether month, quarter or year – will only result if the planning exercise is conducted at regular intervals during the business year (rolling forecast) with a simulation of changing overall ACTUAL data.

The increased flexibility in decision-making resulting from more efficient strategic planning can also provide your business with a significant advantage in the relevant market environment.

GET IN TOUCHEnter Data now and learn more about our solution for Predictive Planning!

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Axians IT Solutions GmbH – the experts for predictive planning in the Cubeware ecosystem

Axians IT Solutions GmbH is one of the largest vendor-independent IT service and software providers in Germany. Business Analytics made by Axians IT Solutions GmbH combines methodology with the latest BA technologies to create a vendor-independent portfolio of solutions. Besides the analysis of data for planning, forecasting and reporting, an important component is the identification and analysis of new sources of data such as feedback from social networks and full-text analysis. The added value is a comprehensive and customised product offering.

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