After the data has been prepared and visualized via dashboards and reports, it is now necessary to use the data obtained accordingly. Thus, the term Business Intelligence continues to encompass methods of corporate performance management, i.e., the support of planning and control processes in the company. Digital planning, forecasting and optimization describes all the capabilities of an IT-supported solution in the company to support users in digital analysis and planning. Learn more about the advantages of Digital Planning here.
Typical questions that can be answered in the context of Business Intelligence with Digital Planning and forecasting:
- Away from "Excel hell": How can the planning process be simplified with digital planning and still remain agile?
- What are the possible applications of the extensive toolbox of digital planning?
- How can Data Science methods, e.g. forecasting, improve digital planning?
- What are the fields of application for mathematical optimization in planning?
How digital planning works:
The digital planning solution includes all of these tasks: Through central data storage with all dependencies and distributed access, all data is networked and mutual influences are defined. Thus, effects, e.g. from sales planning on cash flow, can be identified immediately, compared by means of the scenario function and, if necessary, planned in a targeted manner by Mathematical Optimization.
Data Science complements manual digital planning with statistical methods
- Comprehensive forecasting algorithms automatically detect historical trends
- AI and ML are used to identify dependencies and take them into account in planning
- Statistical methods can be used separately from manual planning or as a supplement to it
- Example: Consideration of seasonalities for sales planning, or correlations to advertising measures
Mathematical optimization provides decision templates and narrows down variants
- The previous methods provide one (or more) planned scenarios, which have to be implemented under given circumstances, e.g. production capacities
- Mathematical optimization calculates the optimal solution under the given parameters from thousands of options for action
- Example: Calculation of a production plan taking into account sales planning, production capacities, costs of raw materials and distribution, markets
Faster decision making
In uncertain times, digital planning can help companies make decisions quickly. Scenarios are considered, dependencies resolved, consequences presented. In seconds, large teams are provided with the information they need; conversely, global teams provide the company with data that is vital to its survival.
Central knowledge instead of seperate hunches
In addition to speed, traceability and trust are key factors in digital planning. The central, quality-assured data storage as well as access rights and defined process flows make information and its procurement transparent: All users access the central data storage via different paths (Web, Excel), which incidentally provides the necessary functions required for planning purposes due to its analytical character.
Data Science as valueable addition
Data Science, whether it be forecasting or decision optimization, usefully complements digital planning. Hidden correlations become visible and potential alternative actions are shown. Integrated into the planning process, these additional possibilities create comprehensive intelligence that directly benefits the business process.
From analysis and planning to forecasts and optimization – examples:
The planning solution forms the nucleus of the application: "IBM Planning Analytics" (formerly "TM1"). The solution is optimized for planning applications: the central data storage does not only ensure common consistent data access across all access options, but also a powerful engine for all types of calculation: aggregation distribution (spreading), rules, etc.
For more information about IBM Planning Analytics, click here.
Forecasting or Data Science is a special discipline in Data Processing, which uses mathematical methods (statistics or Artificial Intelligence / Machine Learning) to identify connections or calculate time series into the future. We use the integration of IBM Watson Studio and IBM Planning Analytics to calculate forecasts in real time from past data.
Here you can find out more about Data Science with IBM Watson Machine Learning or Watson Studio.
Whether with or without Data Science, different scenarios often have to be considered and evaluated in course of planning. Above all, framework parameters must be adhered to: production capacities, unit costs and prices, transport routes, etc. Often there are many – sometimes competing – inputs on the way to the goal, with millions of possible combinations. Mathematical Optimization uses all parameters and boundary conditions to determine the optimal combination to achieve the business relevant goals in a very short time.
Here you can find out more about Decision Optimization with IBM Decision Optimization.
Our services for digital planning, forcecasting and optimization
Depending on the scope of the requirements, a planning project usually starts with the definition of a data model and with the transfer of the relevant data from the previous system into the planning system. Calculations are then specified, evaluations created, and planning processes defined. Data science is integrated into the planning process as an expansion stage, or mathematical optimization is used to resolve conflicts, e.g. between sales and production planning.
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