Planning and management control must be continuous activities over time, significantly if their effectiveness and performance can be increased. This often happens when using advanced analytics and the innovative tools connected to them.
These continuous activities require great attention over a short and extended period. However, the practice of nurturing these two topics does not mean they're carried out the same way. For example, suppose the effectiveness and performance can be increased, as happens when one uses advanced analytics tools connected to them. In that case, it's essential to define operational and economic-financial objectives in the short, medium, and long term. With the high integration of planning and management control, many challenges come with it.
In addition to being strongly interconnected, planning and management control activities are particularly complex. Those who must deal with them are faced with various challenges related to the structure and operation of the company, and the answer to these challenges is a digital transformation.
This workflow where advanced analytics are used helps manage the complex interaction between all functions that contribute to planning but with different backgrounds and languages. Without this workflow and strategy, a CFO must spend hours on complex consolidation and number interpretation tasks spread across spreadsheets collected by each department. Analytics tools can replace spreadsheets with features dedicated to simulations and "what-ifs" that are more suitable for the use of advanced analytics, which responds to two challenges related to planning and management control: the slowness both in reporting processes and in the generation of alternative scenarios.
In the first case, we find ourselves with gaps in the final balance that make the comparison with the planned objectives ineffective, and, thanks to advanced analytics, they can be filled with data-driven logic immediately without having to wait for the time of the complete accounting closure often not compatible with those of the decision-making process. In the same way, it is possible to quickly generate countless alternative scenarios for simulation and functional elements for planning and management control but are rarely available in companies that have not yet turned towards digital transformation.
Analyzing the planning activity from a more operational point of view, some areas in which effective use of data has a significant impact: are margins and working capital.
In sales, for example, advanced analytics make customer revenue planning more precise and faster, based on their historical behavior, and leveraging correlations with internal and external variables. This means, for example, being able to consider the Covid-19 effect on sales and, therefore, on planning and management control. As far as costs are concerned, thanks to the logic of predictive maintenance, always based on analytics, it is possible, for example, to improve the maintenance plans of the machinery, better estimating their impact on margins and the income statement. In the management of working capital, on the other hand, by introducing the statistical analysis of the behavior in the payments of customers and suppliers, it is possible to detach oneself from an accounting and documentary approach by obtaining more precise forecasts to optimize and therefore increase cash availability.
Even in the management control phase, data science can positively impact operations. Still, it is essential to consider that analytics is a gradual process. Among the main success factors are the cleaning of data and their sudden availability. Therefore, every company must obtain a correct synchronization and alignment between general accounting and analytical/industrial accounting. In larger realities, verifying data alignment between the different enterprise planning software (ERPs) used by the various companies or business units is also necessary. Often, the foreign company management systems represent heterogeneous, unstructured, and non-aligned sources of data, and preliminary activity of creating a data lake and redefining the data strategy is necessary to enable the predictive processes inherent in planning and management control based on advanced analytics.
Another essential prerequisite to making the most of the advantages of data science in planning and management control is the presence of people with a background that makes them able to interact with the predictive analytics environment. It is therefore often necessary for a cultural transformation that leads the company to equip itself, for example, with a data scientist and with data analysts capable, each in a particular business area, of extracting trends and valuable insights from data in a single context.