Contextualization
One of the most important areas within a company's logistics segment is the area responsible for planning. One of the main responsibilities of this area is to centralize information from other areas, such as sales forecasts and production capacity estimates. With this data in hand, production plans, raw material receipt plans and even customer delivery plans are formalized.
Planning, when carried out efficiently, allows the organization to meet demand with greater organization, reducing costs associated with shortages or excess products. This directly contributes to financial gains and greater competitiveness in the market.
Types of indicators
Therefore, it is essential to monitor and measure the indicators involved in the planning process on a regular basis. In other words, it is essential to compare the forecasts made with the actual values determined after officialization. In this context, three concepts that are widely used in monitoring indicators emerge: Accuracy, Adherence e Bias.
Accuracy
A Accuracy This is the ability of a forecast to accurately reflect the actual values obtained. This indicator measures how close the planning is to reality, and is crucial for assessing the quality of the input data and the predictive model used. Accuracy can be measured using the formula below.
Formula 1: Calculation of the Accuracy Indicator. Source: ILOS
Accuracy has values between 0 and 100%, where values close to 100% indicate that the forecast made accurately portrayed reality. In turn, values especially below 50% indicate that the forecast made had low accuracy.
Adherence
A Adherence, in turn, refers to the degree of compliance with a plan in relation to what was officially defined. This indicator analyzes whether internal and operational processes are aligned with what was planned, measuring, for example, the percentage of execution of what was planned versus what was carried out. Adherence can be calculated by percentage of achievement, as follows.
Formula 2: Calculation of the Adherence Indicator. Source: ILOS
Adherence only allows positive values, where values close to 100% indicate that the plan was close to reality. Furthermore, by allowing values above 100%, it is possible to analyze through adherence whether the real value was higher or lower than reality. It is worth noting that values above 100% do not necessarily indicate a beneficial result, since the planning did not correspond to reality, which can have negative impacts on the company, such as excess costs and overload of resources.
Bias
Finally, the Bias refers to the systematic direction of forecast errors, indicating whether estimates tend to overestimate or underestimate actual outcomes. A negative bias indicates overestimation (planning more than necessary), while a positive bias indicates underestimation. It can be measured by average percentage error, as follows.
Formula 3: Bias Indicator Calculation. Source: ILOS
Bias admits values between -100% and 100%, where values close to 0% indicate a balance or absence of errors.
Relationship between indicators
By indicating the ability of a forecast to accurately reflect the actual values found, without indicating whether any errors were due to overestimating or underestimating reality, the Accuracy indicator is commonly accompanied by Adherence or Bias. These, in turn, have similar interpretations and, depending on the context of the organization, one is chosen over the other.
If the company's focus is to specifically analyze planning errors, the use of Bias is the most appropriate. However, when the company wants to analyze the relationship between planning and implementation, it should opt for Adherence.
Planning horizons
Once the indicators to be calculated have been defined, it is necessary to record the projection values, which will later be compared to the actual value.
Measuring indicators over different time horizons is essential to assess the progress and accuracy of planning. A commonly used model is the three-period assessment: M-6, M-3 e M-1, where “M” represents the month of officialization and the forecasts made six, three and one month before the reference month.
This sequential analysis allows the organization to assess the quality of forecasts over time and identify opportunities for improvement, adjusting processes to reduce inconsistencies and maximize operational efficiency.
Conclusion
In an increasingly competitive scenario, it is not enough to just plan – you need to plan precisely. Constant measurement and analysis of results allow companies not only to adjust their operations, but also to anticipate challenges and explore new opportunities. By aligning planning with reality, it is possible to transform uncertainties into strategic advantages, reducing costs, optimizing resources and ensuring greater competitiveness in the market.
