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The Domino Effect of Inaccurate Sales Data

Many organizations use the data collected from each sale carried out in a way that allows them to gain insights into their customers preferences, needs, wants, buying trends and potential opportunities available in their market. It can also be used to measure the performance of the organizations sales teams and track key performance indicators. However, how are these factors affected when the sales data used is inaccurate?

We consider the domino effect of inaccurate sales data on forecasting, resource allocation and an organizations’ credibility.


Forecasting is carried out to predict “future sales revenue” (Gartner_Inc, 2023). These predictions are made based on past sales data and the more accurate the data is, the more accurate the forecast is likely to be. However, when sales data is inaccurate, it becomes increasingly difficult to accurately forecast future sales volumes and revenue streams, leading to poor planning and resource allocation decisions (Flood, 2023).

For example, if sales data shows a sudden spike in demand that is inaccurate, the resulting forecast may be overly optimistic, leading to over-investment in production and supply chain management. On the other hand, if sales data shows a decline in demand that is inaccurate, the resulting forecast may be overly pessimistic, leading to missed sales opportunities and lost revenue.

Resource Allocation:

Inaccurate sales data can negatively affect resource allocation as it can lead to poor or incorrect decision making regarding the allocation of resources for sales and marketing activities (Oboloo, 2023), such as; overinvesting in markets or customer segments that aren’t actually profitable or underinvesting in areas that have real growth potential (Balyuk, 2022). Overall, inaccurate sales data can lead to inaccurate resource allocation which can result in lost opportunities, decreased productivity and lost revenue for the organization (Oboloo, 2023).


Inaccurate sales data not only effects the outcomes of decisions made using this incorrect data but it also effects the organization’s credibility in the eyes of its customers and stakeholders. This is because inaccurate sales data communicates false information regarding the organization’s performance and success, potentially resulting in stakeholders becoming sceptical of the organization’s ability to meet their expectations and deliver on their promises (Foote, 2023). In addition to this, customers may become frustrated and distrusting if they are basing their purchasing decisions on inaccurate sales data, as this could lead to them purchasing products or services that do not fulfil the needs as successfully as they were led to believe, explains Foote (2023).


Balyuk, A. (2022, September 5). 5 signs of bad resource allocation and how to improve it with a resource management solution. Epicflow.

Flood, P. (2023, January 24). The consequences of poor data quality for a business.,and%20missing%20out%20on%20conversions.

Foote, K. D. (2023, March 1). The impact of poor data quality (and how to fix it). DATAVERSITY.,is%20mishandling%20their%20personal%20data.

Gartner_Inc. (2023). Definition of sales forecast – gartner sales glossary. Gartner.,impact%20decisions%20on%20key%20deals.

Oboloo. (2023). The dangerous effects of resource allocation syndrome in business. Oboloo Articles.