The deal was 257 thousand, but 200 are entered into the system

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This mistake follows from the previous one. It is important not only to collect data, but also to store and process it correctly. Data quality is one of the main concerns of any company that collects and processes information. According to Gartner , companies lose more than $12.9 million annually due to poor-quality data. Poor-quality data does not reflect the qatar telegram number database company's real processes and does not correspond to the goals and objectives of the business.

If a company collects irrelevant and poor-quality data, it will draw incorrect conclusions about business processes within the company. A simple example: calculating the average check price instead of the median price. If out of 100 purchases per month, 90 are made for 1,000 rubles, and the remaining 10 for 20,000 rubles, then the average check will be 2,900 rubles. This indicator will not reflect purchasing power, because 90% of purchases are made for up to 1,000 rubles.

Often, poor data collection is caused by an excessive number of parameters. For example, there is an indicator of the quality of filling in a CRM system - and companies often ask to record it.

But in reality, the problem is largely imaginary: the reason is that managers, overloaded with the need to record a lot of data, write whatever they have to in some parameters, for example, instead of a real email address .

Or they indicate irrelevant figures, this is one of the most common problems. For example, the budget was 257 thousand rubles, and the manager wrote just 200. This will lead to the fact that neither the average check nor other related parameters will match.