In today’s world, data is an invaluable asset for companies, however, many make mistakes in its management that can have serious consequences in decision making and, therefore, in the success of your business. In this article, we will analyze the 5 most common mistakes that can sometimes be very costly for organizations.
- Not defining clear objectives: One of the most common mistakes is not defining clear objectives for data collection and analysis. Instead of setting specific and measurable objectives, companies often focus on collecting as much data as possible without having a clear strategy. A Forbes study found that 40% of companies do not have a clear strategy for their data and 44% do not know how to measure the success of their analytics initiatives. This can lead to the collection of irrelevant data or a lack of concrete action from the data collected.
- Failure to use appropriate tools for data analysis: Organizations can make the mistake of using inadequate tools for data analysis. Often, companies focus on analytics tools that are not advanced enough to handle large data sets. According to a McKinsey study, less than 50% of companies use advanced data analytics tools. One example of this mistake occurred when technology company Hewlett Packard Enterprise (HPE) invested in a data analytics tool that was not right for its business. The tool was too complex for the HPE team and did not deliver the results they expected, leading to an investment of around USD $50 million in a useless tool.
- Lack of data updating and cleansing: Many companies do not devote sufficient time and resources to updating and cleansing their data, which can lead to errors and thus poor decision making. According to a study by Experian Data Quality, 75% of companies surveyed believe their data is inaccurate in some way. In addition, the average annual cost of inaccurate data is $14.2 million for companies in the United States, according to a Gartner report. Companies that do not update their customer list regularly may be sending promotions to customers who are no longer interested in their products and not to potential new customers who might be. As a result, sales may be lost and the effectiveness of their marketing campaigns may be diminished.
- Lack of data integration: Many companies have different systems and tools that are not integrated, making data analysis and decision making difficult. An Aberdeen Group study found that 65% of companies surveyed have multiple data systems that are not integrated. As a result, the company may have a fragmented view of its customers and its overall business. An e-commerce company that does not integrate its data analytics system with its inventory management system may have trouble quickly identifying products that are running low and not making informed decisions about inventory replenishment, which can lead to lost sales and increased warehousing costs.
- Lack of data security: Data security is essential to protect confidential company and customer information. Companies must implement adequate security measures to protect their data from unauthorized access, theft or loss. Often, companies underestimate the importance of data security and fail to take the necessary steps to protect their data. A concrete example of the lack of data security is the recent case of Equifax, a credit reporting company that suffered a major cyber-attack in which the personal data of more than 143 million people in the United States was compromised. It was discovered that the attack occurred due to a vulnerability in the software Equifax was using. This incident has had a significant impact on the confidence of Equifax’s customers and has led the company to pay more than $700 million in settlements and penalties related to the cyberattack.
Data management is crucial to the success of any business today. However, errors in data collection, analysis, updating, integration and security can be costly and have serious consequences for decision making. It is important to have a clear data strategy that is aligned with the business objectives and cross-cutting strategy of the organization so that instead of being a threat, it becomes a source of opportunities and information for making the right decisions.
Sources:
Forbes – “The State of Data and Analytics in 2020”(https://www.forbes.com/sites/louiscolumbus/2020/04/27/the-state-of-data-and-analytics-in-2020/?sh=6e573e95678c)
McKinsey & Company – “The age of analytics: Competing in a data-driven world”(https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/the-age-of-analytics-competing-in-a-data-driven-world)
Experian Data Quality – “The Global Data Management Benchmark Report”(https://www.edq.com/globalassets/edq/documents/research/global-data-management-benchmark-report.pdf)
Aberdeen Group – “Data Integration: The Foundation for Trust in Digital Business”(https://www.aberdeen.com/white-paper/data-integration-trust-in-digital-business/)
