In today’s data-driven world, it is difficult to believe there are still organizations out there that do not have a good handle on their own data. While it is possible to list out and describe numerous benefits of a good Data Management strategy, this article will focus on some of the risk involved in ignoring data management, or not having a cohesive strategy for business data. We will break down the primary risks in two main categories: operational/technical risk and business risk. This will provide organizational leadership with a better understanding of why they need to pay attention to their data. While the risks listed below are not the only risks, they are the primary drivers towards making business decisions and still maintaining regulatory compliance.

Operational / Technical risks:

• Performance Efficiency – With a well-architected data strategy, data will remain in the right systems, so the required applications or users have access to it quickly. By archiving (or data warehousing) older data, it can keep operational transactions running more efficiently, allowing for greater productivity for users and better customer experience for customers.
• Resource Usage – By maintaining clean master data, organizations end up with a single source of truth, which can be maintained for multiple systems and applications in a single place. This reduces duplication, and can reduce the resources required to store, process, and query data, thus minimizing technology expenses and improving overall profitability.

Business risks:

• Missed Opportunities – Without a good understanding of an organization’s data, analysis to determine business risks or potential new ventures will not be available, causing organizations to miss out on additional profits. As an example, consider data that shows a company’s primary product gets a lot more sales on Mondays in June, more than any other time period. (In this simplified example, we are not going to factor in why that might be.) Organizations that have this data readily available can then make determinations to focus promotions and business drivers more during this time, and not worry about spending additional marketing dollars during other periods.
• Time To Market – With quality data and supportive analytics, organizations can take advantage of emerging technologies such as machine learning, robotic process automation, and AI to complete work faster and bring new products to market quicker, thus shortening the investment time and generating sales sooner. By becoming first to market, an organization could also get a good advantage over competitors and drive more customer acquisition.
• Compliance – As privacy continues to expand as a priority, organizations are falling under more, and stricter, compliance rules (think GDPR, HIPAA, SOX, etc.). Arranging data in a logical, coherent fashion, and classifying it correctly, allows for better access controls and policies to both limit access only where it’s needed, as well as audit any access that does happen. This can greatly help in passing audits, as well as reduce the risk of data breaches, data exposure, and even data loss or corruption. In many cases, companies that do not have a good data strategy do not recognize these risks until they fail an audit, or a breach has already occurred, which could come with significant remediation costs.
• Customer Experience – Studies show that customers are more likely to stay on a website, or make a purchase, the more engaged they are. The more data you collect about your customers (maintaining security and privacy of course), the better the customer engagement, and the greater likelihood of customer satisfaction, new customer adoption, and customer retention. All of these relate directly to bottom-line revenue and provide great value for a company.

Some organizations are more cost-conscious and ignore data management, or put it on a future roadmap that is lower on the priority scale. Just being aware of some of the risks called out here can help organizations overcome them, or at least make a plan to reduce them. The cost of enabling a comprehensive data management strategy are generally far less than the costs involved in remediation for an issue, and frequently even less than potential revenue gains from timely decision making based on accurate data.

The Bottom Line:

Ascend Technologies can help your organization define, monitor, implement, and take advantage of a holistic data management strategy, working as a partner in the success of any organization.

Written by Andy Maser, Data Architect