Solutions Review’s Expert Insights Series is a collection of contributed articles written by industry experts in enterprise software categories. In this feature, ThinkData Works CEO Bryan Smith offers tips for saving on data management costs in the ‘era of disruption.’
Investing in data and analytics was a major priority for companies in the 2010s; it now makes up a significant cost on company balance sheets due to a lack of transparency and organization in their data strategies. As companies navigate the current economic downturn, improved data management presents significant cost-saving opportunities through identifying redundancies in data purchasing and storage, as well as predicting costly supply chain disruptions.
A major challenge large organizations face is their data strategies often lack coordination and transparency across departments. Without a comprehensive view of their data purchases, organizations are at risk of buying the same data multiple times across different departments and paying to store it in different locations. This increases costs without providing any additional value or insights for the business.
By employing effective data management practices, companies can save money by eliminating these redundancies. A data catalog is a useful data management tool to identify these redundancies and streamline their processes around collecting, cleaning, organizing, and managing an organization’s data. For example, within two weeks of adopting a data cataloging solution, a major Canadian Bank realized they were purchasing the same data in six different departments – to the tune of $1.2 million per year. Identifying these duplications through a data catalog allowed the bank to save money on their purchases and streamline their internal data collection and management processes.
The data catalog also helped to create greater transparency across the organization as it increased visibility into what data was stored where, improving both their data residency oversight and their data governance posture overall.
To further streamline storage and internal distribution when accessing and managing data, companies should also implement data virtualization capabilities. Data virtualization lets businesses centralize their data operations without centralizing their data assets, creating a unified view of data that can be easily accessed without moving or duplicating the data into a warehouse. The result is improved agility, reduced complexity, faster business decision-making, and improved data governance. Ultimately, implementing data virtualization capabilities will allow organizations to leverage their data assets more effectively to gain greater competitive advantages.
Data Management Costs
Predicting Supply Chain Disruptions
With the global pandemic, the Suez Canal debacle, climate change disasters, and the Russia-Ukraine war, companies have experienced many unprecedented supply chain disruptions over
the past few years. With each evolving disruption, companies taking a reactive approach continue to scramble to find new suppliers and experience major delays as a result – all causing significant losses in profit. A 2021 survey found global supply chain disruptions cost large companies, on average, $184 million a year. However, these disruptions and delays were and continue to be avoidable.
By using data management tools, organizations can gain insights into their operations and identify weaknesses in their processes that could lead to future disruptions. Data observation tools like a data catalog provide decision makers with an overview of the connections between different parts of the business, allowing for more accurate predictions about how any changes in one part of the system might affect other areas. This gives businesses critical insight into their data ecosystem without disrupting their data operations. By layering external data – sanctions lists, weather patterns, abnormal activity, fluctuations in demand – on top of existing processes, businesses can create a multi-dimensional view of their supply chain that notifies them early about events that might impact an organization’s suppliers, or their suppliers’ suppliers, before they occur. This helps companies plan ahead and make informed decisions when analyzing their supply chain in the long-term.
Furthermore, having access to clean and organized data also allows businesses to better understand customer needs so they can anticipate demand shifts as well as industry trends that may impact their operations. With this information at hand, companies are better equipped to make informed decisions on resource management during times of uncertainty or disruption.
Transitioning from a ‘Wait-and-See’ to a Data-Enabled Approach
The automotive industry’s supply chain was hit particularly hard by the Russia-Ukraine war. Every hour lost from slowdowns and shortages is estimated to cost manufacturers US $1.3 million. Canadian auto parts manufacturer Martinrea was one of many companies who saw their supply chain disrupted as manufacturers and suppliers they relied on were negatively impacted by the conflict.
In the politically fraught climate, maintaining a reactive ‘wait-and-see’ approach was too risky – to protect the company’s bottom line, Martinrea partnered with data experts to implement a Supply Chain Resiliency Platform that would allow the company to collect, analyze, and proactively act on data about their suppliers, and their suppliers’ suppliers. The platform informed decisions about how to effectively manage their entire supply chain, and provided increased visibility into all layers of their supply chain to predict potential issues and pivot early to prevent business-impacting delays.
Using this technology, Martinrea successfully identified 50 suppliers that were negatively impacted by the conflict, effectively extending their analytical scope beyond direct suppliers and into second- and third-degree relationships. At the outset of the engagement, Martinrea estimated that the outcomes of this implementation would result in more than US$40 million in annual value from avoided disruptions and optimisations.
By leveraging the power of data management, businesses can improve their financial performance while also ensuring that operations run smoothly despite any potential disruptions. From identifying redundancies in data purchasing and storage to predicting supply chain disruptions, data management tools not only save money but also improve trust and transparency across organizations.
- 3 Ways to Save on Data Management Costs in the Disruptive Era - March 30, 2023