Anyone working in business understands the importance of a diverse and vibrant base of suppliers. It would be hard to find a company on earth not reliant on at least a handful of these partners to deliver their end products.

In the digital workforce, data acts as the supplier, delivering components necessary to generate new insights and improve performance. Leaders must adopt this mindset if the goal is to transform the company, so all critical operations – from decision-making to customer relationships to innovation – are data-driven. 

Quality over quantity 

The data-centric business is less concerned about sheer volumes of data, and more focused on data’s value. Because data is an essential ingredient in getting things done, it needs to be thorough, differentiated, and reliable. Gathering large quantities of data is important, but usefulness is the priority. 

This isn’t an approach simply suited for start-ups or born-digital companies. Walmart, with 100,000 physical suppliers and 10,000 stores, has applied a data-centric strategy, significantly restructuring how the 60-year-old retail giant goes to market. 

One example of Walmart’s transformation is the “Data Café,” a hub connecting hundreds of datasets both internal (i.e., transactions or user profiles) and external (syndicated data or social media). Data informs the entire company as it strives to compete in a digital age. Data keeps brick-and-mortar stores welcoming, stocked, and secure, even as consumes increasingly more investment. 

A working partnership

In its quest to be data-centric, the company must pursue a working partnership with data much like they would pursue with suppliers of raw materials, components, or services. At the same time, they must calibrate their view of data, realizing it comes in different forms and from a variety of sources.

However, don’t ignore data available across your own enterprise. Many businesses have figured this out, learning to better accumulate data from their own customers and their operations. Every company hosts a wealth of potential data sources – from manufacturing to finance to marketing. Since not all of it is immediately useful, it should be classified into Critical, Strategic, Niche, and Nice-to-Have. 

Physical supply chains are diverse, spanning different geographies, specialties, and capabilities. The data supply chain needs to similarly play a much more dynamic role than what can be collected from just the internal pipeline. In fact, a company’s data supply chain is woefully under-resourced if it only relies on the data it can collect on its own. 

External suppliers can offer broad, high-quality data sets, such as U.S. census data, credit data or weather data. In addition, sources such as academic studies, shipping manifests, or website traffic reports can provide granular data on more specific topics. Also, data can get hyper-targeted by focusing on things like pharmaceutical research or travel patterns in certain geographies, or automotive financing trends in specific zip codes. 

Of course, regulations governing data collection, storage, and usage may pose challenges on how data can be utilized. For instance, some data may have Personally Identifiable Information or other privacy-related content requiring careful handling – rules and acceptable practices vary greatly by country. Synthetically-generated data can help analytics and AI systems move forward by addressing challenges presented by sensitive or unavailable data.

Health and wellness of your data

Just like companies invest heavily in the health and wellbeing of their human employees, a robust end-to-end governance process protects the health and wellbeing of your data. 

Quality control and consistency are necessary to ensure data collection is resilient. Just as a disruption in one part of the supply chain can impact an entire product or portfolio of products, even a small dose of bad data can similarly have wide impacts on the entire body of analysis being done. 

Inviting data in 

Data will help optimize operations and keep the strategy on track and relevant, but only if it is treated as lifeblood instead of an appendage or afterthought. This happens best when it is viewed like the critical supplier that it is – worthy of having a voice, deserving of investment, and subject to high standards. 

Whether it's Walmart, or any company in any other industry, becoming data-centric does not happen by accident. Data, like all key suppliers, must be considered early in the process and must remain a partner over the lifecycle of products, decisions, and campaigns.