Democratizing data is one of the top trends in 2022. A recent survey found that 90% of 500 executives surveyed have prioritized data democratization for their organizations. Yet, 75% of business executives admit few data projects produce actionable insights.
Despite the promise of better decision-making, improved efficiency, and faster pivoting, only 60% of respondents say their businesses are effective in delivering equal access. For many, the problem is unusable data. Data scientists spend almost half their time preparing it for accessibility.
For manufacturers, the problem is compounded by the slow progress toward digital transformation. Although manufacturers have transformed factory floors, their business operations still lag behind. How can manufacturers expedite their operational changes? How can they ensure that their data democratization delivers the expected benefits?
What Does Data Democratization Really Mean?
A standard definition of data democratization is:
An ongoing process that makes data available to employees regardless of their skill set. The data is curated and accessible in a way that lets employees work comfortably and confidently.
Yes, data democratization means making data accessible, but it also requires:
- Curating data to ensure data integrity
- Ensuring that employees are data literate
- Providing tools so employees can comfortably work with data
Without a comprehensive plan for data democratization, manufacturers will become part of the 75% that fail to realize data’s full potential.
Curating Data
Breaking down silos and giving employees access to data from across the enterprise may meet the definition of democratization, but it falls short of delivering a usable solution. Take materials outsourcing as an example.
An electronics manufacturer has collected the spreadsheets from procurement that hold information on parts and materials used in manufacturing. They have loaded them into a database that is accessible to everyone involved in the design and manufacturing of its product line. Six months after the database deployment, individuals are back using their spreadsheets.
Why? The company failed to curate the data because it lacked a data management strategy.
When the data was merged, no one checked for duplicate records or missing data. The information was converted to a .csv file and mapped to database fields. If a part number appeared on three spreadsheets, it appeared three times in the database.
When a design engineer or a procurement agent queried the database, three records were displayed for the part number. Should they select the supplier with the lowest price? Was the pricing related to quantity? Was the first entry the preferred choice?
Without curated data, employees are forced to make a decision that could result in lower-quality materials or delivery delays. Employees might spend hours calling around to determine which record is the best one to use. Soon, they have reverted to their old spreadsheets or created new ones. Using the data was too risky, and verifying the data was too time-consuming.
Even if the original data is cleansed to remove duplicates and supply missing data, companies may forget to curate updated data. Who decides if a vendor should be removed? Specifically, how is pricing updated? How is a new supplier added to the database?
The first step in democratizing data is not making it accessible but ensuring it is reliable.
Providing Tools
For employees to evaluate suppliers of direct materials sourcing, they need tools. It’s not just parts or materials; it’s also determining technical requirements, compliance standards, and contractual terms.
Technical Requirements
For example, electronics manufacturers often have specific technical requirements. Finding the right supplier may require input from engineering, product development, and procurement. What tools are available to share information?
When engineering sets the specs, do they have access to existing vendors who might be able to supply the part? Do they have the ability to indicate alternative specifications if necessary? For many manufacturers, it’s a back-and-forth process between engineering and procurement because engineering does not have the tools to communicate alternatives to procurement. Data visibility is restricted without the right tools.
Quality and Compliance Standards
Quality requirements are part of direct material outsourcing. The details may be part-level metrics or system certifications. Whatever the standards, they need to be established before sourcing begins.
Engineers may evaluate a supplier’s capability before setting specs, or procurement may be tasked with ensuring that quality standards are met. In either case, the information should be democratized, so it is accessible to everyone.
Beyond making the data accessible, manufacturers need to provide tools that enable employees to quickly evaluate the collected data. Having better visibility allows a more comprehensive analysis of a supplier’s capabilities. Before procuring parts, knowing the supplier’s quality assurance program and any past issues minimizes product defects.
Delivery Schedules
Direct material sourcing resides on the critical path for most manufacturers. Without direct materials, delays happen, products are unavailable, and revenue declines. Given the criticality, why don’t manufacturers provide tools to analyze delivery track records?
Finding qualified suppliers that understand the technical requirements of electronics and guarantee delivery is time-consuming. That’s why some companies have procurement specialists who focus on specific suppliers or materials. Unfortunately, specialization means that when the agent is unavailable, nothing happens. With the right tools and democratized data, manufacturers can reduce the need for specialization.
Training Employees
Providing employees with data management tools means training them on how to use them. Companies cannot assume that individuals will know how to use the tools to deliver the desired results. Unlike other subjects, data literacy is not a skill that is taught in educational systems. A recent survey found that less than 30% of the US workforce feels data literate.
Data literacy requires a skill set that includes reading, manipulating, communicating, and producing data for critical use. That process involves using the right tools for analyzing and presenting data. The more proficient employees become in understanding and presenting data, the more efficient the procurement process becomes. Approvals move faster because the information is easy to digest.
Educating employees on the different aspects of data management can help improve data quality. As employees become more knowledgeable, they can communicate their data needs, improving results. Once people understand the importance of data integrity, they are more conscious of the impact of a data entry error.
Why Do Companies Need Democratized Data?
Manufacturers and suppliers cannot realize the benefits of data democratization unless they go beyond data collection. They need to provide individuals responsible for direct materials sourcing the tools that lead to stronger price negotiations, more sources for the same materials, and better decision-making.
Consolidating direct materials sourcing into a single source of truth provides procurement with needed information for securing the best possible price. They can use data from across the enterprise to decide on the best supplier for specific components and locate alternative supplies should the supply chain be disrupted.
Training employees on the fundamentals of data management combined with the right tools can turn every employee into a data analyst, which is what data democratization is about. It’s only when data democratization is fully implemented can manufacturers realize improved efficiencies, better decision-making, and faster pivoting when the unexpected happens.
Democratizing data is an ongoing process that requires consistency. Using Part Analytics’ platform ensures data consistency from multiple, disconnected sources to deliver democratized data. It provides a data management tool that enables better sourcing decisions across the enterprise.
As Donna Hagerman of Part Analytics pointed out, “Taking direct materials sourcing digital doesn’t work unless companies are willing to put the effort into managing and democratizing the data.”
