Master your data

Image: Angelica Yiacoupis

From the August 2019 print edition

As business becomes more global and digital, technology is more integral than ever to the way companies operate. This puts a vast amount of information at the fingertips of most supply chain professionals. Companies therefore must process and interpret data in ways that are beneficial to their organizations.

As well, companies must now deal with data in real time, says Maria Greaves-Cacevski, strategic sourcing, pharma services group, at Patheon. Software and information systems support global supply chains and networks, and data is the foundation of that. Without accurate data, knowledge-based business decisions become impossible, Greaves-Cacevski says.

Global business means more risk, she says, and organizations are using more data systems than ever. There are online systems such as SAP and Oracle, and even tools like Excel spreadsheets remain common. “That’s why good data is critical to any sort of supply chain or procurement network, because that’s the only tangible (thing) that we can make any sort of purchasing decisions, logistical decisions (from),” she says.

The quality of an organization’s data is affected by the rate of human error in dealing with that data, Greaves-Cacevski says. Typos, for example, can affect data quality. Clarity is paramount. Many companies therefore will accept orders only from SAP, she says. As well, real-time data is critical, she says. With data snapshots like forecasts, organizations open themselves to risk. Circumstances change and an inventory count may have adjusted inventory levels. Another supplier could then place an order that uses whatever inventory was shown. A new client means the demand forecast goes up. But while a forecast is merely a snapshot, real-time data shows what’s actually happening.

The concept of garbage in, garbage out is critical to planning, Greaves-Cacevski says. If an organization’s warehouse management system isn’t connected to a customer relationship system, which isn’t connected to demand flow and so on, each functional group remains disconnected, she notes.

“All of these systems are connected through data,” Greaves-Cacevski says. “You input data to place a buy. You input data to release and receive inventory. You input data to pay for that released and received inventory. A lot of cross-functional teams rely on the accuracy of data.”

Like having no data, bad data comes with risks, Greaves-Cacevski says. Regularly reviewing data helps practitioners to become more familiar with its accuracy. Procurement often bases decisions from forecasts, which often comes from entities like customers, suppliers and even from within the procurement team itself. Monitoring data helps validate where changes occur and therefore aids in predicting what’s going to happen, she says.

Communication is key
Having a consistent format for how data is communicated and received is useful, Greaves-Cacevski says. Sending data as a snapshot in a format that can’t be edited or manipulated—for example a PDF—provides the sender peace of mind. But it creates the potential for error if the receiver must transcribe that data in some way into another format or document. If the receiver is in a hurry, they may keystroke the wrong number or value. That can create a trickle effect, spreading inaccurate data to others.
“We need to make sure that we have a consistent way of communicating or transcribing our data,” Greaves-Cacevski says. “It might be more effective for me to give you Excel. You can use the Excel because that’s pretty common to most of our ERP systems. That way it’s easy to upload and you are uploading the accuracy of the data.”

As well, ensure data isn’t over- or under-communicated, Greaves-Cacevski advises. When communicated down, data must be more succinct and granular. When communicating up, it may be enough to provide the big picture, or how information affects a specific goal or target. “You need to be able to show your data in a way that your audience can capture the essence without questioning the data,” she says.

Finally, Greaves-Cacevski recommends having an organization’s master data steward or team regularly vet data in a consistent, regular format. Organizations invite miscommunication when they change the way data is communicated. Doing so can use more resources as an organization struggles to interpret faulty data. “If we’re presenting the data in a way that it can’t be easily understood or interpreted, then we’re delaying how quickly that data can be optimized,” she says. “And we’re also essentially making that data useless.”

Supply chains face a data “tsunami” from procurement, accounting and ERP systems, external business partners and even connected devices, says Mark Morley, director of strategic product marketing at OpenText. This data impacts business leaders’ decisions and making sense of it is a challenge for many companies. That data must be timely and accurate.

Reducing time and improving the speed of information flows is important, Morley says. For example, seamlessly exchanging advance ship notices (ASN) between a supplier and car manufacturer is important because this notifies the manufacturer when an inbound shipment will arrive at the factory gate and when parts can be fitted to a car. This information is important as part of a just-in-time production system. Ensuring that the notice is in electronic format so it can be exchanged seamlessly between business systems is critical.

It’s equally vital that data exchanged between trading partners be accurate, he says. If inaccurate information is exchanged, it could then be brought into SAP, for example, potentially impacting downstream production systems. Being able to check business transactions before they enter ERP essentially places a ‘firewall’ around applications.

To help ensure good data, rules can be set up and aligned with business processes so that information contained in transactions aligns with business rule templates, Morley says. Many companies have business rules or templates in place to define how data should be formatted and exchanged across the supply chain. There are also tools to help validate data against business rules and information, then accepted or reworked. “Companies should consider leveraging analytics against this transactions data,” Morley says. “This can provide deep insights into whether business transactions have complete and accurate data compared to previous or historical transaction flows, and it can also indicate the performance of the trading partner concerned.”

Morley recommends setting up processes to check data quality and that ASNs match the order (the same goes for receiving an invoice without an ASN already received). Define the rules for each process to which each transaction type must adhere or align. Have some communication, for example a detailed return email, to tell the sender an inbound transaction has been highlighted as inaccurate. This should announce the transaction has been discarded and not delivered. This protects backend systems and forces suppliers to check data accuracy before sending. Morley also suggests considering AI or have workflows to do repetitively analyze transaction flows and ensure data accuracy.

Good data lets organizations make solid decisions, while bad data can lead to poor decisions, notes Jason Newbold, co-founder and COO of DirectRFP, a cloud-based RFP community platform. Having valid data allows procurement teams to understand the marketplace for the goods and services they are looking to buy which is the most critical component in any negotiation, Newbold notes.

“First, validate the source of the data, how was it gathered, how many samples are being looked at and who gathered the data,” he says. “Do they have an ulterior motive? Second, you should start with your current environment and compare the data you’ve received to what you know in your environment. Does it measure up? Lastly, check with peer groups, do they have similar data points and reference?”
Once data has been acquired and validated, organizations can ensure there’s a strategy in place to leverage that data, Newbold says. Typically, DirectRFP’s clients seek to leverage data to negotiate better rates, better contract terms and improved goods and services. Using that data to negotiate with vendors and partners can not only help realize those results, but also help strengthen relationships with end partners—sharing validated data with vendors can help them work to meet an organization’s needs while remain competitive in the market. “Too many times we see the negotiation of a deal lead to a sour relationship as buyers may believe that by berating the vendors they can get a better ‘deal’ and in many cases without good data to help the vendor there is still gaps in the final ‘deal,’” he says.

‘Big data’ is now a common phrase, Newbold notes. The more data, the more likely an organization is to make better decisions. Technology can help gather and correlate that data. “Business continues to become more competitive and we all need to be more efficient in our processes—and with the combination of technology and data we can be,” Newbold says.

As the world becomes more globalized and digital, data is more important than ever. Procurement organizations would do well to ensure their data is as accurate as possible and communicated effectively to help optimize performance.