Many technology companies worldwide are transitioning how they manage their suppliers and collaborate with their engineering teams. The objective is to become more agile and responsive by accelerating internal decision-making and collaborating with suppliers.
Digital maturity is more than a buzzword. It is a strategic imperative for many procurement teams. By overcoming the challenges and leveraging advanced digital procurement solutions, businesses can unlock new opportunities, drive innovation, and gain a competitive edge.
The Benefits of Digital Maturity for Procurement Teams
While many of today’s leading tech companies are positioned to accelerate their digital transformation and reach the highest levels of digital maturity, outdated methods, organizational structures, and inefficient solutions are slowing them down.
In a recent industry survey by Supplyframe, over 50% of respondents said they were ready to “shift left” and operationalize risk insights throughout the design phase. Shift left is moving or tackling tasks upstream in the process timeline.
The advantage of shifting left is a swift and significant increase in efficiency. It is still early for companies to execute a shift left. Only 16% of respondents to a Supplyframe survey said they have some level of collaboration and alignment between engineering and sourcing teams. Three-quarters of respondents said they are still using ad-hoc sourcing spreadsheets.
1. Increase Efficiency
Digital transformation of procurement operations streamlines manual processes, reduces the time and resources necessary to onboard new suppliers, and purchases order management and invoice processing. Automation eliminates repetitive tasks, allowing procurement professionals to focus on adding value to the organization.
2. Lower Costs
The procurement team helps organizations lower costs by optimizing sourcing strategies and identifying opportunities for supplier consolidation. Real-time data and analytics enable proactive cost management and risk mitigation, ensuring companies make informed decisions that reduce costs.
3. Greater Visibility and Control
Digital transformation improves visibility across the procurement process, from requisition to payment. Centralized dashboards and reporting tools offer real-time insights into spending patterns, supplier performance, and compliance metrics. The insights allow stakeholders to make data-driven decisions that mitigate risk.
4. Strategic Supplier Relationships
Digital transformation in procurement facilitates the cultivation of strategic supplier relationships. By leveraging supplier data and performance metrics, organizations can identify and nurture high-performing suppliers while mitigating risks associated with underperforming ones. This strategic alignment fosters collaboration, innovation, and mutual growth.
5. Agility and Innovation
Agility and creativity are essential for preserving a competitive edge in today’s fast-paced business environment. Digital procurement transformation enables organizations to adapt quickly to changing market conditions, identify emerging trends, and capitalize on new opportunities. By leveraging technology, companies can drive continuous improvement and innovation in the procurement organization.
The Resources Companies Require to Create a Digital Maturity Roadmap
1. Descriptive Analytics (DA)
DA focuses on past procurement data to understand what has already happened based on the data gathered at the time. For example, historical purchases, requisitions, purchase orders, invoices, tax receipts, and goods received notes (GRNs).
GRNs acknowledge the delivery of goods by a supplier and the customer’s receipt. They help procurement teams understand and manage historical data so they can identify trends, patterns, and risks.
DA is the simplest type of analytics to apply to procurement. However, it is essential when analyzing spending patterns, evaluating supplier performance, and incorporating purchasing behavior into a broader procurement strategy.
2. Diagnostic Analytics (DIA)
DIA is a more complex process than DA. Descriptive analysis focuses on the “what” of past procurement data, and diagnostic analytics go deeper to understand the “why.” They get at the root cause of a problem or situation that occurred in the past.
Diagnostic analytics help determine the causes of disruptions in the supply chain. By examining past and present data, diagnostic analytics can explore the cause of the supplier’s delay, for example, by providing insight into whether the event was an isolated incident or a recurring problem that might necessitate switching suppliers.
3. Predictive Analytics (PA)
As the name suggests, companies use predictive analytics (PA) to predict future events based on past and present data. By necessity, these tools tend to be more sophisticated than descriptive data and diagnostics. Processing vast quantities of data often employs artificial intelligence (AI) and machine learning (ML).
Used correctly, PAs identify future spikes in demand based on past trends, allowing procurement teams to adjust stock volumes and take other actions to avoid disruptions. Also, PAs can look at broader data sets, including publicly available information such as weather patterns, to identify potential disruptions along the supply chain that could harm procurement.
4. Prescriptive Analytics (PRA)
Prescriptive analytics (PRA) harnesses the potential of cutting-edge AI and machine learning (ML). Prescriptive analytics can analyze data, make predictions, and recommend a course of action based on the findings. PRL and ML capabilities enable organizations to respond rapidly to changing requirements and constraints.
Many use cases are available that merge predictive forecasting and simulation with prescriptive approaches. One use case is predicting infection risks during surgery and instituting rules to mitigate the risks. The use cases extend to forecasting product orders that optimize responses to fluctuating supply chain demands, which circumvents the use of flawed historical data.
Leverage Predictive Analytics for Procurement Organizations
Since the 2020 pandemic, supply chain disruptions have become commonplace. Consequently, many procurement departments have fought against the current procurement practices and accepted that their internal processes need work.
There are good reasons companies should work toward adopting predictive analytics in procurement, otherwise known as predictive procurement.
The companies that have emerged victorious in the pandemic chaos are those that have made the shift from reactionary to proactive. Those who have failed to shift are likely to struggle for survival.
Alleviating supply chain disruptions requires understanding how and why shortages happen, the relationship between supply chain and procurement, and how the organization’s internal procurement processes can be structured and improved.
The Shift From Reactionary to Proactive Supply Chains
Procurement professionals cannot possibly digest the complexity of the machine-generated decision-making process and the vast amount of data generated daily.
However, by merging internal, historical data with external sources of insight, teams can control costs and improve outcomes by making more informed decisions. It is also possible to anticipate demand changes and how they affect supply and pricing.
Since the pandemic in 2020, supply chain disruptions have become more commonplace. Many procurement departments discovered that their internal processes needed work.
For many years, It has been argued that companies should work toward adopting predictive analytics in procurement, otherwise known as predictive procurement.
The companies that have emerged victorious in the pandemic chaos are those that made the shift from reactionary to proactive. Those that have failed to shift are currently struggling to survive.
Understanding how and why shortages happen, along with the relationship between supply chain and procurement, and how the organization’s internal procurement processes can be structured and improved to alleviate supply chain disruptions are essential.
By merging internal and historical data with external sources of insight, procurement teams can control costs and anticipate demand changes and how they affect supply and pricing, improving outcomes by making more informed decisions.
Once the predictive analytics are activated, visibility along the supply chain will improve, and managers can make decisions faster and more efficiently.