Amazon Business is a Business Reporter’s client.
In recent years, data has taken center stage in the way purchasing works. With technology now able to provide information about how much organizations spend and with whom, and how much unmanaged spending is, data is shaping many important decisions. However, big data and artificial intelligence allow organizations to utilize broader sources of information and trends, helping companies better predict likely patterns of spending and demand, as well as manage risks more effectively.
In Europe, governments and industry associations are encouraging greater adoption of innovation and data insights to promote transparency, sustainability, and competitiveness, while those working in the procurement sector must also be aware of the need to comply with the stringent GDPR data regulations.
There are three main ways in which procurement itself can use data in its daily function:
Supplier relationship management
Data can help build stronger relationships with key suppliers, allowing procurement to pinpoint exactly what is being spent and with which suppliers. Once companies know who their key suppliers are and have better visibility into spending, they can take steps to build even further relationships.
From a risk perspective, this means ensuring they are financially viable and working closely to identify any potential issues that may cause problems. There are also opportunities to discuss cost reduction initiatives, perhaps from economies of scale or through eliminating inefficiencies. Data can help hold suppliers accountable, ensuring that standards and quality do not slip.
Data can help organizations better understand how much spending is tied to individual suppliers and to what extent they are dependent on specific suppliers,” he adds, “and can also identify opportunities to enhance cash flow and sustainability performance. Amazon Business, for example, allows procurement departments to direct internal customers to specific products that meet sustainability or other CSR criteria, such as local or small businesses, through its Guided Purchase tool (a Business Prime resource).”
Demand forecasting
Being able to accurately forecast demand is vital so organizations can ensure they are purchasing the right quantities and keeping the optimal stock level, with the consequent cash flow benefits. In Europe, a diverse business environment, unique market dynamics, and the stringent regulatory environment create a complex framework. Data can help predict consumer needs, as well as identify anything that could potentially disrupt supply chain or transportation links and impact stock levels.
This can be achieved in part by identifying previous customer demand levels and any seasonal, cultural, or weather-related peaks, but can also take into account other sources using big data. For example, it can identify long-term climate trends or potential component shortages and plan accordingly.
This information can also help identify the best time to purchase. Olague gives the example of PCs and laptops, which saw high demand in 2022 as businesses and individuals sought to adapt to the post-Covid scenario. “There was very little stock, so prices increased dramatically,” he recalls. “This year companies have stock, and there is less demand because laptops tend to last an average of three years, but 2024 will be different again. Companies need to anticipate this and plan accordingly.”
Cost optimization
Data can also identify cost reduction opportunities, potentially as a result of previously unrealized insights about total spending, which could present opportunities for fee reductions or identify cases where the company may be holding excessive stock. It can also highlight spending categories where the company is paying too much and it may be appropriate to conduct a competitive bidding process or look for alternative suppliers.
To learn more about how Amazon Business can help you gain greater spending visibility and reduce unplanned expenses for smarter business purchases, visit business.amazon.co.uk.
