Spend management is a process of collecting, collating, maintaining, categorizing, and evaluating spend data to reduce procurement costs, improve efficiency, monitor and control workflows, and regulate compliance. Spend management affects and manages various activities across the procurement cycle. It includes requisition processing, budgeting, planning, supplier management, contract management, inventory management, sourcing, and product development. Every organization, regardless of their size and type, can refer to this comprehensive discussion on spend management across departments. Download this whitepaper to understand the different elements of spend management and how to optimize it.
Sources of expenditure range across the procurement of goods and services. They include employee salaries, rent, utilities, licenses, advertising and marketing, insurance, training, etc. Sources of expenditure vary from business to business, depending on the nature of the business. Hence, spend management is an activity that every business must carry out uniquely.
Although identification of sources of expenditure is necessary, plotting and identifying an exhaustive list of expenditure sources is a challenge. To help overcome this challenge, either automation at source eradicating duplication or a team of department heads can is the solution. A bird’s-eye view into the spend infrastructure should help identify overlooked savings opportunities.
Ideally, the accounts department is in charge of expenditure data repository. With the help of automation, they can capture and maintain records of spends. Mandating records for audit at regular intervals is always recommended.
While identifying sources of expenditure may have its challenges, centralizing the data into a repository is no mean feat. The data is sensitive and critical and hence cannot be accessible and visible to all. This makes it necessary for the organization to appoint a responsible individual who can categorize and process the data in chunks and have a unified view of the spending structure.
Since expense data is analyzed, interpreted, and showcased to draw inferences and make decisions, it becomes imperative that such information is accurate. Validating transaction entries include tallying the data entries with receipts, inventory, communication, etc. Cleaning the data includes activities such as removing duplicates, errors, spelling mistakes, and such.
Since spend data may not always be accurate due to its manual processing, differences in formats, data fields, etc., standardization is necessary. To do so, establish a format for versatile domains such as currency, dates, etc. For managing your taxonomy structure, follow, here’s a link to the whitepaper “Spend Analysis: Making Sense of Data.”
Spend data comprises various types of spends. These categories and classifications are created depending on an organization’s objectives and operations. It is necessary to keep in mind that the groups prepared by the authorities for this classification should cover all spend to bring them under one view.
Based on the information that one needs, you can categorize data is categorized in more than one way. For example, IT services may be classified as ‘Types of IT services’ or tagged by its ‘vendor name.’ Here, it becomes necessary for an organization to prioritize its needs, which requires the understanding of spend per vendor or spend per activity.
Analyzing the collected, cleansed, and classified spend data will highlight recurring spend activities and other anomalies. It’ll help in calculating aggregates/averages, percentages, etc.
You can achieve the afore-discussed through a human analyst and technologies such as artificial intelligence (AI) and machine learning (ML). Here’s a Hackett Group report that gives cost benchmarking guidelines. This report will help organizations benchmark their employee compensation costs or outsourcing costs and derive a cost-benefit analysis by calculating the ROI.
Execute changes concluded and decided upon based on The project, if introduced from scratch, can be rolled out in phases and spend data can be collected and analyzed department-wise if not organization-wide to test and correct the procedure.
Change management is often challenging activity, and for it to be successful, it requires acceptance and participation of all stakeholders.
Data collected can help you forecast events. With spend management, obtaining accurate and regular data is secure and effective. It enables you to track and identify trends in data to forecast spend scenarios and plan for the slacks and booms.
Data forecasting, as discussed above, depends on the accuracy of the data collected and the ability of the analyst. However, with e-procurement systems that use Artificial Intelligence (AI), categorizing and managing spend data has become a cake-walk. For a detailed look into what an advanced spend analysis structure looks like, refer to this whitepaper.
Spend management, in any organizational lifecycle, gains importance as soon as expenditures start growing exponentially. Until then, firms do not worry about late payments, percentage point discounts, or even vendor performance. The growth of expenses is proportionate to the importance of spend management. If you are in a tough spend management situation, have you considered optimizing your spend process? With the steps discussed, we assure you that it is possible to manage to spend before it goes out of hand.
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