Spend Analytics: Part 2A - Applications of Spend Analysis
Sourcing and Supplier Analytics
on Apr 17, 2012
The most common application of spend analysis is to identify potential cost savings. However, spend analytic systems can be and are used for much more than that. We explore here some of the common and novel ways that enterprises are using spend analytics.
In Part 1 of this series, we discussed the Evolution of Spend Analysis. Here we will discuss what people are actually doing with spend analytic tools. The answer, it turns out, is “lots of different things” beyond just analyzing spend. We’ll take a look at these in four broad categories. We’ll cover the first two in this article and the last two in the next article in this series:
Sourcing and Spend Analytics
Parts and Product Management
Finance, Performance, and Cross-Functional Applications
While these are described here as separate categories, it is common to combine them together. For example, a company might want to know how much they are spending by supplier or by part.
Sourcing and Spend Analytics
The first and most obvious reason most people want to analyze spend is to find savings opportunities; figure out how to spend less and spend more wisely. This information can then be used to shape and improve a company’s sourcing, contracting, and procurement strategies.
Some of the lowest hanging fruit is in spend consolidation. As a company moves to a centralized purchasing model, they need to find out who is buying what at the department, division, and business unit level. Very substantial savings are possible just by consolidating purchases and achieving volume discounts. This is an ongoing process, not only to reign in rogue spending, but also to integrate the spend of acquired or merged businesses. Almost all solutions will provide a Pareto analysis view, so you can see which few commodities comprise your biggest categories of spend. Some solutions may help further in identifying the areas where the quickest and largest savings can be achieved, such as commodities where the sourcing complexity is low but the impact is high.
By correlating actual spend with contract terms and conditions, spend analytics can check that you are paying the actual contracted price, as well as to see how much is being bought off-contract, what is the reason for the off-contract purchase (e.g. contract expired), how much of that is non-compliant, rogue spending, who is approving purchases above their spending approval limits, and so forth.
You may also use spend analytics to find where suppliers are offering different terms to different business units or geographies. Then you can consolidate the spend on the most favorable terms being offered. Further, you can identify suppliers that don’t provide early payment discounts or favorable terms. You could then negotiate better deals with them or switch those purchases onto p-cards.
A spend analytics system can also highlight where spend is above the maximum or below the minimum volume thresholds in the contract. It can analyze volume discounts to see if the company is missing out on any discount opportunities. It can look for price variance across business units and sites, or compare today’s price against historical prices. In this way you can identify further opportunities for savings.
It is true that a good e-procurement or P2P (Procure-to-Pay) system may provide a few of these monitoring and compliance checking capabilities (for example, automatically enforcing approval limits, or guiding or restricting procurement to preferred vendors) without involving a spend analytics solution. But not all companies have all of their spend managed by procurement systems. In any case, spend analytics tools integrated with contract management and P2P systems, can generally do much more sophisticated types of analysis, monitoring and compliance checking.
Sourcing Events Design
After identifying the opportunities, analytics can be used to help design sourcing events by answering questions like what have we historically paid on average, what have our volumes been, and other data needed to prepare bid packages and decide what should be in the RFP.
Third Party Spend Management
These capabilities can be extended to third parties that are buying on your behalf, such as outsourced contract manufacturers. This may require integrating component data from a PLM (Product Lifecycle Management) system, along with data from the CMs (Contract Manufacturers). This way, the CM can behave more like an extension of the company, with spend data consolidated across the outsourced manufacturing base.
Though not yet in widespread use, spend analytics can be used to analyze total cost. By integrating information about transportation, tariffs and duties, inventory carrying costs, insurance, and other data, the sourcing team can take look at the impact of purchasing decisions on the total cost to the enterprise, find opportunities beyond just reducing the unit cost. This creates a cross-functional view of the savings opportunities.
Spend analytics can be used to identify where you have fragmentation in your supply base, with too many suppliers for the same commodity. They can then help you figure out which ones to keep by showing you things like your total spend with each supplier and their past performance. Here it is important for the system to be able reliably identify suppliers’ parent-child relationships (which company owns which other company), so that spend can be combined for companies that have a common owner/parent. This capability is helpful not only for supplier rationalization, but also for negotiations, to demonstrate your total spend with the entity.
Supplier Diversity / Sustainability
Provided you have the required source data, spend analytics tools can also help look at whether you are meeting supplier diversity goals or requirements (e.g. minority or women-owned). This analysis can show a breakdown by division or business unit, to see if each is pulling their weight. Some holding companies or private equity firms with multiple holdings use these kinds of tools across their portfolios. This analysis can extend to meeting other types of goals and certifications, such as sustainability requirements (carbon footprint, social responsibility, etc.), again provided that you are able to collect and have access to the required data. Here the analytics system may work hand-in-hand with a Supplier Information Management system, which has the actual information and certifications about the ownership, environmental impact, and social responsibility of the suppliers.
When it comes to social responsibility, many retailers, OEMs, and major brand companies have come to realize that the court of public opinion holds them responsible for their entire multi-tier supply chain, regardless of whether the supplier is a tier 1 supplier, tier 2, or further upstream. The type of supply chain mapping required is beyond what most spend analytics systems do today. But large progressive companies are not only holding their suppliers accountable to minimum standards, but also their suppliers’ suppliers and beyond, so these capabilities can and should be developed. Tracking and monitoring sub-tier suppliers also is important in managing risk.
Supplier Performance, Quality, Compliance
Analytics can be used to help monitor and improve supplier performance, including things like performance against service level agreements, quality inspection failure rates, on-time delivery rates, invoice accuracy, and compliance with the company’s supplier mandates and standards (such as using the correct transportation carrier, correct labeling, pallets configured, ASNs received, etc.). The analytics system can identify problem suppliers and then let you drill down to see exactly what you are buying from them, what their issues are, and explore options for resolving those issues (including alternative suppliers).
Some companies also will benchmark suppliers against their peers. This is can be done using your own information about other suppliers. It can also be done using external benchmarks, if you have access to that data. Some supplier network and ERP companies are experimenting with making supplier performance information available anonymously to participating buyers, which can be further used to compare the identify underperforming suppliers.
Supplier Risk and Supply Chain Risk Management
Risk management requires integrating data from many different systems such as supplier management, quality systems, financial systems, and external sources to provide a cross-system and cross-supply-chain view. The analysis often involves a cross-functional team such as members from finance, logistics, procurement, manufacturing, engineering, etc. There are a number of angles that can be considered when using spend analytics for managing supplier risk:
Sole sourcing risks—Identify and highlight sole sourcing of critical parts or materials. Identify alternative sources if they exist.
Supplier viability—Monitor financial data on the suppliers . . . but this tends to be a lagging indicator of trouble. Leading indicators include deterioration in supplier quality, increase in shortages, reductions in on-time delivery rates, order accuracy and other supplier performance issues. Some systems also scan the news and the web for troubling developments, such as law suits, security breaches, or illegal activities at the supplier. All of these raise the red flag for further investigation.
Geography-based risks—Check for geographic concentrations of your supply base, and correlation with risks such as earthquake and other natural hazards, political instability, exchange rates, etc.
Analytics can also help explore and discover options for mitigating risk, such as which other suppliers might be available or whether a geographically-at-risk supplier has plants in other geographies. A more advanced version of this will allow the user to do “what-if” analysis and explore the cost-benefit tradeoff of various risk mitigation options (see Total Cost Analysis, above).
In Part 2B (the next installment of this series), we will look at how spend analytics tools are used for parts and product management, as well as finance, performance, and cross-functional applications.
To view other articles from this issue of the brief, click here.