Spend Analysis: The Window into Strategic Sourcing available in Hardcover, eBook
Spend Analysis: The Window into Strategic Sourcing
- ISBN-10:
- 1932159932
- ISBN-13:
- 9781932159936
- Pub. Date:
- 02/01/2008
- Publisher:
- Ross, J. Publishing, Incorporated
- ISBN-10:
- 1932159932
- ISBN-13:
- 9781932159936
- Pub. Date:
- 02/01/2008
- Publisher:
- Ross, J. Publishing, Incorporated
Spend Analysis: The Window into Strategic Sourcing
Buy New
$64.95Buy Used
$43.35-
-
SHIP THIS ITEM
Temporarily Out of Stock Online
Please check back later for updated availability.
-
Overview
Product Details
ISBN-13: | 9781932159936 |
---|---|
Publisher: | Ross, J. Publishing, Incorporated |
Publication date: | 02/01/2008 |
Edition description: | New Edition |
Pages: | 272 |
Product dimensions: | 6.00(w) x 9.00(h) x 0.80(d) |
About the Author
Read an Excerpt
CHAPTER 1
FUNDAMENTALS OF SPEND ANALYSIS
Every CFO's dream is to be able to cut millions of dollars in costs, not on a onetime basis, but annually — and to keep raising the bar for the procurement and operations teams to squeeze out additional savings year after year. Over the last few decades, most CEOs have focused on driving frontline revenue growth as a means of increasing EPS (earnings per share) and have often ignored or neglected the other side of the equation, namely, the cost. Now, the focus is slowly shifting. In today's global economy, in which more than half of your products and services might be sourced from suppliers in different countries, the ability to systematically manage a large and diverse supply base could well prove to be the single most important differentiator between leaders and laggards over the next 10 years.
Companies who understand this have already implemented strategic sourcing initiatives and are reaping handsome rewards. Take the example of Dave Picarillo, VP of Sourcing at BrainTree Sourcing, a division of Royal Ahold. Ahold, as you might know, is responsible for sourcing goods and services for 6 grocery brands and more than 1200 supermarkets in the United States. Dave also oversees sourcing for Ahold's divisions that operate 85 warehouses which provide goods and equipment to restaurants throughout the United States. In the United States alone, Ahold spends more than $3 billion annually on indirect goods and services.
Ahold launched its strategic sourcing program in 2003. In 2 years, the program had yielded a mouth-watering savings of $350 million just on indirect procurement! What's more, the savings have kept growing each year. Ahold now expects to expand the program to private label goods, expecting to save 5 to 10%. So how did Dave accomplish this? What did he do that others should be paying attention to?
Ahold's biggest problem prior to this new strategic sourcing program was getting good visibility into their category spend. Ahold's traditional methods relied on distributed category teams submitting spreadsheets to the procurement team. Because of different standards and the differing quality of data, the spreadsheets and the data were not tightly organized at the corporate level. Therefore, Ahold was never able to get a clear, corporate-wide view of what it spent. Without this visibility, Ahold could not identify overall efficiencies and weaknesses of its sourcing process. With this in mind, the first step that Dave took was implementing a Web-based spend analysis application. With the new system, procurement and category managers at Ahold could get corporate-wide spend visibility through a Web browser from anywhere in the world. Managers could "slice and dice" the spend data in real time, identify opportunities for vendor consolidation and other savings, and generate actionable reports on a continuous basis, which gave Dave the foundation to implement an integrated Web-based supply management system which could be used to create and manage savings programs that could be monitored on a continuous basis.
In short, Dave replaced the ad hoc, disconnected sourcing processes with an integrated strategic program, which not only produced lower spending on goods and services, but also shortened the production conception to reception time in stores. The spend analysis application empowered category managers to review more spending projects in less time. The RFx (request for information/quote) portal allowed buyers and suppliers to collaboratively finalize requests for quotes, thus replacing the emails- and spreadsheets-based point-to-point system. Furthermore, the new system also made it possible to score supplier performance. Managers in different divisions can now rate the same supplier across different categories. Finally, Ahold can now leverage the optimized bidding and allocation capabilities of the tool to ensure that contracts for certain categories such as washing windows are given to local providers.
The payoff from such systems has been staggering to those on the cutting edge. According to a 2005 ROI leadership report in Baseline Magazine, GlaxoSmithKline (GSK), a drug maker and distributor in the healthcare industry, boasts of an annual return of 5451% from its sourcing programs — and this is just the beginning. As companies gain more visibility and control in sourcing, they can hold suppliers more accountable, negotiate for better terms and conditions, and channel the learning process across the entire supply base. Managers at Ahold went through about 3 days of training, followed by biweekly meetings on best practices. Ahold incurred about $1 million in costs to implement the complete system. Thus the benefits of $350 million in savings far exceeded the cost.
WHAT IS SPEND ANALYSIS?
Spend analysis is the starting point of strategic sourcing and creates the foundation for spend visibility, compliance, and control. Spend analysis organizes procurement information via supplier hierarchies, commodity alignment, and spend amount, in order to:
Ascertain true category spend
Identify strategic sourcing opportunities through demand aggregation and supplier rationalization
Identify expense reduction through increased compliance — in the form of vendor rebates, maverick spend, contract compliance, and budget variance
The savings can range from 2 to 25% of total spend.
Basics
Let us simplify the above definition even more. Put simply, spend analysis is a process of systematically analyzing the historical spend (purchasing) data of an organization in order to answer the following types of questions:
What was the corporate-wide spend associated with each cost center last year? Does the aggregate amount enable me to increase leverage with suppliers?
What are the top commodities? What has the spend trend been over the last few years? Which of these commodities represent opportunities for spend reduction?
Which suppliers are the most valuable and strategic?
How much am I spending with preferred suppliers? How much am I spending with poorly performing suppliers?
What percentage of spend is associated with contracts?
The idea is to be able to examine these reports and identify opportunities for savings. For example, if the spend associated with nonpreferred suppliers is high, this category is clearly where spend "leakage" is occurring because the prices and terms negotiated with preferred suppliers are usually better than the prices and terms that are in effect with nonpreferred suppliers. Similarly, if a particular commodity is fragmented (i.e., is being sourced from many suppliers), this commodity could be consolidated into fewer suppliers and better prices could be negotiated by channeling a higher volume of spend through them.
If your purchasing or finance department can readily provide accurate answers to the above questions, then your company has perhaps already implemented a good spend analysis solution. If the latter is not the case, then you should challenge the accuracy of the answers. Chances are, though, that your purchasing department will not be able to provide the answers. In fact, there is a high likelihood that you will not receive even one answer. If that is the case, you are not alone. A vast majority of enterprises have not yet implemented spend analysis.
At this point, you might wonder what is so difficult about analyzing purchasing data. The above questions seem simple enough to answer. To understand this situation, take a look at Figure 1.1, which shows a few transactions pulled from the AP (accounts payable) systems of two divisions of a corporation. Examine these transactions and try to quickly answer the following questions:
1. How much did the company spend on personal computers?
2. How much did the company spend with IBM on software?
3. What was the spend associated with IT and professional services in Q3 and Q4 of 2006?
You will quickly figure out the challenges in analyzing this data. The two divisions have separate cost centers and separate GL (general ledger) codes, which have not been integrated. You may also have noticed that all of the transactions belong to IBM, but this might not be easily apparent if you did not know that Lotus Corporation, Ascential, and MRO Software are subsidiaries of IBM. You might also have noticed the many different variations of the name IBM. Also, the various fields in the two extracts are not identical. Division 2 transactions do not show commodity codes or SIC (standard industrial classification) codes. They do contain descriptions, but they are not very good.
In short, the data residing in business systems are many times not cleansed, enriched, consolidated, and organized at the corporate level. This makes it very difficult to make like comparisons. Moreover, the information is finance-centric. The various GL, cost center, and other codes were created to facilitate accounting, not purchasing. Figure 1.2 shows a procurement-centric view of the same spend, in which spend is aggregated by categories. This view is so much more meaningful! A few facts immediately catch your attention — Division 1 is spending much more money on personal computers and computer maintenance than Division 2, even though they spend less money on software than Division 2. Why could this be happening? Is it because they have old legacy computers that they are trying to replace? You can also see that Division 1 is not buying any servers from IBM, but is spending heavily on IT consulting. If the two divisions can combine their spend, they can negotiate better terms with IBM for both divisions across all categories.
Now extend this analysis to millions of transactions across hundreds of systems and you will begin to appreciate the challenges as well as the power of spend analysis. For example, Figure 1.3 illustrates a report that shows the top ten commodities by spend. This report is very useful because it immediately shows the commodities that you should be focusing on for cost reduction based on spend volume alone. However, this report does not give you much information as to whether the opportunities are related to supplier consolidation, maverick spend, contract compliance, or others. This report also does not tell you how easy or complex it will be to source these commodities. Thus, you would need to overlay other reports on this report in order to pinpoint the exact opportunities.
A glance at Figure 1.4 immediately reveals the fact that professional services is the most fragmented commodity. Professional services might represent a better opportunity for supplier consolidation than electronic components, even though it has a lower spend.
If spend analysis is so useful, why haven't companies widely implemented it? In a survey of 400 procurement professionals conducted by Supply and Demand Chain Magazine, just one third (32%) of respondents reported that their companies use spend analysis all the time to help set a baseline for sourcing activities, and only 20% reported that they currently use spend analysis software. What are the reasons for such low adoption? First of all, we are talking about analyzing not a few hundred or a few thousand transactions or even a few million. We are talking about tens or hundreds of millions of transactions. The sheer volume of data makes this an enterprise-class application. Yet there is more to the complexity of the situation than just the volume of the data. A total of 41% of the respondents ranked their inability to get data from disparate systems as the greatest challenge to effectively gathering the raw information necessary for spend analysis, and 31% said that they lacked the analytical tools necessary to identify savings opportunities. Consequently, 74% of respondents said they are still using desktop software such as spreadsheets and databases moderately or extensively for spend analysis.
The challenges are not all technical. A majority of respondents (54%) cited the absence of a strategic sourcing process and the mindset within their organizations as key limitations to improving their procurement processes, while 32% pointed to a lack of organizational know-how as a limiting factor.
It is not surprising, then, that 56% of the respondents reported that use of spend analysis at their companies was limited either to individual locations or to a single division, while just 44% reported being able to use spend analysis on a cross-divisional basis.
In Chapter 3 (How to Implement a Successful Spend Analysis Program), we will discuss all of the challenges and best practices for implementing a successful spend analysis program. To embark on that journey, perhaps it might be beneficial to review the history of spend analysis, which will give us a general sense of how the requirements in this area, and the corresponding complexity in the spend analysis applications, have evolved. Then, we will examine the data warehouse approach and investigate if ETLA, or the "Extract Transform Load Analyze" process, which is used to build a traditional data warehouse, is applicable to spend analysis. As it turns out, the spend analysis requirements present various challenges that make it rather difficult for traditional data warehousing to support.
HISTORY OF SPEND ANALYSIS
Spend analysis has its roots in strategic sourcing, which is a term coined loosely in the 1980s to describe the systematic effort started by automotive companies such as Ford and GM to streamline and rationalize their supply base. Prior to that, most companies were pursuing similar goals, but these goals were mostly at a tactical level, and no effort was made in designing a bottom-up process and elevating it to a strategic program with direct influence on the EPS (earnings per share). This "elevation" to a strategic level is credited to the automotive industry, which endorsed these practices perhaps as a direct response to the success of the Japanese companies.
Soon, a number of specialized consulting houses opened shop, with some such as A.T. Kearney at one time having hundreds of consultants worldwide involved in helping companies reduce their purchasing costs. Most of the early programs were designed around supplier rationalization in key commodities. The idea was to identify aggregate spend associated with each supplier, and then to use intelligent segmentation techniques to retain some suppliers and consolidate/eliminate others that were not deemed to be strategically important. Most of the "spend analysis" was thus done only at a supplier level and sometimes at the division and/or cost center level. Often, the DUNS (Dun and Bradstreet, D&B) classification was used to categorize suppliers.
This approach to spend analysis yielded enormous success by the early and mid 1990s, and early supply chain and ERP vendors tried to enter the area with elementary offerings. Most work in the mid to late 1990s was being done by consultants who were targeting indirect spend commodities. With the enormous success of FreeMarkets in their reverse auctions strategy for direct materials, this discipline was formalized into SRM (supplier relationship management) with the emergence of a new class of enterprise vendors such as Ariba and Emptoris that offered integrated modules such as RFx, reverse auctions, bid optimization, supplier performance, and spend analysis for creating and managing an end-to-end supply management program.
In the early 2000s, there was a "horizontal" shift in categories. The early successes in the indirect spend categories paved the way for expansion into MRO (maintenance, repair, and operations) and direct materials. In the last few years, we have also seen "vertical" movement. The low-hanging opportunities in vendor consolidation had already been addressed. Companies now wanted a deeper, granular "look" to identify opportunities such as product consolidation (products that are functionally equivalent), item price variance, unrealized rebates and volume discounts, and others. This desire for a deeper, granular look created the need for much more advanced enrichment platforms (identifying functionally duplicate items is not a very easy exercise) on the one hand and a more demanding application to identify these opportunities on the other hand. Spend analysis thus became the "window" into strategic sourcing — it was the front end that helped identify opportunities and also a back end that helped monitoring and tracking of these savings. In other words, spend analysis became a "must have" for any sensible strategic sourcing program.
(Continues…)
Excerpted from "Spend Analysis"
by .
Copyright © 2008 Emptoris, Inc. and Kirit Pandit and Haralambos Marmanis.
Excerpted by permission of J. Ross Publishing, Inc..
All rights reserved. No part of this excerpt may be reproduced or reprinted without permission in writing from the publisher.
Excerpts are provided by Dial-A-Book Inc. solely for the personal use of visitors to this web site.
Table of Contents
Foreword,
Preface,
Acknowledgments,
About the Authors,
Web Added Value,
PART I,
Chapter 1 Fundamentals of Spend Analysis,
Chapter 2 Business Imperative and Return on Investment,
Chapter 3 How to Implement a Successful Spend Analysis Program,
Chapter 4 Opportunity Identification,
PART II,
Chapter 5 The Anatomy of Spend Transactions,
Chapter 6 Spend Analysis Components,
Chapter 7 Taxonomy Considerations,
Chapter 8 Technology Considerations,
PART III,
Chapter 9 Tracking and Monitoring,
Chapter 10 Spend Analysis and Compliance,
Chapter 11 The Future of Spend Analysis,