Printer Friendly

Cycles of lean: findings from the leanness studies--part 2.

Cycles of Lean: Findings from the Leanness Studies--Part 1" showed that leanness, as measured by long-term inventory turnover trends for more than 1,500 companies, rises and falls in multiyear cycles and, lately, distressingly downward. Part 2 extends the studies to leanness rankings by industrial sector; Lean's tendencies to focus inwardly on operations as opposed to external flows; how sales, general, and administrative (SG&A) costs are affected by Lean or its lack; and the value that the mergers-and-acquisitions community places on Lean successes.

In Part 2 of the leanness research, I use scored and graded long-term inventory data from Part 1 but sorted and combined with additional data in support of four special-topic studies. For each of the four, there appears to be a paucity of relevant academic research and hypotheses. Rather, the basis for the studies is more in the nature of reasonable assumptions, some of which have been advanced in connection with case studies or consultants' propositions. My intention is for the results to advance Lean theory and applied management decision making. This article discusses the four studies in the following order: long-term leanness trends by industrial sector; components of total inventory; effects on, or related to, SG&A costs; and how leanness is valued for companies that are delisted from stock exchanges.

LEANNESS BY SECTOR

At least annually for some 15 years, I have sorted the full set of leanness data not only by region but also by industry sectors, 32 of which generally include sufficient numbers of companies to be treated as a sector for study and ranking purposes. Early on, sector-based mean scores on long-term inventory trends were found to be highly divergent, suggesting that sectors with higher scores (Lean-exemplar sectors) have been competing, in part, on value-chain leanness, and those with lower scores have untapped opportunities to gain competitively by becoming lean. Table 1 is a ranking as of March 2016 of the 32 sectors, best to worst, along with sample sizes and mean scores.

Over the years, rankings have shifted a good deal for all but three of the industry sectors. It is no surprise that the Pharmaceuticals industry, which has long been known for having such high profit margins that companies have had low concern for costs, has been near the bottom in every iteration. Perhaps its ranking will rise in the future. The reason is that in various countries the toughened healthcare cost controls should elevate the emphasis on cost management, including through application of Lean methodologies. (1) Textiles has usually joined Pharmaceuticals near the bottom--its current rank is 29th--and it has never ranked above fifth lowest. Pump/hydraulic/pressure's high rank has been relatively stable, staying between third (its present rank) and 13th.

Of the other sectors, Chemicals, near the bottom in all the early years' rankings, began climbing the ladder in 2008 and now is above the median at 13th. Electronics, however, ranking near the top in some years, has plunged to 31st, which may be due in part to massive outsourcing of production, thus greatly lengthening Electronics's value chains. And Paper-converted products, ranked second in some of the early rankings, has tumbled to 11th.

Six of the sectors have particularly small sample sizes and thus are susceptible to large shifts in mean scores as the companies making up the sectors change: Furniture, Wire/Cable, Forest products, Paper, Personal-care products, and Vehicles (light, meaning vehicles other than Heavy Industrial). For example, Wire/Cable, now 24th and made up of just 34 companies, has ranked as high as third and as low as 30th.

The wide range of scores might be viewed as a trimodel distribution.

High. Scores for ranks 1 through 8 are from 0.56 to 0.41.

Middle. Scores for ranks 9 through 25 are from 0.38 through 0.20 and straddle the grand average of 0.30 for all 1,531 companies.

Low. Scores for ranks 26 through 32 are from 0.19 to 0.10.

The wide gulf between scores for high and low groups may point to practical advice. For a company in any of the eight high group sectors, the advice might be that its competitors show strength in leanness, which suggests close links along value chains to final customers. If it is weak in leanness and does nothing, it may be vulnerable to customer defections--even if its prices are lower and product quality higher. For the low group, the company's competitors tend to be weak on leanness. If it pushes its own Lean buttons hard, it may gain customers fed up with competitors' long lead times and related ills.

INVENTORY COMPONENTS: SHOWING MYOPIC, INWARDLY FOCUSED LEAN

The mean scores and rankings by region and sector indicate rather generally where things are going well and poorly in the Lean world. More specific awareness arises from a manufacturers-only study that breaks total inventory for each company into its components: purchased/raw material (RM), work-in-process (WIP), and finished goods (FG); or, in use at some companies, raw-and-in-process (RIP) or work-in-process and finished goods (WP/FG). This excludes retailers and distributors since they maintain just one unsubdivided inventory category. In this components phase of the research, figures of merit are in days of inventory, the reciprocal of inventory turnover.

The rationale for conducting this components research centers on the current high interest in supply chain management (SCM) issues. University business schools and their operations-management departments have been ramping up SCM programs, concentrations, and majors, many even changing their department name from operations management to supply chain management. In addition, the Decision Science Institute reported that of 30 tracks at its 2014 annual meeting, SCM garnered 117 paper submissions, nearly double the number for Healthcare, the next most popular. (2) Also, numerous published articles have been proclaiming bright careers in SCM, including three that begin with "The Rise of" and continue with words such as "the Supply Chain Executive" and one rating it "Top Job." (3) This growing attention suggests a general belief that SCM has suffered from neglect, which should be expected to show up tangibly in the form of growing RM and FG inventories.

Determining days of inventory involves enlarging the Excel database by adding year-by-year component inventory numbers found in manufacturers' annual reports. Currently, this components database includes 759 manufacturers: 550 U.S. and 209 non-U.S. companies. For each company I graphically plot calculated production days of inventory to permit visual scoring of trends--one file for U.S. and another for non-U.S. manufacturers. (Using production days avoids exogenous variables, such as pricing, that are likely to be active if sales days' inventory were used.)

While assembling the files was straightforward, interpreting the trends was not--because of connectivity among the four trend lines on each company's graph. I attempted different ways of assessing that connectivity--for example, comparing pairs of trend lines--but abandoned the efforts because of the inability to develop simple, usable scoring rules. In addition, trial efforts were not leading to useful findings. Finally, I reduced the assessment to tallying numbers of up (worsening) trends, down (improving) trends, and no clear trends (NCTs) separately for each of the four trend lines (RM, WIP, FG, and Total) per company.

[FIGURE 1 OMITTED]

Consider Coloplast A/S as an example (see Figure 1). Three of the four inventory elements--Total, FG, and WIP--were down (improving) trends; the fourth, RM, was no clear trend. The simple scoring rule involved is if a trend looks viable for as many as the past five years, tally it; otherwise, do not. As for RM at Coloplast, it was nearly flat in the most recent five years. In many other cases that rule is useless because plotted points are too erratic, so the scoring involves looking for what would be, if calculated, an up or down line of regression, then tallying it as up or down.

The visual tallying for the 759 manufacturers has resulted in the findings in Table 2. The large percentages under no clear trend stand out. If Lean were performing well among these manufacturers, one would expect lower incidence of NCT and higher incidence of

Figure 1: Coloplast A/S--Downward Trend for Total, Finished, and Work-in-Process Inventory and No Clear Trend for Purchased Materials improving trends for all four inventory elements. Instead, the improving trend percentages are in the teens for each of the three component inventory elements. Moreover, for total inventory, a substantially larger percentage is trending upward (worsening, 31%) than downward (improving, 20%). All this further indicates that Lean has been performing poorly.

Poor Lean efforts show up especially in FG and RM percentages--that is, in distribution and supply: for FG, the 28% of worsening trends is considerably larger than the 17% of improving ones. For RM, the difference is similar at 24% and 16%. Improvement shows up only in the WIP percentages--that is, in internal manufacturing-related processes--and then only weakly--improving trends at 17% and worsening trends at 16%.

For these components studies, maintaining graphs of company data in a U.S. file and a separate non-U.S. file permits comparisons. The bottom row in Table 2 indicates a notable finding: 209 non-U.S. companies are grading significantly better on Lean in operations as measured by WIP than the 550 U.S. companies--an improving WIP trend of 25% vs. a worsening trend of 17%. No such U.S./non-U.S. differences showed up for Total, FG, and RM, so they do not appear in the table.

At this point, since it relates to supply chain management obstacles, there is reason to comment on one other source of hard-data inventory studies: CFO magazine's annual Working Capital Scoreboard. It lists and ranks six companies in 20 different industry sectors by days' inventory outstanding (DIO), days' sales outstanding (DSO), days' payables outstanding (DPO), and their sum, days' working capital (DWC). If CFO's DIO data, which uses sales rather than cost of sales, were extracted and graphed for the past 10 years, the resulting trends should be expected to look rather similar to the long-term trends in the leanness studies. The CFO scoreboard, however, includes only 120 companies, all U.S. based.

Moreover, a presumption underlying the CFO scoreboard is that low numbers for all three components of working capital are worthy of higher regard. That presumption--a common mind-set in CFO circles--is, in some respects, contrary to a central aim of Lean. CFO printed the following explanation regarding DSO and DPO: "... forcing customers to pay quicker and slowing payments to suppliers.to some extent pits the CFO against the supply chain management and 'partners-in-profit' elements in the company." Further, "Instead of seriously undertaking supply chain collaborations--joint value-chain efforts--it's easier simply to use guile and clout to get inventory off your balance sheet and onto that of suppliers and distributors/retailers. which does wonders for one's DIO and balance sheet, but to the overall detriment of the company and its external suppliers." (4) As the leanness data shows, such working-capital-management tendencies may be contributing to worsening overall inventory trends and, especially, growth of supply and distribution inventories.

REDUCED SG&A COSTS:

UNSUNG LEAN BENEFITS

Still another special study, begun in 2011, pertains to Lean's underappreciated but likely seeming beneficial effects on sales, general, and administrative costs. (5) The customer-side benefits of effective Lean should generate reduced or slower-growing SG&A costs. That is, Lean's high-priority pursuit--of quicker, more flexible, higher-quality response to customer demand--should contribute to higher sales and customer retention and thus may be accompanied by reduced expenditures by sales and marketing in order to meet sales objectives. Conversely, when Lean is flagging--evidence being worsening inventory trends--SG&A costs should rise because sales should exert extra efforts and costs to deal with growing inventories poorly tuned to the market.

Lean also should reduce certain administrative costs. For example, some Lean-oriented companies turn away from facets of IT planning and control. (6) They see fit to do so as their operations become product-family or customer-family focused (the value-stream concept), which does the following:

* Simplifies planning, scheduling, and costing;

* Enables visual (no-transactions) flow methods attained, for example, through cellular organization, kanban, and continuous replenishment; and

* Facilitates measuring performance in natural units (e.g., flow time, flow distance, inventory) rather than monetized (accounting system) indicators. (7)

In this SG&A study, covering 91 companies mainly from the United States, production days of SG&A are calculated using cost of sales (COS): Production days' SG&A = Annual SG&A x 365/Annual COS. The 151 companies in this assessment are manufacturers; a similar study of retailers and distributors is an upcoming project. The purpose is to reveal whether the fruits of Lean or the penalty of its lack are reflected in SG&A.

To obtain SG&A numbers, data collection entailed returning to annual reports. Using COS and inventory data in existing Excel data records, I calculated days of SG&A for each company and loaded those numbers into a separate graphical file of days' SG&A and days' inventory. Finally, I assessed the resulting graphs for clear trends via visual tallying rules similar to those in the components studies. For the sake of reliable trend analysis, all 151 companies had to be represented by at least 10 years of data. Scoring results appear in Table 3.

[FIGURE 2 OMITTED]

It is important to note that since the financial community is more prone to express certain ratios in terms of sales rather than cost of sales, days' SG&A was calculated for most of the companies using sales days (SG&A x 365/Sales Revenue) and COS days. Sales days of SG&A are omitted from further discussion because including them would be redundant: For the large majority of the 91 companies, production days' and sales days' SG&A moved up and down in rather close symmetry.

The primary findings are twofold. First, the negative contention, which is a worsening trend in days' inventory and will show up as increased SG&A costs, is not supported: A worsening (upward) trend in days' inventory was found for 48 of the 151 companies. Second, I found 16 of the 48 with uptrends in SG&A costs vs. 21 with downward and 11 others with no clear trend in SG&A. Examples of each finding appear in Figures 2 and 3.

One of the 16 companies bearing out a link between worsening inventory and higher SG&A is American Science & Engineering (scanning, screening, and inspection products). Figure 2 illustrates that as the company's production days of inventory rose erratically, production days of SG&A rose, too, though with less erraticism. Among the 21 companies with contrary tendencies is Lennox International (air conditioning/heating appliances). As shown in Figure 3, as inventory grew at Lennox, SG&A activities and their costs decreased sharply.

[FIGURE 3 OMITTED]

Other companies that stand out for contrary SG&A tendencies include Baker Hughes, Eastman Kodak, Graftech International, Hutchinson Technology, and Molex--all with SG&A efforts flagging even as inventory trends are solidly up (worsening). Also contrary, but in the opposite direction, are ATMI, Inc.; Belden Inc.; Conmed; Ingersoll Rand; Parker Hannifin; Roper Industries; and Novozymes Group (Denmark). These companies experienced upward SG&A trends even as inventory trends were plunging. That Parker Hannifin is included in this group was a surprise because Parker has been among industry leaders in adopting Lean accounting practices.

As for the second contention--that downward-trending inventories should be accompanied by lower SG&A costs--it, too, is not supported: Of the 91 companies, 35 showed improving (downward) trends in days' inventory. Of that total, slightly more companies (16) showed contrary (upward) tendencies than those (14) that showed alignment with improving inventory trends.

In summary, the manufacturers studied are tending to respond to un-Lean conditions--excess inventories--by, contrary to reason, spending less on SG&A: less selling, advertising, demand data analysis (Big Data), and so on. Similarly, by a small margin, they tend to respond to good Lean trends--reduced inventories--by staying the course: keep spending as usual, which perhaps is to be expected since it is in the nature of organizational entities to resist budgetary cutbacks.

DELISTED COMPANIES: A LEAN HAVEN?

A final special study examines the long-term inventory performance of companies that I removed from the active database because they were delisted from the stock exchanges. These companies and their inventory-turnover data, graphs, scores, and grades remain in a separate delisted Excel file. (For this assessment, I used only companies that were delisted more recently than 2005 to more closely match the time period used in computing inventory-turnover scores for companies in the still-active database.) I compared scores for the delisted companies with scores for those that are still active, with this purpose in mind: When publicly traded companies go belly-up or are delisted for having been privatized, acquired, merged, divested, or spun off, a typical reason would seem to be that they had been subpar performers. (8) To test that, I compared delisted and active companies by long-term inventory reduction, a catchall kind of excellence indicator. No comparisons were done for Japan, Asiana/Africa, and non-U.S. Americas because of minimal numbers of delisted companies in those regions.

I did not expect the result. Overall, delisted companies show up as stronger performers in leanness trends than ones still listed. The exception is continental European companies, where mean leanness scores for the total group of 130 are almost the same (0.79) as the scores for the 49 delisted ones (0.77). The mean leanness score, however, for the 876 U.S. companies in the active database is 0.30, and for 129 delisted companies it is notably greater at 0.57. For the U.K., the difference is more extreme: a weak average of 0.28 for 58 active companies vs. a strong 0.78 for 60 delisted companies. One explanation might be that many delistings were done out of strength, resulting in financially lucrative privatization or absorbed through acquisition or merger with a company that places high value on leanness, revealed by due diligence of cash flow and inventory data in candidate companies' financial statements. The same phenomenon would apply as well to the U.S. delisteds but to a lesser extent.

IMPLICATIONS OF THE STUDY

In concluding this two-part leanness-studies report, it is fitting to briefly affirm the competitive importance of Lean and of inventory as a basis for assessing Lean's effectiveness. Lean's primary performance metric, associated with its customer-focused objective of flexibly quick response, must be lead time--how long an entity along the value chain waits to receive goods or services. Synonyms include queue time, wait time, flow time, and throughput time.

Lead time, however, is not a standardized, readily available metric. On the other hand, inventory is standardized and eminently researchable, at least for publicly traded, inventory-intensive companies for which inventory serves well as a close surrogate for lead time. Moreover, for those companies, keeping inventory records is a legal requirement, which has made it possible to conduct this leanness research.

This research is unique in that it tracks Lean performance via the inventory surrogate over many years' time spans, is global in scope, and includes large numbers of companies studied. Although articles and blogs by the dozens, easily found through search engines, have asserted that Lean is floundering or has a high failure rate, it appears that few, or none, have backed up the assertions with hard data of a longitudinal and global nature.

Others may see fit to probe the same or related issues in Lean effectiveness using the leanness data and findings from this two-part article as a catalyst. The research, using inventory as a telling indicator, could lead to more stability in the quest for continuous improvement in the eyes of the customer.

It is important to understand that in the services sector, in which Lean has established a strong presence, the inventory surrogate is not a viable, researchable measure. On the other hand, where real customers may be at arm's length or only one remove from the server, lead time (wait time) serves well as the ultimate measure of Lean effectiveness. Despite the lack of standard metrics for tracking (or researching) service-sector wait times (when customers wait, their displeasure is palpable), this is an advantage in a Lean-services context that is not available in manufacturing. Perhaps because of that advantage, the long-run prospects for Lean in services may not turn out to be one of worsening performance, which, as these leanness studies show, is the current trend for companies that deal in tangible goods.

Richard J. Schonberger, Ph.D., is an independent researcher, author, and presenter based in Bellevue, Wash. He is a member of IMAs Greater Seattle Area Chapter. You can reach Richard at (425) 467-1143 or saincl 7@centurylink.net.

ENDNOTES

(1) Robert E. Spector, "The Impact of Inventory Turns on Speed, Quality, and Costs," Pharmaceutical Manufacturing, June 17, 2009.

(2) Melissa Korn, "The Hot New M.B.A.: Supply-chain Management," The Wall Street Journal, June 5, 2013; "2014 DSI Annual Meeting Wrap-Up," Decision Line, January 2015, p. 16.

(3) Carlos Cordon, "The Rise of the Chief Supply Chain Officer," IMD International, April 2008, https://www.imd.org/research/ challenges/upload/TC037_The_rise_of_the_chief_supply_chain _officer.pdf; Stewart Lumsden and David MacEachern, "The Rise of the Chief Procurement Officer" (Career ladder column), Supply Chain Quarterly, Quarter 1, 2010; Merrill Douglas, "The Rise of the Supply Chain Executive," Inbound Logistics, October 2001, http://www.inboundlogistics.com/cms/article/the-rise-of-the-supply-chain-executive/; Abe Eshkenazi, "APICS Supply Chain Management Now: Supply Chain Manager Rated Top Job," APICS email message, February 20, 2015.

(4) Richard Schonberger, "Doing the Right Thing, Just in Time," CFO, December 15, 2012, p. 7.

(5) Lean Horizons Consulting, "The New Lean Vision: Creating and Sustaining Enterprise Lean," 2008, http://www.lean horizons.com/resources/LHC_Lean_Trends.pdf; Guidon Performance Solutions, "Using Lean Six Sigma for Fast Track SG&A Reductions; a Webinar," December 10, 2009, http://www.slideshare.net/guidon/using-lean-six-sigma-for-fast-track-sga-reductions-2691607.

(6) Doug Bartholomew, "Can Lean and ERP Work Together?" Industry Week, April 12, 2012.

(7) Robert W. Hall, "Lean on Steroids: Why We Should Rely on Physical Measures, not Financial Ones," www.lean.org/Lean Post/Posting.cmf?LeanPostid=265.

(8) Cory Janssen, "The Dirt on Delisted Stocks," 2002, http:// www.investopedia.com/articles/02/032002.asp; Jonathan R. Macey, Maureen O'Hara, David Pompilio, "Down and Out in the Stock Market: the Law and Economics of the Delisting Process," Yale Law School Legal Scholarship Repository, Faculty Scholarship Series (Yale Law School), January 1, 2008, http:// digitalcommons.law.yale.edu/cgi/viewcontent.cgi?article=4860& context=fss_papers.

Caption: FIGURE 1: Coloplast A/S-Downward Trend for Total, Finished, and Work-in-Process Inventory and No Clear Trend for Purchased Materials

Caption: FIGURE 2: Inventory and SG&A at AS&E

Caption: FIGURE 3: Inventory and SG&A at Lennox International Example of a company that, contrary to logic, reduced its SG&A efforts even as inventories grew
TABLE 1: Sector Rankings on Long-term Inventory Turnover *

Rank   Sector                         Sample Size   Mean Score

1      Telecom                            62           0.56
2      Electric                           115          0.50
3      Pump/hydraulic/pressure            90           0.49
4      Sheet metal                        73           0.45
5      Meta lworking/machining            335          0.44
6      Machinery                          173          0.43
7      Semiconductors                     77           0.41
8      Medical devices/supplies           79           0.41
9      Petroleum                          55           0.38
10     Instruments/test equipment         71           0.38
11     Paper-converted products           47           0.37
12     Personal-care products             36           0.36
13     Chemicals                          136          0.35
14     Forest products                    34           0.34
15     Apparel/sewn products              45           0.34
16     Liquid/gas/powder/grains           396          0.30
17     Paper                              31           0.27
18     Motors and engines                 64           0.27
19     Heavy industrial vehicles          58           0.27
20     Distribution/wholesale             91           0.26
21     Plastic/rubber/glass/ceramic       255          0.25
22     Retail                             173          0.24
23     Vehicular components               123          0.22
24     Wire/cable                         34           0.21
25     Food/beverage/tobacco              155          0.20
26     Basic metal processing             73           0.19
27     Vehicles (light)                   36           0.17
28     Aerospace-defense                  67           0.16
29     Textiles                           45           0.16
30     Pharmaceuticals                    90           0.14
31     Electronics                        362          0.13
32     Furniture                          26           0.10

* Data as of March 2016. Most companies are counted in two or more
sectors; for example, all 77 companies in Semiconductors are also
counted and scored in Electronics.

Table 2: Days' Inventory Trends for 759 Global Manufacturers *

                                    Long-term Trend

Days' Inventory            Up           Down       No clear
                       (Worsening)   (Improving)    trend

Total                      31%           20%         49%
FG                         28%           17%         55%
RM                         24%           16%         60%
WIP                        16%           17%         67%
WIP -U.S. (n=550)          15%           14%
WIP-Non-U.S. (n=209)       17%           25%

Table 3: Inventory (INV) and SG&A Trends for 151 * Companies

Inventory (INV) trends    Sales, General, and Administrative (SG&A)
                                        trends

Upward (worsening)        16    Upward (worsening) aligned with INV
INV trend, 48 companies         trend

                          21    Downward (improving) counter to INV
                                trend

                          11    Neither aligned with nor counter to
                                INV trend

                          48    Subtotal

Downward (improving)      16    Upward (worsening) counter to INV
INV trend, 35 companies         trend Downward (improving) aligned
                          14    with INV trend

                          5     Neither counter to nor aligned with
                                INV trend

                          35    Subtotal

No clear INV trend,       9     Upward (worsening) counter to flat or
68 companies                    downward INV trend Downward
                          8     (improving) counter to flat or upward
                                INV trend

                          51    Largely aligned with INV trend, or no
                                clear alignment

                          68    Subtotal

Total 151                 151   Total
COPYRIGHT 2016 Institute of Management Accountants
No portion of this article can be reproduced without the express written permission from the copyright holder.
Copyright 2016 Gale, Cengage Learning. All rights reserved.

Article Details
Printer friendly Cite/link Email Feedback
Author:Schonberger, Richard J.
Publication:Management Accounting Quarterly
Article Type:Report
Geographic Code:1USA
Date:Sep 22, 2016
Words:4233
Previous Article:Integrating practice into accounting education.
Next Article:Estimating retail breakeven using markup pricing.
Topics:

Terms of use | Privacy policy | Copyright © 2021 Farlex, Inc. | Feedback | For webmasters |