WHY DO MANAGEMENT PRACTICES DIFFER ACROSS FIRMS AND COUNTRIES? Nick Bloom (Stanford University & SIEPR) Blackrock, March 16 th 2010

MOTIVATION Large persistent productivity spread across firms and countries Britain less productive than the US since about 1900 Firms at 90 th percentile of productivity distribution about twice as productive at those as the 10 th percentile Could this be in part because of differences in management? Summarize a ten-year LSE, Harvard, Stanford and McKinsey project to measure management across firms and countries 2

1.“Measuring” management practices 2.Evaluating the reliability of this measure 3.Describing management across firms & countries 4.Accounting for management across firms & countries 5.Different sectors and evidence of causal impact OUTLINE 3

1) Developing management questions Scorecard for 18 monitoring, targets and incentives practices ≈45 minute phone interview of manufacturing plant managers 2) Obtaining unbiased comparable responses (“Double-blind”) Interviewers do not know the company’s performance Managers are not informed (in advance) they are scored 3) Getting firms to participate in the interview Introduced as “Lean-manufacturing” interview, no financials Official Endorsement: Bundesbank, PBC, CII & RBI, etc. Run by 75 MBAs types (loud, assertive & business experience) THE SURVEY METHODOLOGY 4

Score(1): Measures tracked do not indicate directly if overall business objectives are being met. Tracking is an ad-hoc process (certain processes aren’t tracked at all) (3): Most key performance indicators are tracked formally. Tracking is overseen by senior management. (5): Performance is continuously tracked and communicated, both formally and informally, to all staff using a range of visual management tools. (4) Performance tracking 5

Score(1): Top management's main focus is on short term targets. (3): There are short and long-term goals for all levels of the organization. As they are set independently, they are not necessarily linked to each other (5): Long term goals are translated into specific short term targets so that short term targets become a "staircase" to reach long term goals (10) Target time horizon 6

Score(1): Goals are either too easy or impossible to achieve; managers provide low estimates to ensure easy goals (3): In most areas, top management pushes for aggressive goals based on solid economic rationale. There are a few "sacred cows" that are not held to the same rigorous standard (5): Goals are genuinely demanding for all divisions. They are grounded in solid, solid economic rationale (11) Targets are stretching 7

Score(1): Poor performers are rarely removed from their positions (3): Suspected poor performers stay in a position for a few years before action is taken (5): We move poor performers out of the company or to less critical roles as soon as a weakness is identified (15) Removing poor performers 8

Score(1): People are promoted primarily upon the basis of tenure (3): People are promoted upon the basis of performance (5): We actively identify, develop and promote our top performers (16) Promoting high performers 9

MANUFACTURING SURVEY SAMPLE Interviewed 7000 firms across Asia, Europe and the Americas Obtained 45% coverage rate from sampling frame (with response rates uncorrelated with performance measures) Medium sized manufacturing firms: Medium sized ( ,000 employees, median ≈ 250) because firm practices more homogeneous Focus on manufacturing as easier to measure productivity (but show results for Schools, Hospitals and Retail) 10

1.“Measuring” management practices 2.Evaluating the reliability of this measure a) Internal/External validation b) Measurement error/bias 3.Describing management across firms & countries 4.Accounting for management across firms & countries 5.Different sectors and evidence of causal impact OUTLINE 11

INTERVAL VALIDATION: RE-SURVEY ANALYSIS 1 st interview 2 nd interview Re-interviewed 222 firms with different interviewers & managers Firm average scores (over 18 question) Firm-level correlation of

EXTERNAL VALIDATION OF THE SCORING Performance measure ln(capital) ln(materials) management (average z-scores) ln(labor) other controls Use most recent cross-section of data (typically 2006) country c Note – not a causal estimation, only an association 13

Dependent variable Productivity (% increase) Profits (ROCE) 5yr Sales growth Share Price (Tobin Q) Exit EstimationOLS Probit Firm sampleAll QuotedAll Management28.7*** 2.018*** 0.047*** 0.250***-0.262** Firms EXTERNAL VALIDATION: BETTER PERFORMANCE IS CORRELATED WITH BETTER MANAGEMENT Includes controls for country, with results robust to controls for industry, year, firm-size, firm-age, skills etc. Significance levels: *** 1%, ** 5%, * 10%. Sample of all firms where accounting data is available Standard errors clustered by firm 14

EXTERNAL VALIDATION: FUTURE STOCK RETURNS Most intriguingly, for an earlier (summer 2004) survey cohort of publicly quoted US firms we find correlated future (2005) stock holding returns Stock holding returns over 2005 (%) Management score (to nearest 0.5) assessed in summer 2004 Significant at 1% level # of firms 15

EXTERNAL VALIDATION – ROBUSTNESS Performance results robust in all main regions: Anglo-Saxon (US, UK, Ireland and Canada) Northern Europe (France, Germany, Sweden & Poland) Southern Europe (Portugal, Greece and Italy) East Asia (China and Japan) South America (Brazil) 16

EXTERNAL VALIDATION: WELL MANAGED FIRMS ALSO APPEAR TO BE MORE ENERGY EFFICIENT Energy use, log( KWH/$ sales) Management 1 point higher management score associated with about 20% less energy use 17 Source: Bloom, Genakos, martin and Sadun, NBER WP Analysis uses Census of production data for UK firms

1.“Measuring” management practices 2.Evaluating the reliability of this measure 3.Describing management across firms & countries 4.Accounting for management across firms & countries 5.Different sectors and evidence of causal impact OUTLINE 18

US MANAGEMENT BEST ON AVERAGE WITH A TAIL OF DEVELOPING COUNTRIES Average Country Management Score 19

US SCORES HIGHLY BECAUSE OF FEW BAD FIRMS Firm-Level Management Scores 20

COUNTRY LEVEL RELATIVE MANAGEMENT Relatively better at ‘operations’ management (monitoring, continuous improvement, Lean etc) Relatively better at ‘people’ management (hiring, firing, pay, promotions etc) People management (hiring, firing, pay & promotions) – operations (monitoring, continuous improvement and Lean) 21

1.“Measuring” management practices 2.Evaluating the reliability of this measure 3.Describing management across firms & countries 4.Accounting for management across firms & countries Competition Family firms Multinationals Labor market regulations Education 5.Different sectors and evidence of causal impact OUTLINE 22

TOUGH COMPETITION LINKED TO MUCH BETTER MANAGEMENT PRACTICES Various ways to measure competitive intensity (long-run market profits, trade-openess, market concentration, surveys etc.) In every case more competition leads to better management 23

OWNERSHIP MATTERS – FIRMS WITH PROFESSIONAL CEOS ARE WAY BETTER RUN THAN FAMILY, FOUNDER OR GOVERNMENT FIRMS Distribution of firm management scores by ownership. Overlaid dashed line is approximate density for dispersed shareholders, the most common US and Canadian ownership type Average Management Score 24

MULTINATIONALS APPEAR ABLE TO TRANSPORT GOOD MANAGEMENT AROUND THE WORLD Average Management Score Foreign multinationals Domestic firms 25

LIGHT LABOR REGULATION ALSO FACILITIATES GOOD MANAGEMENT (PITY THE FRENCH) World Bank Employment Rigidity Index Average people management (hiring, firing, pay and promotions) 26

EDUCATION IS ALSO STRONGLY LINKED WITH BETTER MANAGEMENT PRACTICES Management score (rounded to nearest 0.5) Percent with a degree Non-managers Managers 27

1.“Measuring” management practices 2.Evaluating the reliability of this measure 3.Describing management across firms & countries 4.Accounting for management across firms & countries 5.Different sectors and evidence of causal impact OUTLINE 28

ALSO RAN A SMALLER RETAIL MANAGEMENT SURVEY (USING AN ALMOST IDENTICAL GRID) WITH BROADLY SIMILAR RESULTS United States Canada United Kingdom Overall management scores Retail Found a strong correlation between management and profits and productivity in retail 29

RECENTLY ALSO BEEN RUNNING A HOSPITAL MANAGEMENT SURVEY Management practice scores Hospitals Again, found a strong correlation between management and performance (e.g. patient survival after heart-attacks) 30

MAJOR REASON FOR HIGH US SCORES ARE PRIVATE HOSPITALS ARE MUCH BETTER RUN Public Private Average management score Hospitals (US data) 31

Schools ALSO RUNNING A SCHOOLS MANAGEMENT SURVEY, IN WHICH US MANAGEMENT SCORES ARE POOR (THINK RUBBER ROOM & UNIONS) Again, found a strong correlation between management and performance (e.g. pupil exam grades) Average management score 32

FINALLY, IN SEARCH OF CAUSATION WE ARE RUNNING MANAGEMENT EXPERIMENTS IN INDIA To investigate the causal impact of management I am working with the World Bank to run experiments in large Indian firms Find large performance impact from improving basic management for operations, quality, inventory and HR Outside a typical Indian factory in our experimentsInside a typical Indian factory in our experiments 33

Many parts of these Indian plants – as in most developing countries - were dirty and unsafe Garbage outside the plantGarbage inside a plant Chemicals without any coveringFlammable garbage in a plant 34

The plant floors were also disorganized – the land that Lean forgot Instrument not removed after use, blocking hallway. Tools left on the floor after use Dirty and poorly maintained machines Old warp beam, chairs and a desk obstructing the plant floor 35

Yarn piled up so high and deep that access to back sacks is almost impossible The inventory rooms had months of excess yarn, often without any formal storage system or protection from damp or crushing Different types and colors of yarn lying mixed Yarn without labeling, order or damp protection A crushed yarn cone, which is unusable as it leads to irregular yarn tension 36

Not surprisingly, modern management practices led to large performance improvements – e.g. defects down by 50% 2.5 th percentile Control plants Treatment plants Weeks after the start of the intervention Quality defects index (higher score=lower quality) Start of Diagnostic Start of Implementation Average (+ symbol) 97.5 th percentile Average (♦ symbol) 2.5 th percentile 97.5 th percentile End of Implementation Notes: Average quality defects index, which is a weighted index of quality defects, so a higher score means lower quality. Plotted for the 14 treatment plants (+ symbols) and the 6 control plants (♦ symbols). Values normalized so both series have an average of 100 prior to the start of the intervention. Confidence intervals from plant block bootstrapped. 37

SUMMARY 1.Variations in management practices (for monitoring, targets and incentives) account for large differences in performance 2.Huge differences in these management practices across organizations in every sector and country we have looked at 3.Competition, ownership, regulations and education seem key factors in explaining these differences Quotes: 38

MY FAVOURITE QUOTES: [Male manager speaking to an Australian female interviewer] Production Manager: “Your accent is really cute and I love the way you talk. Do you fancy meeting up near the factory?” Interviewer “Sorry, but I’m washing my hair every night for the next month….” The traditional British Chat-Up 39

Production Manager: “Are you a Brahmin?’ Interviewer “Yes, why do you ask?” Production manager “And are you married?” Interviewer “No?” Production manager “Excellent, excellent, my son is looking for a bride and I think you could be perfect. I must contact your parents to discuss this” The traditional Indian Chat-Up MY FAVOURITE QUOTES: 40

Interviewer: “How many production sites do you have abroad? Manager in Indiana, US: “Well…we have one in Texas…” Americans on geography Production Manager: “We’re owned by the Mafia” Interviewer: “I think that’s the “Other” category……..although I guess I could put you down as an “Italian multinational” ?” The difficulties of defining ownership in Europe MY FAVOURITE QUOTES: 41

Don’t get sick in Britain Interviewer : “Do staff sometimes end up doing the wrong sort of work for their skills? NHS Manager: “You mean like doctors doing nurses jobs, and nurses doing porter jobs? Yeah, all the time. Last week, we had to get the healthier patients to push around the beds for the sicker patients” MY FAVOURITE QUOTES: 42

The bizarre Interviewer: “[long silence]……hello, hello….are you still there….hello” Production Manager: “…….I’m sorry, I just got distracted by a submarine surfacing in front of my window” The unbelievable [Male manager speaking to a female interviewer] Production Manager: “I would like you to call me “Daddy” when we talk” [End of interview…] MY FAVOURITE QUOTES: 43

BACK-UP 44

WE USE LARGE SAMPLES BECAUSE THE WIDE VARIATION IN MANAGEMENT MEANS SMALL SAMPLES CAN BE POTENTIALLY MISLEADING Case studies provide rich firm- level details, but the variation in management practices means these can easily be misleading (e.g. Enron, was a case-study favorite with many HBS Enron cases) Management score Log of Sales/employee ($’000) 45

WE ALSO GOT MANAGERS TO SELFSCORE THEMSELVES AT THE END OF THE INTERVIEW We asked: “Excluding yourself, how well managed would you say your firm is on a scale of 1 to 10, where 1 is worst practice, 5 is average and 10 is best practice” We also asked them to give themselves scores on operations and people management separately 46

MANAGERS GENERALLY OVER-SCORED THEIR FIRM’S MANAGEMENT “Average”“Worst Practice” “Best Practice” 47

SELF-SCORES ARE ALSO UNINFORMATIVE ABOUT FIRM PERFORMANCE Labor Productivity Self scored management * In comparison the management score has a correlation with labor productivity Correlation 0.032* 48