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    CALIFO RNIA M ANAG EMENT REVIEW VOL.43,N O .4 SUMM ER 200164

    Work reported here wassupported by the MIT Center for Innovation in Product D evelopment under

    N SF Cooperative Agreement N umber EEC-9529140. For more information on the research program

    that generated thisarticle, visit < http://web.mit.edu/nelsonr/www/>.

    Nobody Ever Gets Credit

    for Fixing Problems thatNever Happened:C REAT IN G A N D SU ST A I N IN G PRO C ESS

    IM PRO V EM EN T

    Nelson P. Repenning

    J ohn D. Sterman

    How much w ould your organization pay to develop manufacturing

    capability eq ual to Toyota s? How mu ch w ould a w orld-class, six-

    sigma qu ality program be w orth to your company? How about

    Harley-Davidsons ability to tap into th e hearts an d min ds of its cus-

    tomers or Dells ability to man age its supply cha in? Most fi rms are w orking

    aggressively to develop these and similar capabilities through process improve-

    ment . The combined expenditure of U.S. compan ies on m an agement con sul-

    tan ts and train ing in 1997 w as over $100 billion, and a sizeable fraction w ent

    tow ards efforts to develop operational capabilities ma tching tho se of the best

    fi rms in business. Whether its an a dvan ced man ufacturing system or the ability

    to respond q uickly to chan ging customer needs, the drive tow ard improvemen t

    ha s become a w ay of life in corporations toda y. There is only on e problem.

    Despite these vast expenditures, and n otw ithstandin g drama tic successes in a

    few compan ies, few efforts to implement such programs actually produce signifi -

    cant results.

    Con sider, for exa mple, Tota l Quality M an agem ent (TQM). In t he 1980s,

    spurred by the success of many Ja panese fi rms, TQM w as all the rage amon g

    U.S. fi rms. Consultan ts and business school faculty preached its virtues an d

    man agers made pilgrimages to companies with a w ard-w inning qua lity pro-

    grams. B y th e mid-1990s, how ever, TQM w as considered pass. Academics hadmov ed on to oth er issues, TQM received rare men tion in the popular bu siness

    press, and articles that did men tion it usua lly did so in a n egative context. TQM

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    had all the earmarks of a management fad: An initial burst of enthusiasm, a

    fl urry of activity, and then a steady decline as it w as replaced by n ew er innova-

    tions such as re-engineering. It w ould be easy to conclude tha t TQMs underly-

    ing value wa s minimal.How ever, w hen one looks at the experience a little more carefully, a dif-

    ferent picture emerges. A number of careful studies have now demon strated that

    compan ies ma king a serious comm itment to the disciplines and meth ods associ-

    ated w ith TQM ou tperform their competitors.1 There is now little doubt tha t

    w hen u sed properly, TQM produces signifi cant v alue to both organizations an d

    their customers. Yet para doxically, it rem ains little used. A recent study found

    that few er than 10% of the Fortune 1000ha d w ell-developed TQM program s;

    an d, in a noth er study, TQM fell from th e third most comm only u sed business

    tool in 1993 to 14 th in 1999.2 The situation is similar for a w ide range of oth er

    administrative and technological innovations.3 Techn iqu es touted a s today s

    core competencies all too often become tom orrow s failed programs. Once

    an effort has failed, th ere is an almost irresistible temptation to label it a fad or

    fl avor of the mon th. How ever, digging a little deeper shows that man y such

    techniques have useful content. It should come as little surprise then that many

    currently popular innova tions are little more than old ideas w ith new acronyms.

    The core disciplines associated w ith stat istical process cont rol an d varia nce

    reduction become six-sigma; w hat w as once called a q uality circle is now a

    high-performan ce w ork team.

    Thus, toda ys ma na gers face a paradox. On th e one han d, the nu mber of

    tools and techn iques ava ilable to improve performance is grow ing rapidly. Fur-

    ther, with ad van ces in information techn ology and th e ever-grow ing legions of

    management consultants, it is easier than ever to learn about these techniques

    an d to learn w ho else is using them. On the oth er hand , there has been littleimprovement in the ability of organizations to incorporate these innovations in

    th eir everyda y activ ities. The a bility to identifyand learn aboutnew improvement

    meth ods no longer presents a signifi cant ba rrier to most ma na gers. Instead, suc-

    cessfully implementingthese innova tions presents the biggest challenge. Pu t m ore

    simply, you can t buya tu rnkey six-sigma qu ality program. It m ust be developed

    from within.

    To learn how fi rms can overcome this improvement paradox, w e

    ha ve, over the past decade, studied process improvement an d learning programs,

    focusing on the dynamics of implementation and organizational change. We

    conducted o ver a dozen in -depth case studies in indu stries including telecom-

    mun ications, semiconductors, chemicals, oil, au tomobiles, and recreational

    products. 4 We gathered data through observations, extensive interview s with

    participants, a rchival records, an d q uan titative metrics. We complemented

    our fi eld research w ith the development of a series of models capturing the

    dynam ics of implementation and improvement.5 Using system dynamics as the

    basis for understanding implementation has yielded a number of insights into

    the improvemen t paradox . In a t least some cases, these insights have proven

    N obody Ever GetsC redit for Fixing Problemsthat N ever Happened

    C ALIFO RN IA MA N AG EM EN T REVIEW VO L. 43, N O . 4 SUM M ER 2001 65

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    instrumenta l in helping firm s benefi t from the potential provided by available

    improvement tools and techniques.

    Most important ly, our research suggests that th e inability of m ost organi-

    zations to reap the full benefi t of these innova tions has little to do w ith the spe-cific improvemen t tool they select. Instead, the problem ha s its roots in how

    the introduction of a new improvement program interacts with th e phy sical,

    economic, social, an d psychological structures in w hich implementa tion ta kes

    place. In oth er w ords, its not just a tool problem, any more tha n its a hu ma n

    resources problem or a leadership problem. Instead it is a systemic problem, o ne

    tha t is created by the interaction of tools, equipment, w orkers, and m an agers.

    The Structure of Improvement

    We present th e lessons that h ave em erged from our study in the form o f

    a causal loop diagram. Our m odel provides both a useful framew ork for thinkingabout th e challenges associated w ith implemen ting improvement programs and

    practical suggestions to increase the cha nces that your n ext such effort w ill suc-

    ceed. While the theory reported here initially emerged from the study of tw o

    improvement initiatives in a major automaker,6 the resulting model is quite gen-

    eral and can be applied to a range of situations. We have observed these dynam-

    ics in almost every organization w e have studied.

    Figure 1 begins w ith th e basic physics und erlying process improvement.

    The actua l performan ce of any process depends on tw o factors: the amo unt o f

    Time Spent Worki ngand the Capabilityof the process used to do tha t w ork. For

    example, in manufacturing, net usable output is given by the product of labor

    hou rs per day a nd productivity (usable units per labor h our).

    The performan ce of an y process can be increased by dedicating a dditional

    effort to either w ork or improvement. How ever, the tw o activities do not pro-

    duce eq uivalent results. Time spent on improving th e capability of a process

    typically yields the more enduring chan ge. For exam ple, boosting the w orkw eek

    20% might increase output 20%, but on ly for the du ration of th e overtime.

    Ga ins in process capability, how ever, boost the ou tput generated by every sub-

    sequent h our of effort. Similarly, overtime devoted t o rew orking defective prod-

    ucts can boost net usable output, but only as long as the overtime is continued,

    w hile eliminating th e root causes of those defects perman ently reduces the need

    for rew ork. We capture th is persistence by represent ing Capabilityas a stock

    (denoted by a rectangle), that is, as an asset that accumulates improvements

    over time. Specifi cally, Time Spent on Impr ovementincreases the flow of Investments

    in Capabili tytha t a ugmen ts process capability.

    While it often yields the m ore permanen t gain, tim e spent on improve-

    ment does not immediately improve performance. It takes time to uncover the

    root causes of process problems an d th en to discover, test, a nd im plemen t solu-

    tions, show n in the diagram as a delay between improvement activities and th e

    N obody Ever GetsC redit for Fixing Problemsthat N ever Happened

    CALIFO RNIA M ANAG EMENT REVIEW VOL.43,N O .4 SUMM ER 200166

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    resulting cha nge in process capability. Mo reover, n o improvem ent in capa bilitylasts forever. Ma chines w ear, processes go out of con trol w ithout regular atten-

    tion, d esigns become obsolete, and procedures become outd ated. Thus, w e also

    show an outfl ow from the stock capturing the inevitable decline of a ny capabil-

    ity tha t is not regularly main tained. The lag in enh an cing capability depends on

    the technical an d organization al complexity of th e process. Studies show tha t

    the d elay in improving relatively simple processes such as th e yield of m achines

    in a job shop is on th e order of a few mon ths, w hile the delay in improving

    highly com plex processes such as product development can be several years or

    more.7 Similarly, the lifetime of improvem ents in capa bility w ill be shorter in

    organizations w ith high rates of change in products and people.

    Besides the physical an d institutional structures that determine perfor-

    ma nce, Figure 1 also show s the goal for process through put set by senior man-

    agers (labeled Desired Performance). The goa l could be the n um ber of products

    dema nded by custom ers each da y, the rate at w hich claims need to be processed

    by an insura nce company, or the num ber of new products the fi rm seeks to

    launch this quarter. People compare that goal to their actual performance to

    determine the Performance Gap. Not surprisingly, in th e organ izations w e studied

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    C ALIFO RN IA MA N AG EM EN T REVIEW VO L. 43, N O . 4 SUM M ER 2001 67

    FIGURE 1. The Physics of Improvement

    N ote:A rrowsindicate the direction of causality. Signs( + or ) at arrowheadsindicate the polarityof relationships: a + means

    that an increase in the independent variable causesthe dependent variable to increase, all else being equal (a decrease causesa

    decrease); similarly, a indicatesthat an increase in the independent variable causesthe dependent variable to decrease (a

    decrease causesan increase) . For more details,see J. Sterman,Business Dynamics:Systems Thinking and Modeling for a Complex World

    (N ew York,N Y: Irwin/McGraw-H ill, 2000).

    Investment inCapability

    Capability CapabilityErosion

    Time SpentWorking Actual

    Performance

    PerformanceGap

    DesiredPerformance

    Time Spent onImprovement

    DELAY+

    ++

    +

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    it w as rare to fi nd a process performing abo ve expectations. Instead, m ana gers,

    w orkers, an d engineers usually faced high an d rising deman ds, sometimes

    despite dow nsizing a nd cuts in resources. They w ere constantly searching for

    w ays to improve an d close the performance gap. Since most organizations arereluctant to increase plant and equipment or hire more staff, managers hoping

    to close a performance gap hav e only tw o basic options.

    First, they can try to increase the am oun t of time people actually spend

    w orking. Figure 2 show s this option, w hich forms a balancingfeedback, the Work

    Harderloop B1. The process represented by this loop w orks as follow s: Man agers

    facing a performa nce gap are u nder pressure to increase performan ce. They

    pressure people to spend mo re time and energy doing w ork. An increase in the

    time spent w orking increases the performan ce of th e process and closes the per-

    form an ce gap. This structure is called a bala ncing feedba ck loop becau se it con-

    stantly w orks to balan ce desired and a ctual performan ce.

    Pressure to do Workincludes, most obviously, direct mea sures such a s

    telling people to w ork faster or put in overtime, setting mo re aggressive targets

    for throu ghput, a nd im posing m ore severe penalties for missing th ose targets.

    Pressure a lso includes mo re subtle actions designed to extract greater effort from

    employees. These include th e frequency w ith w hich performance is review ed,

    the detail with w hich the review s are conducted, and the seniority of th ose

    doing the review ing. At one company w e studied, it w as not un usual for senior

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    CALIFO RNIA M ANAG EMENT REVIEW VOL.43,N O .4 SUMM ER 200168

    FIGURE 2. The Work HarderBalancing Loop

    N ote:T he loop identifier,B1, indicatesa negative (balancing) feedback. See J. Sterman, op.cit.

    Investment inCapability

    Capability CapabilityErosion

    Time SpentWorking Actual

    Performance

    PerformanceGap

    DesiredPerformance

    Time Spent onImprovement

    DELAY+

    +

    +

    +

    +

    +

    Pressure to

    Do Work

    B1

    Work Harder

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    vice-presidents to review t he performan ce of individual mach ines on the fa ctory

    fl oor. Not surprisingly, such attent ion sent a strong message to all involved: keep

    the ma chines busy at all costs. Similarly, a project mana ger we interview ed

    recalled tha t w hen a subsystem for w hich he w as responsible fell behind sched-ule, his boss required him to call in every hourw ith a statu s report until the pro-

    totype m et its specifi cations.

    A second option to close a performance gap is to improve th e capability o f

    the process. In Figure 3 w e represent this option as an other ba lancing feedback

    process, the Work Smarterloop B2. Here, mana gers respond to a performance

    shortfa ll by increa sing the pressure on people to improve capability. They m ay

    launch im provement programs, encourage people to experiment w ith new

    ideas, and in vest in training. If successful, these investments w ill, w ith time,

    yield improvements in process capability, boost th roughput, an d close the per-

    forman ce gap. Of course, everyon e know s that it is better to w ork sma rter than

    to w ork harder: An hour spent w orking produces an extra hours worth of out-put, w hile an hour spent on improvement may improve the productivity of

    every subsequent hou r dedicated to production. Yet, despite its obvious and

    documen ted benefi ts, wo rking smarter does have limitation s. First, as show n

    in the diagram , there is often a substan tial delay betw een investing in improve-

    ment a ctivities and reaping the benefi ts. Further, the greater the complexity of

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    C ALIFO RN IA MA N AG EM EN T REVIEW VO L. 43, N O . 4 SUM M ER 2001 69

    FIGURE 3. The Work SmarterBalancing Loop

    Investment inCapability

    Capability CapabilityErosion

    Time SpentWorking Actual

    Performance

    PerformanceGap

    DesiredPerformance

    Time Spent onImprovement

    +

    +

    +

    +

    +

    +

    +

    +

    Pressure to

    Do Work

    B1

    Work Harder

    B2

    Work Smarter

    Pressure toImprove

    Capability

    DELAY

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    the process, th e longer it takes to im prove.8 Second, investmen ts in capability

    can be risky. Improvemen t efforts dont a lw ays fi nd th e root cause of defects,

    new tools sometimes don t produce the desired gains, and experiment s often

    fail. While investmen ts in capability m ight eventu ally yield large and endu ringimprovements in productivity, they do little to solve the problems man agers face

    ri ght now.

    Thus, it is not surprising tha t m ana gers frequent ly use the Work Harder

    loop to both accomm odate va riations in da ily w orkload an d solve pressing prob-

    lems created by un expected breakdow ns or defects. When a ma nufa cturing line

    serving an important custom er goes dow n, a m ana ger is unlikely to react by

    sending the w ork team to training in reliability improvemen t. Instead, tha t

    manager is going to get the line running and push for overtime until the ship-

    ment is out the do or. Of course w hen th e line is back runn ing and th e product

    has been shipped, the manager should return attention to the improvement

    activities that w ill prevent future breakdow ns, and m ake up for the improve-

    ment tim e that w as lost during the crunch. How ever, it doesnt usually ha ppen.

    Instead, w hat w e repeatedly observe, and w hat is more diffi cult to understand,

    are organizations in w hich w orking ha rder is not merely a m eans to deal w ith

    isolated incidents, but is instead stan dard operating procedure. Rather th an

    using the w ork harder loop to occasionally offset daily variations in w orkload,

    ma na gers, supervisors, an d w orkers all come to rely constan tly on w orking

    ha rder to hit their targets and, consequen tly, never fi nd th e time to invest

    in improvement a ctivities. Wha t starts as a tempora ry empha sis on w orking

    ha rder quickly becomes routine.

    The Rei nvestment Loop

    To un derstand w hy, it is helpful to consider how w orking sma rter andw orking harder are conn ected. The m ost important int erconnection arises

    because organizations ra rely ha ve excess resources. Increasing th e pressure to

    do w ork leads people to spend less time on non -work related a ctivities like

    breaks and to put in overtime (that is, they use the Work Harderloop). For

    know ledge w orkers such overtime is often un paid and spills into n ights and

    w eekends, stealing time from family an d comm unity a ctivities. There are, how -

    ever, obvious limits to long ho urs. After a w hile there is simply no more time.

    If the performance gap continu es to rise, wo rkers have n o choice but to reduce

    the time th ey spend on improvem ent a s they strive to meet their ever-increasing

    objectives. Figure 4 adds th e connection betw een pressure to do w ork and the

    amoun t of time spent on improvement.

    The a ddition al link creates the Reinvestmentloop. Unlike those described

    so far, the Reinvestmentloop is a positive feedback that ten ds to reinforce w hich-

    ever behavior currently dom inates. An organization t hat successfully improves

    its process capab ility w ill experience rising performa nce. As the perform an ce

    gap falls, w orkers ha ve even mo re time to devote to improvement, creating a

    virtuous cycle of improved capability and increasing attention to improvement.

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    Conv ersely, if man agers respond to a th roughput ga p by increasing w ork pres-

    sure, employees increase the amo unt o f time spent w orking and cut th e time

    spent on improvement. Capability begins to decay. As capability erodes, the per-

    forman ce gap grow s still more, forcing a further shift tow ards w orking harder

    an d aw ay from im provement. Here the reinvestment loop operates as a vicious

    cycle, driving the organization to ever-higher degrees of wo rk pressure an d m in-

    imal levels of process capability. Not surprisingly, such a vicious cycle quickly

    drives out m eaningful improvemen t activity. Here, for exam ple, is the w ay a

    ma na ger in an electronics assembly plant explained the persistent failure of the

    organization to engage in process improvement:

    Su pervisors never ha d time to ma ke improvements or do preventative ma inte-

    nan ce on th eir lines . . . they h ad to spend a ll their time just trying to keep the

    line going, but this meant it w as alwa ys in a state of flux, w hich, in turn, causedthem to w ant to hold lots of protective invento ry, because everyth ing w as so

    unpredictable. A quality problem might n ot be discovered until w e ha d produced

    a pile of defective parts. This of course mean t w e didnt ha ve time to fi gure out

    w hy th e problem happened in the fi rst place, since we w ere now rea lly behind

    our production schedule. It wa s a kind of snow ball effect that just kept getting

    w orse.

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    FIGURE 4. The ReinvestmentReinforcing Loop

    Investment inCapability

    Capability CapabilityErosion

    Time SpentWorking Actual

    Performance

    PerformanceGap

    DesiredPerformance

    Time Spent onImprovement

    +

    +

    +

    +

    +

    +

    +

    +

    Pressure to

    Do Work

    B1

    Work Harder

    B2

    Work Smarter

    R1

    Reinvestment

    Pressure toImprove

    Capability

    DELAY

    N ote:T he loop identifier, R1, indicatesa positive ( reinforcing) feedback. See J. Sterman, op.cit.

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    Shor tcut s and th e Capabi li ty Trap

    The Reinvestmentloop means a temporary emphasis on one option at the

    expense of the oth er is likely to be reinforced and eventua lly become perma-

    nent. Organ izations that invest in improvement w ill experience increasing capa-bility and fi nd th at they have m ore time to a llocate to w orking smarter and less

    need for h eroic efforts to solve problems by w orking harder. In t he successful

    initiatives w e studied, leadership often w orked to strengthen th e reinvestmen t

    process by explicitly allocating the resources freed up by productivity gains to

    further improvement. Un fortuna tely, how ever, these initiatives were the excep-

    tion rather than the rule. In most of the organizations in our study the reinvest-

    ment loop w orked as a vicious cycle and prevented improvem ent programs from

    getting off the ground. Even w hen improvem ent programs yielded initial results,

    cost and schedule pressures soon tem pted man y organ izations into dow nsizing

    or higher performan ce goals that drained resources aw ay from im provement,

    w eakening the reinvestment loop an d causing capability to stall or even fall.9

    Understanding w hy the reinvestment loop typically w orked in the dow n-

    w ard, vicious direction rather than the upw ard, virtuous direction requ ires tha t

    w e add a fi na l link to th e model (see Figure 5). As discussed abov e, cutting

    investments in maintenan ce and improvement in favor of w orking ha rder

    erodes process capability an d h urts performa nce. How ever, capability does not

    drop right a w ay. It takes time for process integrity to depreciate. In th e mean -

    time, th e decision to skimp on improvementskipping improvem ent tea m

    meetings, neglecting to take ma chines dow n for scheduled ma intena nce, or

    ignoring documenta tion requirementsboosts the time ava ilable to get w ork

    done right now. We capture this interconnection by adding a negative link

    between Time Spent on Impr ovementand Time Spent Worki ng. When the perfor-

    ma nce gap rises and m an agers resort to increased w ork pressure, overw orkedpeople cut back improvemen t a ctivity to free still more time for production. The

    performa nce gap falls, closing a th ird feedback tha t w orks to balance desired and

    actua l performa nce. We label this the Shortcutsloop (B3) to capture the idea that

    increased throughput comes at the cost of departing from standard routines and

    processes, cutting corners, an d reducing the t ime spent o n learn ing an d

    improvement.

    Shortcuts are tempting because there is often a substantial delay betw een

    cutting corners and the consequ ent decline in capability. For example, supervi-

    sors w ho defer preventive mainten an ce often experience a grace period in

    w hich they reap the benefits of increased output (by a voiding scheduled dow n-

    time) and save on ma intena nce costs. Only later, as equ ipment ages an d w ears

    do th ey begin to experience lower y ields and low er uptimes (see section 4). Sim-

    ilarly, a softw are engineer wh o forgoes documen tation in fav or of completing a

    project on time incurs few immediate costs; only later, w hen she returns to fi x

    bugs discovered in testing does she feel the full impact of a decision m ade w eeks

    or m onth s earlier.10 Thu s, th e Shortcutsloop is effective in closing th e throu ghput

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    gap only because capability does not cha nge immediately w hen th e time dedi-

    cated to learning and improvement declines.

    To illustrate th ese dynam ics, Figure 6 show s tw o simulations of th e mod el

    in w hich w e show how a h ypothetical process reacts to w orking ha rder versus

    w orking sma rter. Bo th simulation s begin in th e same equ ilibrium state. The fi rst

    simu lation show s the response to an increased emphasis on w orking harder. As

    more effort is dedicated to w ork, gross throughput immediately rises. Time spent

    improving falls imm ediately, but capability d oes not. Performa nce therefore

    rises. The benefi t of w orking ha rder is, how ever, short-lived. With less time

    devoted to improvement, capability gradually erodes, eventually more than

    offsetting th e increased time spent w orking. Working harder creates a better-

    before-w orse situation. Conv ersely, as seen in th e second simu lation, increasing

    the time spent on improvement reduces output in the short run. Eventually,

    how ever, capability rises more than enough to offset the drop in w ork effortan d performa nce is permanen tly higher, a w orse-before-better dyn am ic.

    The interaction betw een the ba lancing Shortcutsloop and the reinforcing

    reinvestment loop creates a phenomen on w e call the Capabili ty Trapand helps

    explain w hy o rganizations often fi nd th emselves stuck in a vicious cycle of de-

    clining capability. Man agers and w orkers in need of an immediate performan ce

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    FIGURE 5. The ShortcutsBalancing Loop

    Investment inCapability

    Capability CapabilityErosion

    Time SpentWorking Actual

    Performance

    PerformanceGap

    DesiredPerformance

    Time Spent onImprovement

    +

    +

    +

    +

    +

    +

    +

    +

    Pressure to

    Do Work

    B1

    Work Harder

    B2

    Work Smarter

    R1

    Reinvestment

    B3

    Shortcuts

    Pressure toImprove

    Capability

    DELAY

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    boost can get it by skimping on improvemen t and m aintena nce. How ever, capa-

    bility even tually declines, causing th e Reinvestmentloop to w ork as a viciouscycle. Managers who rely on w orking harder and shortcuts to meet immediate

    through put needs soon fi nd t he process falling short of its objectives, requiring a

    further shift towa rds working harder an d aw ay from im provement. To see the

    capability trap in action, consider how a ma nufa cturing supervisor in an au to

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    FIGURE 6. Simulationsof the Working Harder and Working Smarter Strategies

    SYSTEM RESPONSE TO:

    Time Spent Improving

    Time Spent Working

    Time Spent Working

    Time Spent Improving

    Time Time

    Time Time

    Time Time

    WORKING HARDER WORKING SMARTER

    Actual Performance Actual Performance

    Effort Effort

    Capability Capability

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    company explained the inability of her organization to make a commitment to

    regular improvement activities:

    In the minds of the [operations team leaders] they h ad to h it their pack counts.

    This meant if you w ere having a bad da y an d you r yield had fallen . . . you h ad

    to run like crazy to h it your ta rget. You could say, you are ma king 20% garbage,

    stop the line and fi x the problem, an d they w ould say, I cant hit my pack count

    w ithout run ning like crazy. They could n ever get ahead of th e game.

    By keeping the line going rath er than stopping to fi x the problem, these team

    leaders relied on the Shortcutsloop to hit th eir throughput objectives. However,

    by running like crazy they also caused the Reinvestmentloop to operate as a

    vicious cycle, driving th e line to a minima l level of capability an d forcing them

    to run ever faster.

    The capability trap is not limited to m anu facturingwe ha ve observed

    it in fi rms ranging from fi na ncial services to construction. For example, the

    capability trap prevented a product development organ ization w e studied fromdeveloping new processes that w ould ha ve increased productivity. Like many

    fi rms, they sought to create an engineering library or bookshelf of reusable

    designs and softw are. How ever, as described by an engineering man ager,

    An engineer m ight not ta ke the time to d ocument her steps or put the results of

    a simulation on th e bookshelf and because of that she saved engineering time and

    did her project more effi ciently. But in the long run it prevented us from being

    able to deploy the reusability concepts that w e w ere looking for.

    Ju st as machine operators and supervisors in th e fi rst exam ple faced a basic

    trade-off between producing an d improving, development engineers were forced

    to trade off getting their assigned tasks done aga inst documenting w ha t they

    learned so tha t others might benefi t. Engineers could ma ke more rapid progresstow ards their objectives by ta king shortcuts and ignoring the boo kshelf, but

    doing so prevented th em from initiating the self-reinforcing reinvestment loop

    tha t w ould ha ve led to improved process capability.

    The Persistence of the Capability Trap

    Becau se w orking harder and taking shortcuts produce more immediate

    gains and h elp solve toda ys problems, ma na gers una w are of the inherent

    better before w orse trade-off are likely to choose them ov er w orking sma rter.

    Unfortunately, these temporary gains come at the expense of the long-run

    health of the process. By pressuring people to w ork harder, man agers often un-

    w ittingly force their organizations into th e capability trap w here ever-increasing

    levels of effort are requ ired to maint ain performan ce. Of course, this pheno me-

    non is not limited to large organization s. Many readers will recognize this

    dyn am ic in different a spects of their personal lives. In situation s ranging from

    learning how to use a n ew softw are package to committing to a n ew exercise

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    program, w e often fail to do the thin gs tha t w ill improve our long-run produc-

    tivity an d w ell-being due to the short-run stresses of other obligations.

    A question naturally arising at this point is: Wouldnt managers eventu-

    ally fi gure this out? While it is understanda ble that, on occasion, people getcaught in th e capability trap, w ouldnt th ey eventua lly realize the true source of

    their problems and rebalance their efforts betw een w orking harder and w orking

    smarter? Unfortunately, the data suggest that overcoming the capability trap is

    rare. Man agers often do not realize how deeply th ey are trapped in it. Instead,

    the lessons tha t people learn w hen cau ght in the capability trap often lead to

    actions that ma ke the situation w orse.

    Faulty Attr ibuti ons

    Suppose you a re a mana ger faced w ith inadeq uate performance. Your

    operation is not meeting its objectives and you have to do something about it.

    As w e hav e outlined so far, you h ave tw o basic choices: get people to w ork

    ha rder or get them to w ork sma rter. To decide, you h ave to ma ke a judgment

    about t he cause of the low performance. If you believe the system is underper-

    forming due to low capability, then yo u should focus on w orking sma rter. If, on

    the oth er han d, you think tha t you r w orkers or engineers are a little lazy, undis-

    ciplined, or just shirking, y ou n eed to get them to w ork harder.

    How do yo u decide? Research suggests that people generally a ssum e

    tha t cau se and effect a re closely related in tim e an d space: To explain a puzzling

    event, w e look for anoth er recent, nearby event th at might h ave triggered it.

    People also tend to assume each even t ha s a single cause, underestimate time

    delays, an d fail to account for feedback processes. How do th ese causal attribu-

    tions play ou t in a w ork setting? Consider a man ager observing a mach ine oper-

    ator w ho is producing an unu sually high nu mber of defects. The ma na ger islikely to a ssum e tha t the w orker is at fau lt: The w orker is close in space and tim e

    to th e production of defects, and other operators ha ve low er defect rates. The

    true cause, how ever, ma y be distant in space and time from th e defects it cre-

    ates. Perhaps the defect is actually the result of an inadequate maintenance

    procedure or the poor quality of the training program. In this case, the delay

    betw een the true cause and t he defective output is long, variable, and often

    uno bservable. As a result, man agers are likely to con clude that t he cause of low

    through put is inadeq uate w orker effort or insuffi cient discipline, rather tha n

    features of th e process. The a ttribution of a problem to th e cha racteristicsand

    character fl aw sof individuals in a system rather than to the system in w hich

    they fi nd th emselves is so pervasive that psychologists call it the fun dam ental

    attribution error. 11

    Suppose mana gers conclude th at people, not t he process, are the source

    of low performa nce. Having ma de such an a ttribution it makes sense to increase

    production pressure. As discussed above, an increase in production pressure

    ha s tw o effects. Worker effort imm ediately rises, closing the performance gap

    as the man ager intended. How ever, w orkers are now less able to achieve their

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    objectives by increasing th e time th ey spend w orking. To cont inue to hit th eir

    ever-increasing ta rgets, they eventua lly resort to shortcuts, cutting th e time

    spent on im provement. How ever, as highlighted abov e, the Shortcutsloop, w hile

    ha ving th e desired effect in the short run , yields a lon g-run side effect. With lesseffort dedicated to improvemen t, capability begins to decline. Performan ce falls,

    offsetting th e initial gains. By continua lly increasing throu ghput objectives in

    the pursuit of better performance, ma na gers w ho mistakenly attribute low per-

    forman ce to the attitudes and d ispositions of their wo rkforce inadvertently force

    the system into th e capability trap.

    Super sti ti ous Learni ng

    The bias tow ards blaming people rather tha n th e system in w hich those

    people are embedded means managers are prone to push their organizations

    into th e capability trap. As w orkers spend m ore and more of th eir time on

    throughput and cut back on fundam ental improvement, shouldnt man agers

    realize tha t the true cause of sub-stan dard performa nce is low process capability

    rather than unmotivated w orkers? Unfortunately, in m any situations mana gers

    learn t he opposite lesson.

    Man agers cann ot observe all the activities of the w orkers. Hence, after

    they a pply production pressure, they canno t easily determine how much of

    the resulting rise in th roughput is due to increased w ork effort (the Work Harder

    loop) and h ow much to cutting back on training, improvement or maintenan ce

    (the Shortcutsloop). For example, suppose there is a performa nce gap req uiring

    an additiona l six hou rs of productive effort per person per w eek. Mana gers,

    believing employees are simply not w orking hard eno ugh, increase production

    pressure. Workers buckle dow n, cutting ba ck on breaks, web-surfi ng an d oth er

    non productive time. Suppose these responses yield on ly tw o h ours per personper w eek. To close the rema ining th roughput gap, w orkers resort to shortcuts

    and gradually reduce the time they spend on process improvement, training,

    an d experiment ation un til they free the needed four hours per w eek. Man agers

    observe that th roughput rises by th e equiva lent of six hours of productive effort.

    Because managers do not fully observe the reduction in training, experi-

    mentation, a nd improvement effort (they fail to account for the Shortcutsloop),

    they o verestima te the impact of th eir get-tough policy, in our exam ple by a s

    much as a fa ctor of three. The feedback ma na gers receive does not correct the

    error. To th e contra ry, ma na gers quickly learn th at boosting production pressure

    worksthroughput rose w hen they turned up the pressure. The gain s resulting

    from production pressure provide pow erful evidence confi rming th eir suspicions

    tha t w orkers w ere not giving their full effort.

    We call this syndrome the Self-Confirming Attr ibu tion Er ror: Once man agers

    decide that th e w orkforce is the source of their difficulties, they take actions

    tha t provide convincing and imm ediate evidence confi rming this erroneous

    attribution. The cycle of self-confi rming a ttributions drives the organization to

    higher levels of production pressure a nd few er resources dedicated to process

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    improvement. Far more importantly, how ever, it gradua lly chan ges the ment al

    models of the ma nagers by providing them w ith increasingly compelling evi-

    dence that the source of low throughput can be found in the poor attitudes and

    w eak character of th e w orkforce. Recall the project ma na ger discussed abovew ho w as required to provide hourly status reports on a balky prototy pe. Soon

    afterw ard the problem w as solved, confi rming the bosss belief that he ha d acted

    appropriately, indeed had d ecisively taken ch arge of the situation, ev en th ough

    the team w as already w orking around the clock and his interference drained

    precious time from their efforts to solve the problem.

    More subtly, the long-run effects of production pressure also reinforce

    ma na gers belief tha t w orkers are the problem. The delay betw een increased

    production pressure and increased through put (via th e Work Harderand Shortcuts

    loops) is short, and th e connection betw een w ork effort and ou tput is una m-

    biguous. In con trast, th e erosion of process capability caused by production

    pressure is delayed, grad ual, a nd diffuse. It is distan t in time a nd space from its

    cause. Managers are unlikely to attribute the cause of a throughput gap to the

    pressure they placed on w orkers mon ths or even y ears before. Instead, th ey

    are likely to conclude that th e w orkers ha ve once again slacked off, requiring

    an other increase in production pressure.

    Workers often un w ittingly conspire in strengthen ing the m an agers attri-

    butions. Faced w ith intense production pressure, people are natura lly reluctan t

    to tell supervisors they ca nt m eet all their objectives. The mo re effectively w ork-

    ers cover up the shortcuts they take to m eet their throughput targets, the less

    aw are man agers w ill be of the long-run costs of production pressure. Unaw are

    that improvement activity, maintenance, and problem solving have been cut,

    through put appears to rise w ithout requ iring an y sacrifi ces, reinforcing man age-

    ments attribution that the w orkers really w ere not w orking h ard enough. Whenma na gers eventua lly discover these shortcuts, their view of w orkers as untrust-

    w orthy is confirmed. Ma nagers are then, a s they see it, forcedto monitor w orker

    effort even m ore closely (e.g., mo re frequent status reports, stiffer penalties for

    missing targets, softwa re for monitoring key-stroke rates of data en try opera-

    tors). Wha t starts as an erroneou s attribution abou t the skills, effort, and char-

    acter of the w orkers becomes true. Mana gers w orst fears are realized as a

    consequence of their ow n actions.

    Consistent w ith our th eory, w e are not attributing these dynamics to

    unskilled, inexperienced, or ill-inten tioned m an agers. Rather, the structure of

    the system inadvertently leads even man y ta lented an d dedicated ma nagers into

    the capability trap, w hile at the same time providing compelling evidence that

    the sources of their difficulties lie in factors beyon d th eir control, such a s lazy

    w orkers, a diffi cult union, fau lty machinery, or fi ckle customers. Managers are

    unlikely to escape the capa bility trap because they rarely realize they are in it.

    Instead, as capability stagnates despite repeated attempts at improvem ent, th ey

    slow ly, perhaps reluctan tly, but w ith increasing conv iction, com e to believe

    tha t their problems lie in the attitud es an d chara cter of the people that w ork for

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    them. Having ma de such a n a ttribution, the actions they take, w hile rational

    from th eir perspective, ma ke the situa tion w orse.

    How Super sti ti ous Learni ng Thwar ts Impr ovement Progr amsWha t happens w hen a n organ ization stuck in the capability trap attem pts

    to implement an improvem ent program? Performa nce is low an d w ork pressure

    intense. In such environm ents, improvement programs add to the wo rkload

    the organization is so far behind that it cannot afford to cut back throughput.

    Indeed, in m an y organ izations, man agement imposes aggressive stretch objec-

    tives for both throughput and improvement in the belief that aggressive goals

    are needed to shake things up an d motiva te people. In one fi rm w e studied,

    the general manager laid out his goals for improving the product development

    process by saying:

    We need a development process that is fast, is the best in the industry, and it

    needs to increase throughput by 50% in tw o years. And everyone mu st adhereto the same process.

    At the same time, they lau nched m an y new development projects in

    an ticipation of th e expected productivity gains. View ed through t he lens of man -

    agemen ts ment al model these decisions w ere entirely rational. How ever, tha t

    ment al model, conditioned by the self-confi rming attribution error dyn am ics

    discussed above, led them to the erroneous belief that the delay betw een

    improvement effort and results w as short an d tha t their engineers w ere und er-

    utilized, undisciplined, un motiva ted, an d unw illing to adhere to the specifi ed

    process.

    The com pany spent millions a nd invested countless person-hours to

    create a n ew product development process. The n ew process included better

    technical tools, such as improved CAD/CAE/CAM systems, but also increased

    mon itoring, including a structured stage-gate review process an d ma nda ted use

    of project ma nagem ent softw are. While there w ere some pockets of success, in

    most cases the effort h ad little impact. The leaders of th e chan ge effort often

    attributed its failure to the engineers lack of discipline:

    Engineersby trade, defin ition, and trainingw ant to forever tw eak things.

    Its a Wild West culture. Mana ger A

    We w ent through a period wh ere we h ad so little discipline that w e really ha d

    the process du jour. Get the job done an d how you did it w as up to you.

    Manager B

    A lot of the engineers felt that [the new process] w as no value-add a nd th atthey shou ld have spent all their time doing en gineering an d not fi lling out project

    w orksheets. Its brushed off as bureaucratic.Mana ger A

    It w as fair to say that a lot of engineers viewed th is as a neat w ay to get some

    fancy too ls and to hell w ith process.Manager C

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    Yet, w hen w e asked engineers w hy th e effort failed, we got a different

    story:

    We never had time to ta ke the courses and get th e equipment w e needed to

    really make this stuff w ork. . . . It wa s really exhausting trying to learn how to

    use the tools and do the d esign at th e same time. Engineer A

    People had to do th eir normal w ork as well as [use the new project managem ent

    system]. There just w erent enough h ours in the day, an d the w ork w asnt going

    to w ait.Engineer B

    Un der this system . . . the new w orkload w as all increase. . . . In some cases your

    w orkload could have doubled.Engineer C

    How did w e catch up? We stayed late. Most of the team w as wo rking from 7:00

    a.m. to 8:00 p.m. and on w eekends. A lot of people w orked right throu gh the

    Christmas vacation.Engineer D

    The n ew process is a good one. Som eday Id like to w ork on a project that a ctu-

    ally uses it.Engineer E

    While man agers felt th e engineers had little interest in follow ing the

    process, engineers becam e increasingly frustrated w ith leaders they felt h ad n o

    understanding of w hat w as really required to develop new products. Faced w ith

    the do uble bind of h itting aggressive performan ce targets and eq ually a ggressive

    improvement t argets, they w ere forced to cut corners w hile still appearing to

    follow the process. As one engineer rema rked,

    In ma ny w ays w e w orked around the [new ] system. Good, bad, or indifferent

    thats what happened. We had a due date and we did whatever it took to hit it.

    As ma nagem ent discovers the engineers shortcuts and w orkaround s, their view

    tha t the engineers can t be trusted is confi rmed, an d they a re forced to step uptheir mon itoring. Faced w ith similar diffi culties in its effort to implement a n ew

    product development process, a different fi rm even created a cadre of compli-

    ance ma nagers w hose sole job w as to enforce adherence to th eir new develop-

    ment process.

    Workers in such organ izations quickly learn to h ide problems from oth -

    ers. In a ll of the organizations w e studied, engineers routinely neglected to

    reveal the existence of serious design issues for fear of retribution from m an -

    agers. In on e fi rm, the m otto of the development engineers w as n ever reveal

    you h ave a problem until you also have the solution. In anoth er, engineers

    called th e w eekly progress review meetings the liars clubeach participant

    overstated the progress of his subsystem an d hid know n defects from others in

    the hope tha t others wo uld be discovered fi rst, giving them time to catch up.12

    The con sequence is long delays in the discovery of n eeded rew ork, greatly

    increasing costs, delaying launch, and, often, compromising quality.

    The capability trap goes beyond low capability a nd h igh w ork pressure.

    Eventua lly it gets embedded in deeper structures, including incent ives and

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    corporate culture. As organization s grow m ore dependent on fi refi ghting and

    w orking harder to solve problems caused by low process capability, they rew ard

    an d promote those wh o, through h eroic efforts, man age to save troubled pro-

    jects or keep the line run ning. Con sequently, most organ izations rewa rd last-minute problem solving over the learning, training, and improvement activities

    tha t prevent such crises in the fi rst place. As an engineer at an auto com pany

    told us, Nobody ever gets credit for fi xing problems tha t never ha ppened. Over

    time, senior ma nagem ent w ill increasingly consist of these w ar heroes, wh o are

    likely to groom and favor other can -do people like them selves. As described by

    a project leader w e interviewed,

    Our [company ] culture rewa rds the heroes. Frankly, thats how I got wh ere

    Ive gotten. Ive delivered programs under duress and diffi cult situations and

    the reward that comes with that is that you are recognized as someone that can

    deliver. Those are the opportu nities for advan cemen t.

    Thus incentives and culture n ot on ly reinforce the tend ency tow ard short-runthinking an d w orking harder, but also are themselves sha ped by that very short-

    term focus and w ork-harder m entality, creating an other reinforcing feedback

    tha t intensifies the capability trap.13

    An organization suffering from the self-confi rming att ribution error is

    poorly positioned to escape the capa bility tra p. Improvement programs add

    stress to th e organ ization, triggering greater w ork pressure that prevents people

    from investing in improvement, and encourages shortcuts. In such organizations

    ma ny improvem ent programs never get off the ground. If, despite the w ork

    pressure, people do succeed in a llocating m ore time to improvement, the result

    is a short-term d rop in performance a s time spent w orking falls before the

    investments in improvemen t bear fruit. Observing tha t performance is not

    improving, man agers conclude the particular improvement m ethod is not w ork-

    ing and abandon it. Since the need to improve remains, they search for another,

    more promising tool, only to fi nd it to o suffers a similar fate. The result is grow -

    ing cynicism a mong employees about fl avor of the m onth programs.

    More insidiously, these dyna mics strengthen stereotypes and confl icts

    that not only hurt organizational performance but damage society. Consider,

    for example, how a senior manager explained w hy the product development

    improvement effort he ran had failed:

    Program man agement and the disciplines associated w ith it continue to be a

    problem in my opinion in most w estern cultures. The people tha t a re particularly

    rigorous and disciplined, the J apanese and the Germ ans, tend to be so by cultural

    norms. I cant tell you if its hereditary or society or w here it is they get it but thebest engineers are those tha t tend to be th e most disciplined, n ot a s individual

    contributors but as team -based engineers. So theres a strong push back from the

    w estern type of engineer for much of th is.

    There is no m ention of th e structural features of th e system or th e pres-

    sure, felt throu ghout the organ ization, to deliver ambitious projects on tim e.

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    Instead, this manager blames the failure on the undisciplined character of

    Western engineers. Such a ttributions, here generalized to entire na tional

    groups, and invo king a disturbing racial an d ethn ic subtext, a re typical of the

    fundamental attribution error. As these attributions are shared and repeatedthey become institutionalized. They become part of th e corporate culture, and,

    as suggested by t he q uote a bove, can strength en pernicious stereotypes an d prej-

    udices in society a t large.

    Overcoming the Capability Trap

    So w hat ca n be done? The mo st importan t implication of our an alysis

    is tha t our experiences often teach u s exactly th e w rong lessons about h ow to

    maintain a nd improve the long-term health of the systems in w hich w e w ork

    an d live. Successful improvement m ust include a signifi cant shift in the men tal

    models of tho se both leading a nd participating in a n im provement effort. This

    insight w as captured succinctly by on e man ager in a successful improvemen t

    effort:

    There a re tw o theo ries. One say s, theres a problem, lets fix it. The oth er says

    w e ha ve a problem, someon e is screwing u p, lets go beat th em u p. To m ake

    improvement, w e could no longer embrace the second th eory, we ha d to use

    the fi rst .

    Once the cycle of self-confi rming a ttributions is broken, an y n um ber of process

    improvement tools and metho ds can h elp improve capability. Without this shift,

    new tools and techniques, no matter how great th eir potential, are unlikely to

    succeed.

    Breaking th e cycle of self-confi rming at tributions is not easy, but it can

    be done. The follow ing are examples from tw o organizations tha t overcame

    these diffi culties and introduced successful improvement efforts.14

    Du Pont

    In 1991, an in-house benchma rking study docum ented a gap betw een

    Du Ponts maintenance record and those of the best performing companies in

    the chem icals industry. The benchm arking study revealed an apparent para dox:

    Du Pont spent more on maintenance than industry leaders but got less for it.

    Du Pont had the highest number of maintenance employees per dollar of plant

    value, yet its mechan ics w orked more overtime. Spare parts inventories w ere

    excessive, y et th ey relied heavily on costly expedited procurement of critical

    componen ts. Overall, Du P ont spent 10-30% more on ma intena nce per dollarof plan t value tha n the industry leaders, wh ile overall plant uptime w as some

    10-15% low er.

    An experienced mana ger, Winston Ledet, and a tea m cha rged w ith

    improving maintenance operations, developed a system dynamics model of

    th ese issues. The mo deling process invo lved exten sive han ds-on w orkshops in

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    w hich the tea m, a ssisted by a n experienced mo deler, discussed, tested, and

    chan ged the model as they identifi ed areas needing improvement. Using the

    model as a la boratory t o design a nd test different policies, the team gradua lly

    developed an appreciation for the capability trap and the paradox of high main-tenan ce costs and low reliability.

    To see how the ca pability t rap arose in t he chem icals indu stry, ima gine

    the effects of cost cuts on m aintena nce, such as those beginning w ith the oil

    crisis of 1973 and subsequen t recession. In chem ical plan ts, w hen critical equip-

    ment breaks down, it must be fi xed. Hence maintenan ce managers required

    to reduce costs must cut preventive maintenance, training, and investments in

    equipmen t upgrades. The drop in planned m aintena nce eventua lly causes

    breakdow ns to increase, forcing ma na gement to reassign m ore mechan ics from

    planned ma intena nce to repair w ork. Breakdow ns then rise even more. As

    uptime falls, operators fin d it harder to meet dem an d an d become less willing to

    take equipment dow n for scheduled maintenan ce, leading to more breakdow ns

    an d still low er uptime. More breakdow ns simulta neously constrain revenue (by

    low ering production) a nd increase costs (due to overtime, expedited parts pro-

    curement, th e nonroutine an d often h azardous nature of outa ges, collateral

    dam age, an d so forth). More subtly, low er uptime erodes a plants ability to meet

    its delivery com mitmen ts. As it develops a reputation for poor d elivery reliabil-

    ity, business volume a nd ma rgins fall further. The plan t slow ly slides into th e

    capability trap, w ith high breakdown s, low uptime, an d high costs.

    Policy analysis show ed tha t escaping the capability trap necessarily m eant

    performa nce w ould deteriorate before it could improve: While continuing to

    repair breakdow ns, the organ ization ha s to invest additional resources in

    planned maintenance, training and part quality, raising costs. Most importantly,

    increasing planned maintenance reducesuptime in the short ru n because opera-ble equipment must be taken off-line for the planned maintenance to be done.

    Only later, as the Reinvestmentloop begins to w ork in the virtuous direction, d oes

    the breakdown rate drop. Few er unplanned breakdowns give mechanics more

    time for planned maintenance. As maintenance expenses drop the savings can

    be reinvested in tra ining, parts qu ality, reliability en gineering, plann ing an d

    scheduling systems, and other activities tha t further reduce breakdow ns. For

    exam ple, upgrading to a m ore durable pump seal improves reliability, allow ing

    maintenance intervals to be lengthened and inventories of replacement seals to

    be cut. Higher uptime also yields more revenue an d provides additional

    resources for still more improvement. All the positive feedbacks that once a cted

    as vicious cycles dragging reliability dow n becom e virtuou s cycles, progressively

    and cumulatively boosting uptime and cutting costs.

    Now th e challenge facing the team w as implementa tion. They knew

    noth ing could happen w ithout th e w illing participation of thousan ds of people,

    from th e low est-grade ho urly m echan ic to regional vice presidents. They also

    realized that th eir view s had chan ged because they ha d participated in the

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    modeling process. Somehow they h ad to facilitate a similar learning process

    throughout th e plants.

    The team converted the ma intena nce model into an interactive role-

    playing simulation they called the Manu facturing G ame.15 The game is closelybased on th e model an d realistically captures the time delays, costs, and oth er

    param eters cha racterizing typical plan ts. They embedded th e gam e in an inter-

    active w orkshop designed to create an environm ent for learning tha t addressed

    emo tion al as w ell as cogn itive issues. The process at Du Po nt s Wash ington

    Works complex in Pa rkersburg, West Virginia, w as ty pical:

    The team w as initiated w ith a tw o-day learning lab . . . learning the concepts of

    defect elimination a nd experiencing th e Man ufacturing Ga me. . . . The m aterial

    is presented in the form of lectures, skits and participative exercises in an off-site

    environmen t. Posters and music are used. The a tmosphere is much different than

    routine plant m eetings or training, to open up their thinking. . . . Through inter-

    active exercises, the team develops their personal aspirations for improving the

    area w here they h ave chosen to w ork. . . . [Then] they . . . develop an action

    plan to immediately start w orking.16

    Despite its ma ny simplification s, the game quickly becomes in man y w ays a

    real plant w ith real emotion s and confl icts am ong players. Initialized w ith high

    breakdow ns and low uptime, the people play ing the role of operations mana gers

    face intense pressure to keep equipment run ning a nd often rebuff attempts to

    increase planned m aintena nce, just as in the real w orld. Players w ho stick w ith

    the prevailing cost-minimization , w ork-ha rder, reactive ma intena nce policies

    can keep costs low for a w hile. However, as defects accumulate, uptime slow ly

    sinks w hile costs rise. Teams w ho follow a plann ed ma intena nce strategy fi rst

    fi nd costs rise w hile uptime falls. Soon, how ever, costs begin to fall and uptime

    rises. The gam e allow s people to experience the w orse-before-better dyna mic ina few hours instead of a few m onths. For many, the game w as the fi rst time in

    their careers they experienced the possibility that improvement w as actua lly

    possible.

    The gam e an d learning labora tory proved popular. How ever, playing it

    once w as not enough. The team found that th ey had to run several w orkshops

    for a given plant before a critical mass emerged to lead a ction team s and put

    proactive mainten an ce policies into practice. Individua l plants needed th e capa-

    bility to run th e game so th eir own people, w ith their site-specifi c experience

    an d legitimacy, could run it on dema nd. B y th e end of 1992, some 1200 people

    ha d participated in the w orkshop, an d more tha n 50 facilitators had been

    certifi ed.

    At plants that implemented the program by the end of 1993, the mean

    time betw een failure (MTBF) for pumps (the focus of th e program) rose by an

    average o f 12% each time cumu lative operating experience dou bled. Direct

    ma intena nce costs fell an a verage of 20%. In 23 compara ble plant s not imple-

    ment ing the program the learning rate a veraged just 5% an d costs w ere upan

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    average of 7%. Washington Works boosted production capability 20%,

    improved customer service 90%, an d cut delivery lead time by 50%, a ll w ith

    minimal capital investment and a drop in maintenance costs. For the company

    as a w hole, conservative estimates exceed $350 million/year in avo ided ma inte-nance costs alone.

    How ever, success creates its ow n ch allenges. One issue related to th e

    persistence of th e cost-saving men tality. A member of the m odeling team com-

    ment ed, As soon a s you get the problems dow n, people w ill be taken aw ay

    from the effort and th e problems will go back up. In fact, ma nda ted corporate

    cost-cutting program s did cause signifi cant dow nsizing throu ghout th e entire

    compan y, w eakening the reinvestment feedback and limiting their ability to

    expand th e program. Winston Ledet took early retirement an d began w orking

    w ith other compan ies interested in the gam e and learn ing lab. These fi rms

    include other chem icals ma nufa cturers along w ith fi rms in the energy, auto -

    motive, a nd h igh-tech sectors.

    Br i ti sh Petr oleum

    One of the organizations Ledet w orked with a fter leaving Du Pon t

    w as British Petroleums refi nery in Lima , Ohio. Foun ded in 1886 by J ohn D .

    Rockefeller, an d once Queen of the Fleet, the refi nery enga ged in cost cutting

    during th e 1980s tha t triggered th e vicious cycle of increasing breakdow ns,

    higher maintenance costs, and less planned maintenance, pushing it into the

    capability trap. B y th e early 1990s, Lima lagged w ell behind oth er U.S. refin er-

    ies. B P began to th ink about selling or closing the fa cility.

    In 1994, the Lima facility introduced the maintenance learning lab and

    other system dyna mics tools. It w as not a top ma na gement intervention : The

    origina l champions w ere an equ ipment specialist, a ma intena nce training super-visor, an d an engineer. Successful pilot projects led to favora ble w ord of m outh ;

    eventua lly 80% of all employees participated in th e program. Soon dozens of

    improvement teams w ere in place. During the fi rst six months, ma intenance

    costs ballooned by 30%. Having experienced it in th e game, m ana gement w as

    prepared for the w orse-before-better dyna mic, and focused on th e

    improvements generated by the action teams.

    In J anua ry 1996, BP a nnoun ced that it intended to sell the Lima refin ery

    an d stepped up its cost cutting an d dow nsizing. A few mon ths later BP stunned

    the employees by ann ouncing that it could not fi nd a buyer at a satisfactory

    price and w ould therefore close the refin ery. The an nou ncement w as a deep

    blow to the w orkers an d the commu nity. One of the most importan t businesses

    in the commu nity, the refin ery employed 450 people an d pumped more tha n

    $60 million per year into Limas depressed economy. Some employees became

    discouraged and questioned the value of the learning lab and improvement pro-

    gram. A few transferred to oth er BP facilities or left altogether. Winston Ledet

    described w hat happened next:

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    For those w ho d ecided to stay w ith the ship, a new spirit emerged. They realized

    that th ey needed a future in Lima a nd should take responsibility for creating that

    future. The fi rst step w as to ensure that the exit of m any experienced people did

    not th row them ba ck in the reactive mode. . . . It actually created a clearer focus

    for the people w ho rema ined. They w ere all there because they had chosen to be

    there.

    Soon th e impact of the new ma intena nce policies an d attitudes w as clearly

    visib le (Table 1).

    These drama tic improvemen ts did not go un noticed. On J uly 2, 1998,the bann er headline of the Lima Newsann ounced Oil Refin ery Rescued. Clark

    USA, a privately held Fortune 500company w ith refin ing and distribution inter-

    ests, agreed to bu y th e Lima refi nery for $215 million an d keep it operating.

    The Du Pont an d B P cases illustrate the pow er of a shift in men tal mod els.

    The model, game, and w orkshop do not teach a nyone h ow to maintain eq uip-

    ment. For example, a BP team reduced butane flare-off to zero, saving $1.5 mil-

    lion/year a nd reducing pollution. The effort to ok tw o w eeks and cost $5000, a

    return on inv estment of 30,000%/year. Members of the team h ad know n a bout

    the problem and h ow to solve it for eight yea rs. They a lready ha d all the engi-

    neering know -how they needed, and m ost of the equipment a nd ma terials were

    already o n site. Wha t ha d stopped them from solving the problem long ago? Theonly barrier wa s the mental mod el tha t there w ere no resources or time for

    improvement, th at th ese problems w ere outside their control, and th at th ey

    could never ma ke a difference.

    The m odeling process and t he resulting game w ere effective because they

    eliminated many of the impediments to learning in the real system. Dynamics

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    TABLE 1. Improvement at the Lima Refinery

    Pump MTBF up from 12 to 58 months( failuresdown from more than 640 in 1991 to 131 in 1998).

    D irect savings: $1.8 million/year.

    Hydrocarbon flare-off down from 1.5% to 0.35% , saving $0.27/barrel and improving environmental

    quality.

    O n-line analyzer uptime improved from 75% and not trusted to 97% and trusted,permitting real-time

    optimization of product flow.Savings: $0.10-0.12/barrel.

    Safety incidentsand lost hourscut by a factor of 4.

    Thirty-four production recordsset.

    Cash margin improved by $0.77 per barrel of oil processed.

    Total new value created:$43 million/year.Total cost: $320,000/year. Ratio: 143:1.

    Learning initiative under way for other BP facilitiesaround the world.

    Source:Paul Monus,Proactive Manufacturing at BPsL ima O il Refinery, presented at N ational Petroleum RefinersA ssociation

    M aintenance Conference, M ay20-23,1997, N ew O rleans; J. G riffith, D. Kuenzli, and P. M onus,Proactive M anufacturing:A ccelerating

    Step Change Breakthroughsin Performance, N PRA M aintenance Conference, M C-98-92,1998;Paul Monus, personal

    communication.

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    such as the progressive slide into th e capability tra p that n orma lly play out ov er

    years or even decades could be experienced in just a few hou rs. Unlike the real

    w orld, people could take different roles: A mechan ic play ing the role of plant

    man ager might fi nd himself w ith low u ptime an d then cut preventive mainte-na nce to avoid eq uipment ta kedow ns and cut costs. Seeing people from differ-

    ent functions and backgrounds enacting the same behaviors helped break the

    vicious cycle of self-confi rming a ttribution errors and blame. The systems thin k-

    ing process enabled people to experience for th emselves the long-term, organ i-

    zation-w ide consequences of their actions. They d iscovered ho w to use initial

    successes to create resources for further improvement and how to survive the

    short-run d rop in performan ce. They saw how small actions could snow ball into

    major gains. Most importantly, they learned that they could, after all, make a

    difference.

    Notes1. See G. Easton and S. Ja rrell, The Effects of Total Quality Man agement on Corpo-

    rate Performa nce: An Empirical Investigation, Journal of Business, 2 (1998): 253-

    307; K. Hend ricks an d V.R. Singha l, Qu ality Aw ards an d the Ma rket Value of th e

    Firm: An Empirical Investigation, Management Science, 43/3 (1996): 415-436.

    2. See Easton and Ja rrell, op. cit.; Darrell Rigby, M ana gement Tools and Techniques:

    A Survey, California Management Review, 43/2 (Winter 2001): 139-159.

    3. See J . Pfeffer and R. Sut ton, The Knowing-Doing Gap(Boston, MA: Harvard B usi-

    ness School Press, 2000); K. Klein and J. Sorra, The Ch allenge of Inn ovation

    Implementation, Academy of Management Review, 4 (1996): 1055-1080.

    4. Published summa ries can be found in: J. Sterman, N. Repenning, and F. Kofman

    Un anticipated Side Effects of Successful Quality Programs: Exploring a Paradox

    of Organizational Improvement, Management Science, 43/4 (1997): 503-521; N.

    Repenning and J. Sterman, Getting Quality the Old Fashion: Self-Confirming

    Attributions in th e Dyn amics of Process Improvement, in R.B. Cole an d R. Scott,eds., Improving Theory and Research on Qualit y Enhancement i n Organi zations(Tho u-

    sand Oaks, CA: Sage, 2000), pp. 201- 235; E. Keating and R. Oliva, A Dynamic

    Theo ry of Susta ining Process Improvemen t Team s in Prod uct Developm ent, in

    M. Beyerlein and D. Johnson, eds., Advances in I nterdiscipl inary Studies of Teams

    (Greenw ich, CT: JAI Press, 2000); R. Oliva, S. Rockart, and J. Sterm an, Ma naging

    Multiple Improvemen t Efforts: Lessons from a Semiconductor Ma nufacturing

    Site, in D. Fedor and S. G hosh, eds., Advances in the Management of Organizational

    Quality(Green w ich, CT: JAI Press, 1998), pp. 1-55; J. Ca rroll, J. Sterm an , an d A.

    Markus, Playing the Maintena nce Game: How Mental Models Drive Organiza-

    tion Decisions, in R. Stern a nd J . Halpern, eds., Debating Rationali ty: Nonrational

    Elements of Organizational Decision Maki ng(Ithaca, NY: ILR Press, 1997).

    5. For formal models of implementation see: Sterman, Repenning, and Kofman op.

    cit.; N. Repenn ing, Drive Out Fear (Un less You Ca n Drive It In ): The Role of

    Agency a nd Job Security in Process Improvement Efforts, Management Science,

    46/11 (2000): 1385-1396; N. Repenn ing, A Dyn am ic Model o f Resource Alloca-

    tion in Multi-Project Research a nd Development Sy stems, System Dynamics

    Review, 16/3 (2000): 173-212; N. Repennin g, A Simulat ion B ased-Approach to

    Understanding the Dynamics of Innovation Implementation, Organi zation Science

    (forthcoming).

    6. Repenning and Sterman (2000), op. cit .

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    7. See A. Schneiderman, Setting Quality Goals, Qual it y Progress(April 1988),

    pp. 55-57; J. Sterman, N. Repenning, and F. Kofman, op. cit.

    8. Schneiderman, op. cit.

    9. For an example, see Sterman, Repenning, and Kofman, op. cit .

    10. The dyn amics of project management an d software development ha ve been

    treate d exten sively in system dy na mics. See, for exam ple, T. Abdel-Ham id, The

    Economics of Softw are Qua lity Assurance: A Simulation-Based Case Study, MIS

    Quarterly, 3 (1997): 395-411; D. Ford and J. D. Sterman D yna mic Modeling of

    Product Development Processes, System Dynami cs Review, 14 (1998): 31-68.

    11. For an excellent summary of attribution theory, see S. Plous, The Psychology of

    Judgment and Decision Making(New York, NY: McGra w -Hill, 1993).

    12. See also George Roth and Art Kleiner, Car Launch(New York, NY: Oxfo rd Un iver-

    sity Press, 2000).

    13. See N. Repenn ing et al., Past the Tipping Poin t: The Persistence of Fire-Fighting

    in Product Development, published in th is issue [California Management Review,

    43/4 (Summer 2001)].

    14. These cases are discussed in depth in J . Sterman, Business Dynamics: Systems Thi nk -

    ing and Modeli ng for a Complex World(New York, NY: Irw in/McG raw -Hill, 2000),

    chapter 2.

    15. See Winston Ledet, Engaging the Entire Organization: Key to Improving Reliabil-

    ity, Oil and Gas Journal, 97/21 (1999): 54-57.

    16. R. Tew ksbury and R. Stewa rd, Improved Production Capability Program at Du

    Ponts Washington Works, Proceedings of the 1997 Society for Maintenance and

    Reliability ann ual con ference.

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