Monthly Archives: June 2013

6 Hidden Demands On Engineer’s Time

Firms never have enough engineering resources to meet business demands yet projects often overrun in cost and schedule.  Today’s engineering work environment is a complex and chaotic mix of market change, multiple projects, and development risk/uncertainty.

Development projects, the bread and butter of most engineering organizations, require robust project and risk management protocols to achieve cost, schedule, and quality goals. Engineering resources are often pulled in different directions with discretionary requests for their time contrary to what business leaders set as priorities and their strategic intent. The gap between reality and perception can be large leading to misunderstanding, misdirected blame, reduced morale, and degraded business performance.

To understand engineering delivery throughput it is essential that business leaders understand the total demand that the firm is placing on their engineers beyond project commitments caused by six hidden demands on engineer’s time.

Total Engineering Workload

A non-supervisory engineer’s normal available work time for direct engineering project work is about 82-86% of total possible work hours or approximately 47 weeks when holidays, vacation, and normal business demanded time (performance reviews, town halls, functional group meetings, training) are taken into account. There are slight differences for country, role, company situation, and their level (determining vacation) but this baseline range is fairly consistent world wide. Overtime and weekends are normally held in reserve for short term capacity surges to address unforeseen issues and is over and above this total possible work time.

The reality for most engineering organizations is a total engineering workload for a non-supervisory engineer is comprised of eight types of activities:

  • Multi-Project Direct Work Tasks & Activities;
  • Development Project Risk / Uncertainty Mitigation & Treatment;
  • Discretionary Business Activities;
  • Multi-Project Inefficiencies;
  • Un-Forecast Back-Door / Walk-In Activities;
  • Process Inefficiencies (Business & Engineering);
  • Rework; and
  • Daily Distractions.

Project schedules are often based on the first two types of activities or the work that one would expect would make-up the majority an engineer’s productive time. This approach can lead to under resourced engineering organizations. The problem is that the six hidden demands can create 15-25% additional work. Only 60-70% of engineering capacity may be going to project work as a result causing schedule and cost overruns as well as excessive overtime to keep up. This work volume disconnect drives the engineering capacity perception / reality gap. To address the gap business leaders and engineering management/staff need to determine the extent to which the six hidden demands are impacting their engineering capacity plan.

Discretionary Business Activities

Discretionary business activities are undertaken for good reasons because they lead to growth or improvement in business performance. Engineers often must support business sustaining activities because of their product/technical knowledge, experience, customer knowledge, and academic credentials.  Bids and proposal support alone can on average demand 3-5% engineering productive capacity. Other discretionary business activities aimed at improving business performance may include enhanced training, continuous improvement, or reorganizations which can also consume several percent engineering productive capacity.

The firm’s industry environment, market cycle, and the degree of market force driven change can also have a significant short or medium term impact on the volume of this discretionary engineering workload. Assumptions about discretionary business activity volumes based on years with little change leads to significant engineering capacity demand under estimation.

Capacity availability problems also often arise from discretionary business activities if they are not timed or integrated well with direct project schedule commitments. Discretionary business activities should be synchronized during project demand valleys avoiding seasonal project demand peaks if present in annual work cycle.

Multi-Project Inefficiencies

Most businesses today are multi-project environments because the extremes of dedicated functional or dedicated project teams are inefficient or impossible to implement with scarce specialist expertise. The number, size mix, complexity mix, and novelty mix all combine dynamically to create a constantly shifting work plan with winning / losing project managers. Multi-project inefficiencies are always bad.

Priority conflicts are a leading source of project schedule delays in multi-project environments. Organizations that operate lean or with labour shortages are particularly susceptible to priority conflict. Furthermore a misalignment between project priority and project manager assertiveness can often put individual engineers into difficult situations that impacts morale and job satisfaction that if left unchecked can degrade the operational effectiveness of the engineering organization and impact overall business performance.

Inefficiencies can also be caused simply by the sheer number of individual projects.  The more projects that individual engineers support the more project related overhead activities they are required to keep up with. Project related overhead activities include stand-up or status meetings, project email information, email responses from them, schedule updates/EACs/ETCs, and customer meetings. This activity can require several hours of work per week to sustain multiplied by the number of projects and depending on the stage of the project can be quite intense. This workload is often budgeted under project management as opposed to engineering so is drain on engineering capacity even though project budgets are fine and the net result is a schedule overrun.

To solve this issue business leadership need to implement engineering WIP constraints by limiting the number and mix of projects in process and establish a company wide priority system. Leadership must resist the temptation to load engineering staff up to 82-86% which causes schedule overruns, cost overruns, and near constant overtime leading to fatigue and increased error rate.

Un-Forecast Back Door / Walk-In Requests

Often business leaders and even engineering managers are unaware of many requests coming through the back door to their staff. Individual engineers want to do their best, satisfy external/internal customers but are left confused and unclear of priorities.   Back door and walk-in requests can lead to project schedule delays. Typical examples of back door  and walk-in requests for engineering advice include engineering support to supply chain, engineering support to production, and customer support requests. Another type of back door and walk-in requests on engineers are management questions or management emergencies. Although good intentioned engineers are compelled to respond or they fear being labelled as non-team players, non-responsive, or difficult employees.

Leadership should test whether these back door and walk-in requests are essential for the business and if so should budget to meet this demand. A separate support group could be established if the volume is large enough to separate support work from project work potentially rotating junior staff through the group for experience. Often engineering support groups are completely overhead but when times are difficult the groups are down-sized and the work load moves back to the project support engineers leading to a re-emergence of schedule and cost overruns.

Process Inefficiencies

Waste and inefficient processes add to total engineering workload. Process inefficiencies can relate to either business or engineering process waste. Focusing on engineering process inefficiencies, forms of engineering waste include:

  • Over production of information;
  • Over processing of information (over design);
  • Miscommunication of information;
  • Stockpiling of information;
  • Generating defective information;
  • Waiting for information; and
  • Unnecessary movement in working to the process.

An excellent discussion on engineering waste can be found in Waste in Lean Product Development by Josef Oehmen and Eric Rebentisch. Lean engineering methods provide solutions to eliminating waste in engineering processes.  Simply redesigning business or engineering processes can free up enough engineering capacity to mitigate the other hidden workload – sometimes in the 10-15% range. Leadership should ensure that a volume of engineering capacity is budgeted for continuous improvement on an annual basis.

Engineering Rework

Engineering rework can also be a large drain on engineering resource capacity sometimes exceeding 5%. Engineering rework is difficult to see in the same way that engineering work in process is difficult to see because engineering work involves information rather than physical parts. Engineering rework is any effort spent in correcting information resulting from engineering mistakes, errors, or change required to manufacture, build, or support a product. Often though the actual presence or need for engineering rework can be subjective where right or wrong are not clear cut but accountability for solving engineering rework rests with engineering staff and engineering management. The degree of product novelty and complexity can drive higher rates of rework. Common defect categories include:

  • Technical accuracy;
  • Technical argument structure & soundness;
  • Engineering approach;
  • Deliverable completeness;
  • Regulatory compliance;
  • Deliverable format, typos, or grammatical errors (least important)

Rework is a form of waste and must be eliminated. Organizations should establish engineering error tracking systems as part of an engineering quality management system to determine trends, volumes, and support root-cause analysis continuous improvement activities to reduce rework. Rework should be measured and addressed in conjunction with engineering process improvement.

Daily Distractions

Finally, the daily distractions that impact everyone in a work environment go largely unnoticed in most firms also drain valuable engineering resource capacity. Daily distractions include: phone calls; emails; office noise; excessive meetings; and social walk-in interruptions.  Even just 15min/day of distractions can add up to 60 hours per person. A good method to address daily distractions is to have quiet times, often in the morning when staff are most productive, where emailing and phone calls are not permitted.

Annual Engineering Capacity Forecasting

In today’s complex work environment business leaders and engineering managers need to  understand the total engineering workload, how it behaves dynamically, and how it can degrade the operating efficiency of their finite and constrained engineering capacity to correctly forecast the needed capacity.  The six hidden demands on engineer’s time can have a significant impact on engineering delivery throughput.

Problem areas are opportunities to free up capacity to use on more productive work and reduce project schedule and cost overruns. The annual business operating plan is the time to take a deep look at total engineering workload, underlying work volume assumptions, and plan improvement work to prepare a realistic engineering workload forecast. Periodic time studies may be worthwhile to uncover the degree to which the six hidden demands on engineer’s time are causing project schedule and cost overruns.

Canada’s Industrial Strategy Debate

The topic of Canadian industrial strategy is getting some new air time.  Discussion has been triggered by a paper The Resurgence of Industrial Policy and What It Means For Canada by Dan Ciuriak and John M. Curtis and recently commented on by Terence Corcoran in the Financial Post.

In a previous post  the lack of industrial strategies was discussed a potential cause factor for Canada’s low innovation performance due to the misalignments between national strengths, R&D, and industry.

This post continues this discussion given recent debate in the press but leads to the need for a national vision to really resolve the industrial strategy debate. As Lewis Carroll said “if you don’t know where you are going, any road will get you there” which seems to be the path Canada is on at the moment.

Framing The Industrial Strategy Debate and The Spectre of Social Unrest

The industrial strategy debate can easily be derailed by various extreme views such as nationalism, fear mongering, anti-globalization, etc so how the debate is framed matters if agreement is ever to be reached. For example, one can detect the fear in developed economies from the rise of Asian economies that is just below the surface. The economic arguments should not be framed as re-slicing the same global economic pie with developed economies getting less and Asian more rather the debate in this case should be framed as one of enlarging the global economic pie with growing the global middle class in BRIC and emerging countries.

Re-shoring movement is another simmering issue which hopes to reverse the flow of manufacturing jobs lost to off shoring over the last decade. For example the Society of Manufacturing Engineers has a program called Take Back Manufacturing to bring visibility to this issue. The re-shoring debate is picking up momentum particularly in jurisdictions that have relied on manufacturing.

One can’t deny though that although developed open economies are far from total collapse today one emergent issue not mentioned in the report and why countries in the EU in particular may be relooking at industrial strategy is the very real potential for social unrest given prolonged weak growth.  Europe is already starting to see the emergence of a lost generation.  While free markets are preferred capitalism does create winners and losers. Industrial strategy is insurance against losing, falling behind, and the social implications. What the last 100 years of capitalism has taught us is that if a country slides from a winner to becoming a loser, unemployment swells, a lost generation forms social unrest soon follows. The re-emergence of industrial strategy may simply be a hedge by governments (Japan, Germany, France, US, etc) who need to avoid the potential for social unrest.

Why Canada Needs Industry Strategies

In Canada, the investment in the oil sands will likely reduce in the medium term GDP and growth will slow and unemployment increase unless other industry sectors pick up. Canada’s economy depends on export trade to grow because of our small economy.  GDP growth from NAFTA stalled a decade ago so the new free trade agreements are positive moves to better access global markets. To export firms need to be large enough to have the resources to develop international markets which is expensive and takes time. 98% of Canadian firms are SMEs. Canada is not growing enough global scale businesses. Canadian gazelles growth slows after five years as reported by Deloitte. Global scale businesses require several decades to grow.  Industrial strategy should enable more bang for the buck from innovation to support growing firms to compete internationally.

Our university education & research system is great but there are not enough high value jobs in industry to absorb the number of students graduating and fully capture the economic benefits of science & technology and innovation investments that are disjoint and spread thin. The so called skills mismatch hotly debated now with the shift of our economy to resource based reflects the fact that the university education system is not geared to a resource economy but rather an advanced industrial economy.

Alignment – The Benefit Industrial Strategies Bring

Notwithstanding long run macroeconomic trends the efficiency of Canadian economic development from innovation investments has been undermined by flip flopping due to changes in political power, departmental agenda conflicts, regional in-fighting, loss of government industrial sector knowledge, and a national deficiency in ability to commercialize ideas. These effects have been destroying value by starting, stopping, changing, and restarting innovation support. Canada needs to dampen these effects to gain the following benefits:

  • Align innovation efforts from all levels of government (federal, provincial, and municipal),
  • Alignment between industry, academic, NRC, and government R&D investments which requires a long run view to make the right investment choices – such as recent changes at the NRC,
  • Alignment maximizes value for limited tax dollars going towards innovation, economic development / industrial development,
  • Long term stability to allow clusters to continue to grow and private sector innovation to drive cluster agglomeration and R&D investments to build on each other,
  • Secure the returns from new defence procurement investments targeting key technology areas,
  • Framework for targeting FDI efforts that feed innovation momentum, and
  • Enable Canadian businesses to grow large enough to compete internationally.

Strategic versus Non-Strategic Industries

Although wishful proponents of non-strategic investment may pitch an idea as ‘strategic’ in hopes of gaining an edge there are industries that actually should be designated as strategic. This issue requires honest debate, dialogue, leadership, and long term national vision while avoiding undue influence for agendas that can harm this process. In the presence of globalization nations still have a right and governments an obligation to facilitate this debate and decide what is best for their countries and their citizens. Is this protectionism or simply looking out for the best interests of Canada?

The closest thing Canada has to a stated list of priority areas is the 2007 Science and Technology Strategy where four areas were identified as important for the national interest: environmental; natural resources and energy; health and related life sciences; and information and communication technologies. The report Beyond the Horizon recently proposed that Aerospace and Space be added to these four because of the prominence of this industry sector to the economy overall.

Defence is often touted as ‘strategic industry’ because national security and sovereignty should not be exposed to the risks of a disrupted global supply chain or foreign state interests.  Defence has been a recent focus of Public Works Government Services Canada where there are economic grounds for fostering innovation and maximizing the return from government defence purchases. The often forgotten story behind Silicon Valley is good example of the misconceptions about its history and role government defence investments had in creating the cluster over many decades positioning it to capture the microelectronics and information technology wave.

Building on the four priority science & technology areas, aerospace and space, and defence, two other areas are worthy of consideration: resource value added and food processing/agriculture. With the Canadian economy shifting dramatically to a resource based economy there seems to be a growing recognition that rather than exporting raw materials that Canada should develop a resource value added industrial strategy. With a growing world population Canada has a strong role to play in feeding the world.

Industrial strategies still need to be synchronized with industry cycles and adjust in response to changing macroeconomic, technological, and security environments but by targeting strategic industries the country gains a strong foundation for entire economy in the long run fuelled by aligned innovation to remain globally competitive. Perhaps a good test for a strategic industry is one that enables a country to continue to function within reasonable bounds providing its’ citizens with the necessities for living and security in the presence of a failure in globalization. Beyond this it is really a question of what level of prosperity and wealth the nation intends to reach, maintain, or not drop below.

This leads though to the need for a national vision for the country that can enlighten the debate as to which industries are strategic versus non-strategic in Canada. What is the vision for Canada in the next 20, 50, or 100 years? If we don’t know where we are going how do we know we are taking the right steps to get there.

Innovation Investment Decision Risk Aversion

If overcoming uncertainty and risk is the largest barrier to innovation regardless of the type of firm it is important to understand how human biases and tendencies may be influencing innovation investment decision making. Extreme leadership risk aversion can cause firms to miss good opportunities and harm long run performance and growth prospects. Extreme leadership risk taking on the other hand can bet the farm jeopardizing the entire business. Healthy leadership risk management requires a balance suitable for a firm’s external, internal environment, and business cycle. Canadian business leaders appear to be tending towards extreme risk aversion.

What are some people biases and tendencies that may be driving extreme leadership risk aversion when making innovation investment decisions?

Innovation Investment Risk Sources and Assessment

To understand the people biases and tendencies impacting innovation investment decision risks assessments we first need to quickly review innovation risks assessment.

The return on innovation investments targeting new or improved ways of doing business or products are measured in terms of new value creation or improved value capture. In pure financial terms returns would need to exceed the corporate hurdle rate within the business risk tolerance. Risk assessments for innovation investment therefore consider what could impact achieving the return on innovation investment. Although risk sources tend to be viewed as negative equal balance should be given to upside as well as down side risks.

In general business risk sources that may impact innovation investments can cover operations, market, financial, or political risks including:

  1. Market Risks – Risks impacting revenue forecast and demand for the innovation particularly assumptions related to customer’s need and willingness to pay for the innovation.
  2. Adoption Risks – Risks impacting the adoption of the innovation in the innovation ecosystem up to and including the end user.
  3. Technical Risks – Risks impacting the technical achievement of the innovation performance such as product performance, feasibility (readiness for commercialization), regulatory approval/compliance,
  4. Operational or Execution Risks – Risks impacting the operational delivery of the innovation including supply chain disruptions, procedural failure, cash flow for required work in process.
  5. Co-Innovation Risks – Risks impacting key supplier/partner innovation required to achieve  innovation or deliver the innovation to market.
  6. Schedule Risks – Risks impacting lateness of delivering innovation to capture the value.
  7. Cost Risks – Risks impacting the innovation investment costs that impact profitability.
  8. Quality Risks – Risks impacting the innovation investment customer satisfaction, conformance to specifications, reliability, durability, serviceability, and aesthetics factors.
  9. Financial Risks – Pricing, asset, currency, or liquidity risks impacting the innovation return.
  10. Reputation Risks – Risks impacting business reputation such as product failure, integrity, social systems,
  11. Legal Risks – Risks arising from the innovation that may drive liability torts, property damage, IP legal actions.
  12. Strategic Risks – Risks arising from the innovation that may create new threats from new market entries, strained partnerships, regulatory changes, random surprise events impacting innovation assumptions,
  13. Political Risks – Risks impacting market for the innovation arsing from government protectionism, freedom of trade and tariffs, labour markets, local capital markets, corruption, and openness in different countries.
  14. Business Model Risks – Risks that assumptions unpinning the innovation are valid.

The list of potential risks impacting innovation investments is long giving decision makers reason to pause.  Management competence & experience are required to judge the severity and probability of each risk. The context for innovation investment decision making is therefore complex, ambiguous, and subject to uncertainty.

Risk Aversion In Decision Making

How does the presence of risk affect decision making? According to Kahneman and Tversky most people are risk seeking when it comes to losses but risk averse when it comes to gains.  Instead of weighing decision alternatives impact on total value decision makers frame outcomes as either a gain or loss based on an arbitrary reference point.

For example framed as a gain if faced with two options:

Option A: Receiving $100,000 cash.

Option B: Playing a game that offers a 50% chance of winning $200,000 cash and a 50% chance of not winning anything.

Most decision makers would select the sure thing Option A (ie. risk aversion for a gain) even though the expected value of each is $100,000 (Option B expected value = $200,000 x 0.5 = $100,000). But if the decision was framed as a loss:

Option C: Paying $100,000 for an unexpected cost or expense.

Option D: Playing a game that offers a 50% chance of paying nothing and a 50% chance of paying $200,000.

If forced to decide individuals would choose Option D (ie. risk seeking for a loss) again even though the both have an expected value of $100,000.

This helps to explain why innovation decision makers will take risks on continuous improvement which they frame as loss but not on R&D projects or export trade options which they frame as a gain. Continuous improvement is seen as Option D whereas R&D projects/export trade options are seen as Option B. Canadian business leaders decisions tend towards Option A and D and avoid Options B and C. The ability to make decisions based on probability tends to be avoided unless decision makers have confidence in the business case numbers.

Individual Biases and Tendencies Influencing Innovation Investments

Participants in the innovation risk assessment process could include: idea generator, designer, engineer, project manager, support staff, marketer, sales, executive sponsor, intermediaries, partners, financiers, and finally the investment decision maker. What are some of the individual biases that can influence any of these participants and possibly cause them to be extremely risk averse:

Overconfidence Bias – Individuals tend to have unwarranted levels of confidence in their judgment, occurrence of positive events, and accuracy of forecasts and then the underestimates of the likelihood of negative events. This bias can cause innovators to identify hidden flaws in their assumptions, approaches, or estimates of cost or schedule. High prevalence of this bias may cause decision makers to discount claims from employees appearing as extreme risk averseness.

Status Quo Bias – The tendency for individuals to prefer to leave things as they are driven by an aversion to loss. (Samuelson & Zeckhauser) This bias can cause decision makers to prefer to continue to use the current process, existing product line or business model even though the competition or market is changing. This bias certainly drives extreme risk averse behaviour.

Availability heuristic – The more prevalent a category is judged to be the easier it is for individuals to bring instances of this category to mind. Recent public failures or events may be cited as possible reason not to proceed even though the connection to proposed innovation investment is not relevant. This tendency could undermine the credibility of innovators in the eyes of decision makers.

Base Rate Fallacy – People who consult their neighbors and friends will discount perfectly valid information and choose instead to rely on a vivid example. Flawed vivid examples could steer decision makers and innovators away from the best course of action or alternative. This tendency could undermine the credibility of innovators in the eyes of decision makers.

Herding Instinct – The tendency for individuals to follow the behaviour and opinions of others.(Belsky & Gilovich) Individuals may propose innovation initiatives that are similar to what competitors are doing rather than focusing on what the customer actually needs and wants. This tendency could cause decision makers to delay decisions if they see their competitors not following the herd which is not necessarily bad but if they only approve investments that follow the herd and the herd is not moving it could be interpreted as extreme risk averse behaviour.

Gambler’s Fallacy – The tendency to treat chance events as though they have a built-in evening-out mechanism even though each event is independently determined. Innovators may continue to experiment hoping for a desired end result rather than learning from the results that may point in a very different direction. This tendency could undermine the credibility of innovators in the eyes of decision makers.

Perseverance Effect – The tendency for people to continue to believe that something is true even though they are offered strong counter evidence that disproves or proves it to be false. (Ross & Lepper) This tendency could also blind innovators from learning from results and decision makers to avoid making investment decisions.

Illusory Correlation – Tendency to see invalid correlations between events.(Hamilton & Gifford) This tendency undermines the soundness of underlying rationale or logic of decisions. This tendency could undermine the credibility of innovators in the eyes of decision makers.

Anchor Bias – Tendency to make estimates on readily available evidence that is meaningless. This tendency could also lead innovators down the wrong path or blind them to possibilities. This tendency could undermine the credibility of innovators in the eyes of decision makers. This tendency could also constrain decision making.

Confirmation Bias – Tendency to use favourable information that supports a position and suppress information that contradicts the position. The underlying assumptions and data must be challenged and verified. This tendency could undermine the credibility of innovators in the eyes of decision makers.

Hindsight Bias – Tendency for individuals to infer a process once the outcome is known but unable to predict outcomes in advance…”I knew it all along”.(Fischhoff) The inability to connect the dots to create new value also constrains taking chances.

Functional Fixedness – Tendency to base a problem solution on familiar methods but hinders the development of strategies for new situations.(Adamson & Taylor) This tendency could lead decision makers to constrain their view of available courses of action.

Selective Recall – The tendency to recall only facts and experiences that support assumptions underpinning a position. This tendency could undermine the credibility of innovators in the eyes of decision makers.

Set Effect – Prior experience can have a negative effect on solving new problems by limiting an individuals view in breadth and generality. In the absence of experience and weak competition firms may avoid innovation investments based on limited prior experience.

Biased Interpretation – Individuals only hear what they want to hear particularly in the presence of ambiguity. This applies to misinformed, uninformed, or narrow thinking in strategy that constrains consideration of innovation before it has a chance to demonstrate its potential.

Curse of Knowledge – Individuals who are privy to information and knowledge that they know others are not continue to act as if the others have the information. Innovators seeking to persuade business leaders need to be aware that decision makers do not have the level of technical understanding.

Escalate Commitment – Tendency direct more resources to a failed course of action. This tendency is particularly prevalent in failed innovation projects where good money is thrown after bad based on continued results that contradict assumptions.

Mental Accounting – The tendency to treat money differently depending its source, where kept, and how the money is spent. Some money is spent freely while other money is highly scrutinized. (Thayer) This is an interesting tendency in decision makers particularly if they apply a very stringent standard on innovation investments but not other expenditures with lower potential return or expenditures susceptible to the status quo bias.

Organizational Biases Influencing Innovation Investments

Complex innovation investments often require teams or groups such as: innovation initiative team, product development team, production team, sales team, leadership team, and board. Organizational biases that can influence these teams or groups during innovation and to be extremely risk averse include:

False Consensus Effect – Most individuals think others agree with them more than the group actually does. This effect could give the impression that decision makers are risk averse but actually have better or different information from the team.

Groupthink – The tendency for group members not on side to fall in line and suppress their objections.(Janis) This tendency could undermine the credibility of team in the eyes of decision makers. In the case of a leadership team if members don’t state their views on potential opportunities then good opportunities may be missed.

Tunnel Vision – The tendency for a group to underestimate the number of feasible options available. Tunnel vision could lead to a course of inaction and risk aversion.

Uneven Participation – The tendency for a small number of strong willed individuals to do all the talking. Similar to groupthink.

Naïve Realism Principle – The tendency for people to expect others to hold views of the world similar to their own. This tendency can blind decision makers to good opportunities.

Dominant Bias On Innovation Investment Risk Aversion

Dominant bias and tendencies behind extreme risk aversion in Canada or in general may be the status quo bias, mental accounting, herding instinct, set effect, and biased interpretation. Certainly a predisposition to not take innovation ideas serious because of perceived credibility issues driven by some of the biases may also to blame.

Methods to address individual and organizational biases and tendencies when making innovation investment decisions will be the subject of future posts.

Millennials View On Innovation

Deloitte recently conducted a survey of millennials (born 1982 or later) and their views on innovation. The survey was conducted in 18 countries including developed, BRIC, and developing countries with a sample population of 4982 people.

The study is interesting as it illustrates how the next generation of leadership differs from the current with respect to innovation, how local societal challenges are seen as drivers for innovation, how governments in some countries are holding back (or unable to fully establish conditions for) positive change, and the millennials view of value of competition in solving social challenges.

Global Millennial View

With respect to innovation the key views of global millennials are:

  • 78% of millennials believe innovation is essential for business growth;
  • 71% view innovations from business directly help to improve society;
  • Innovation is seen as one of the top three purposes of business along with improving society and generating profits;
  • Top six challenges facing society: resource scarcity (#1); inflation (#2); ageing populations (#3); unemployment (#4); social unrest (#5); and climate change (#6);
  • Top four business performance measures beyond financial terms were: employee satisfaction and retention (#1); customer/client satisfaction (#2); contribution to local communities (#3); and innovation (#4);
  • Sectors most in need of innovation were: government (#1); energy & resources (#2); and consumer business (#3);
  • Tomorrow’s innovators will be characterized by: creativity & design (#1); academic/intellectual ability (#2); ability to challenge technical skills (#3); being entrepreneurial (#4); and knowledge of specific ideas and techniques (#5);
  • 66% say innovation key to making the firm an employer of choice with 60% saying they work for an innovative employer;
  • 95% view it to be acceptable to make a profit that benefits society.

Gap in Creating Conditions Fostering Innovation

The largest gaps in the conditions seen as most important to foster innovation as viewed by the global millennials are in order of the gap size (# of most important condition):

  • Encourage & reward idea generation & creativity (tied #4);
  • Provide employees with ‘free time’ that they can dedicate to learning (tied #6);
  • Leadership encourages idea sharing regardless of seniority (#1);
  • Promote openness and the freedom to challenge (#7);
  • Commitment to successfully advancing innovative ideas (tied #4);
  • Strong inspirational leadership (tied #6);
  • Clear vision for the future (#2);
  • Encourage both formal & informal learning (tied #5);
  • Commitment to continual development/improvement internal processes (#3);
  • Commitment to continual development/improvement of products & services (tied #5).

These observations suggest that there is a gap between the priorities of current business leaders and the next generation beyond the typical focus of most business innovation on process and product improvement. Millennials see that their ideas are not being heard and they are not being given the opportunity to develop their own ideas to drive social good. This was also reflected in the views that it was easier to be innovative if you work by yourself than a large business and new businesses are seen as more innovative.

Barriers To Innovation

The top barriers to innovation viewed by global millennials are:

  • Lack of Money / investment / financial pressure (22%);
  • Internal culture / attitudes / stuck in ways / inertia (20%);
  • External economy, government etc bureaucracy / organizational (12%);
  • Poor leadership / management / lack of vision (10%);
  • Skill shortages no incentives / low pay (8%);
  • Poor working practices / lack of teamwork (8%);
  • Time / general pressure (5%);
  • Lack of creativity (2%).

Global millennials commented on the internal barriers, bureaucracy, ‘old school’ attitudes, as well as cultural restrictions on thinking that was holding back firms from innovating.

Solving Societies Top Challenges

The key take away from the survey suggests that global millennials see business as a force for social good, innovation as important to solving the world’s biggest societal challenges but still aligned with profit motive.

Necessity as the mother of invention was clear in the data from BRIC and developing countries. The degree of urgency behind the need for social good was illustrated with a very striking tendency for BRIC or developing countries such as South Africa to see innovation as very urgent whereas developed countries to be below the average on many measures.

The views of the top challenges facing society was also very different depending on the country with inflation being a big concern in Asia and US, ageing population in Japan/China, unemployment in Europe, and social unrest in Germany/Russia. This suggests in a globalized world that the perceived societal needs are very local/regional which has big implications on global and export firm market entry strategy looking to expand into BRIC or developing markets.

Finally global millennials view collaboration as important and business competition as actually hindering the environment for solving the biggest societal challenges.  The collaboration of businesses with one another was seen as the most likely method to succeed in solving societal challenges with collaboration with government, NGO, and universities as less successful but still better than direct business competition.

Canada’s Business Leadership Crisis

In our current age of turbulence and rapid global change the growth challenge for developed economies, including Canada, may be due in large part to a business leadership crisis. For several decades Canadian businesses were protected from the ravages of intense competition previously by the low dollar and now resource revenues. The influence of global competition are increasing as Canada is set to sign several new trade deals. As non-renewable resource revenues wane what will sustain Canada’s prosperity in the long run?

Two Leadership Tendencies

In leadership and strategy studies the propensity of leaders to tend towards either “juice squeezers” or “innovators” poses some interesting perspectives on SME growth in Canada and possibly other economies. The tendency was observed by Gary Hamel in his book Leading the Revolution published in 2000 at the height of the bubble and is worth a relook today.

Hamel identified two leadership tendencies:

Value Squeezers – extract as much profits from the current business model.

Revolutionaries – created new value propositions and businesses.

In comparing the two leadership tendencies Hamel noted that value squeezers will eat away at profits of their existing business model until they finally die whereas revolutionaries look for ways to change their existing business model. Hamel’s central theses is that business leaders should evaluate new business models, challenge and if necessary destroy their old business models to avoid profitably going out of business.

Essentially Hamel was saying that value squeezers focused predominantly on value capture to the extreme while revolutionaries focused predominantly on value creation. In a previous post on delivery / innovation looking at Michael Raynor and Mumtaz Ahmed recent article in Harvard Business Review describing Three Rules For Making a Company Truly Great it is perhaps more important to be able to balance both tendencies in the long run or avoid always defaulting to the extreme of juice squeezing.

Leadership Tendency Holding Back Growth

When interpreting Deloitte’s observations that Canadian SME growth tends to slow after the first five years of rapid growth combined with the modest number of Canadian global leaders and the mystery of vanishing medium firms in Canada one might conclude that Canada may have too many juice squeezers and not enough innovators. Indeed the propensity for business leaders to not adopt innovation as a strategy was thoroughly explored by the Council of Canadian Academies in their 2009 report Innovation and Business Strategy: Why Canada Falls Short.

The juice squeezer likely view their leadership tendency is just fine for a market that has changed little over the last several decades and for now is not directly threatened by globalization or major change. Perhaps their market is protected or they have found a nice niche that supports their lifestyle. Risk averse, preference for lifestyle support, and comfortable that their business model is good enough for their existing geographical market and customers are juice squeezer behaviours. If they take any strategic step to grow it is to use their profits in excess of their own or their company’s needs to grow through acquisition. The acquisition will likely be of a similarly positioned firm in the same market.  By acquiring an existing firm risk is low but no real new value has been created in the process. In all likelihood value has been destroyed from the transaction cost and cultural mismatch during integration. A juice squeezer would certainly not see the need to invest in R&D, collaborate with research organizations, diversify their markets, or export.

In the mind of the juice squeezer they likely rationalize that their leadership style got them this far so why change. The problem is that the juice squeezer leadership behaviours may be harming the economy in the long run since the world has fundamentally changed. With all the drive for change to squeeze more profits out the existing businesses in the name of efficiencies have business leaders forgot to look in the mirror and ask themselves if they need to change?

Engaged, purpose driven employees have a good sense whether they see their leaders are juice squeezers or innovators. The question is are boards challenging business leadership or are business leaders themselves self reflecting whether their own leadership tendency is appropriate for today’s turbulent markets?

Role of Demographics

Canada’s and the developed world changing demographics may be our opportunity for leadership change. The current business leadership tendency towards juice squeezing should be seen as “old school’ or applicable for the pre-financial crisis world but not for the post-structural break reality of a global economy where first world nations economic superiority no longer stands. As baby boomers retire with their lifestyle wealth the next generation of Canadian SME business leaders should look towards innovation leadership, purpose driven value creation, and adopting innovation as a strategy.

Leading For Growth Through Innovative

How can a new generation of Canadian business leaders adopt a new set of behaviours to drive growth going forward? How can a new generation of Canadian business leaders create new sources of value rather than shuffling around existing aging value sources? Hamel’s book provides a good working framework.

Hamel proposed some rules for enabling a more innovative organization:

  1. Set unreasonable expectations
  2. Maintain an elastic business definition (or business model)
  3. Create a cause, not a business
  4. Listen to revolutionary voices
  5. Create an open market for ideas
  6. Create an open market for capital
  7. Create an open market for talent
  8. Encourage low-risk experiments
  9. Grow by cellular division
  10. Share the wealth

Many of these behaviours have matured in the decade since the book was first published. Elastic business definitions executed through business model canvas and business model pivots. Creating a cause is central to social innovation. Open innovation has become main stream through crown sourcing. Low risk experiments through creaction, little bets, and the learn-build-measure cycle.

In reflecting on this post if you hope to be in a leadership role in the coming years what kind of leader do you want to be? Canada’s future prosperity depends on it.

Facing and Overcoming Innovation Uncertainty and Risk

Business growth requires leaders to identify opportunities, evaluate their potential and risks, decide amongst the most promising, and executing for results. Growth strategy options include: organic growth, growth through acquisition, or growth through alliances.  Growth can be achieved through product / market choice (concentrated, vertical/horizontal, diversification), white space, or incremental/substantial/breakthrough innovation.

Uncertainty and risk associated with innovation opportunities are often cited as barriers to growth. The inability to overcome uncertainty and risk when innovating was cited as the leading reason for slow Canadian SME growth as confirmed by the 2009 SIBS study and recently by Deloitte.

The 2009 SIBS study reported uncertainty and risk as the largest obstacle (47% of firms) to innovation regardless of the type of firm. Steps taken to overcome uncertainty and risk as an obstacle were also reported to be one of the least effective (38% of firms reporting uncertainty as an obstacle).

The Deloitte study reported that “Canadian business leaders were substantially more risk averse than U.S. leaders, and more reliant on government assistance to pursue new projects” and that Canadian firms “seem unable to deal with these factors successfully” moreover “as Canadian firms mature, they become less likely to engage in the kind of activities that contribute to rapid growth”. The Deloitte study suggests that to deal with risk “firms have the power to mitigate these obstacles by hedging and compensation tactics”. The study also reported that low R&D spending, poor export intensity, lack of market diversification, low access to market diversification, and attitudinal preferences were also major inhibitors to growth.

Innovation though is a non-linear process where the value of success can be much higher than the cost of failure. Global markets are increasingly uncertain.  What approaches beyond hedging and compensation tactics can be used to deal with uncertainty to improve Canadian business leaders confidence?


An interesting view of how to grow in the face of uncertainty comes from Max McKeown who wrote Adaptability: The Art of Winning in an Age of Uncertainty. In this book the author identifies a number of rules for winning in the face of uncertainty.  Chief among these applicable to Canada is that stability is a dangerous illusion. He defines failure as the failure to adapt and success as successful adaptation to cope or win – defining degrees of adaptation outcomes being collapse, survival, thriving, and transcendence.

The author observes that there are three steps to adaptability:

  1. Recognizing The Need To Adapt – The ability to feel or know something is wrong, timeframe of change depends on the situation and can be long or extremely fast, and some find out too late by missing signals or are simply complacent.
  2. Understand The Adaptation Required – Observing that there is often no agreement on adaption requires, culture/rules/tradition can be barriers, learn what works from failure, imagination is needed to see alternatives.
  3. Do What Is Necessary To Adapt – Sometimes adaption must be provoked, strong action to overcome barriers, need to focus on changing the nature of the game, and build influence to make changes.

The rules for winning in the face of uncertainty organized by the three stages as suggested by the author are:

Recognize The Need to Adapt

  • Play your own game – If losing find a way to change the game – no one way to win
  • All failure is a failure to adapt – didn’t recognize it, didn’t understand what adaption required, did not do what was necessary to adapt.
  • Embrace unacceptable wisdom – speaking opposite to the prevailing wisdom creates opportunities.
  • Know when to break the rules – rules contain knowledge & experience, rules also contain prejudice or mistaken beliefs, rules may no longer be applicable.
  • Stability is a dangerous illusion.
  • Stupid survives until smart succeeds – ‘we were wrong’, biases to remain on course of action.

Understand Necessary Adaption

  • Learning fast is better than failing fast.
  • Plan B matters most – adaptability doesn’t kick in automatically.
  • Free radicals – radicals influence the group – stir the pot – counter complacency.
  • Think better together – collective support important.
  • Get a strong partner – diverse skills and talents increases adaption effectiveness.

Adapt as Necessary

  • Never Grow up – organizations get old, grow up, and lose edginess – remain curiosity driven.
  • Hierarchy is fossil fuel – Locks people in boxes, resists learning, and institutionalizes self-interested behaviours.
  • Keep the Ball – reduce the game down to its fundamental components that captures the most important features of the system to improve – compete outside the game.
  • Swerve and swarm – Combining swerving, avoiding dominance of the obvious idea, and swarming, to bring mass participation to finding non-obvious answers is powerful.
  • Get Ambition on – the future gives direction and unlimited energy to change – ambition is a way of seeing the future – ambition gets us started.
  • Always the beginning – Advantage from adapting first, winners acquire resources and knowledge.

Creaction Method

The creaction (short for creative action) method to move forward in the face of uncertainty was proposed by Leonard Schlesinger, Charles Kiefer, and Paul Brown in Just Start: Take Action, Embrace Uncertainty, and Create The Future. These authors observed that most business leaders have worked in a world where the world was predictable and that the future could be forecasted, plans made, resources gathered, and then execute the plan to make it happen.  The core assumptions being that the future will behave like the past so plans can extrapolate current reality moving forward. The authors suggest that the world that is changing fast will become increasingly unpredictable so business leaders need a new way of thinking to drive business growth.

Borrowing from entrepreneurial behaviours, the authors propose the creaction method to succeed when markets are unpredictable. The creaction method is:

  • Act (with a modest goal as a guide);
  • Learn (from the action); and
  • Build (off learning) and then act again.

Creaction starts with a desire to achieve a goal with a purpose no necessarily a passion. The authors suggest acting quickly with the resources have at hand and never more than you can afford to lose if things don’t work out defined as an acceptable loss. A small bet rather than betting the firm. When considering acceptable loss the authors suggest assets at risk are: money, time, professional reputation, personal reputation, and missed opportunities and bounding the investment so that if the option fails it fails cheaply. Enlist the support of other like minded people who share interest in the goal and purpose. When learning from the results of the small step the authors note that “creation is all about exploiting the contingencies and leveraging the uncertainty by treating unexpected events as an opportunity….treating surprises as a gift….running headlong into a problem and then solving it can give you a barrier to the competition”. The book provides useful implementation advice.

Implications For Canada

Max McKeown’s observations on adaptability are particularly poignant for Canada as many SMEs that have stopped growing may have not recognized the need to adapt given the predominance of the resource industries in the overall economy. The implication being that stability is not only a dangerous illusion but that the voices that oppose the prevailing wisdom are potentially being ignored. SME business leaders should stress test their business assumptions and consider potential avenues for change and adaptation. The creaction method provides a means for SME business leaders to take small steps, learn, and adapt to develop growth strategy. Future posts will explore other approaches to overcome risk and uncertainty.

Effective Technical Risk Assessments In New Product Development

Technical risks are a common cause of new product development project cost and schedule overruns. Effective technical risk assessment is therefore on the mind of investment decision makers and all new product development project managers.

Effective Technical Risk Assessment

To be effective, technical risk assessment must be performed up front so that investment decision makers can clearly weight the risk/reward of continuing while enabling product developers to plan the realistic scope of effort along with tackling the biggest technical mitigation efforts immediately.

A technical risk assessment is typically based on lessons learned from previous new product development projects, experience of team members or advisors, and historical data from similar products developed either by the company or competitors. A project pre-mortem  is an effective tactic to identify ‘project killer’ issues up-front to ensure project team members and stakeholders are not feeling pressured to express their views.

Technical risk assessments should cover the feasibility of the product including building blocks (particularly mix of existing/new), how the product building blocks integrate amongst themselves, how the product integrates with the operating environment, ability to manufacture the product cost effectively, and feasibility of new manufacturing technologies.

A central theme in any technical risk assessment therefore is that new product development outcomes depend on the maturity of the underlying hardware, software, and integrated system. A key question facing new product developers then is: How can technology maturity be measured to determine the level of technical risk? 

Technology Maturity Assessment

Good technical risk assessments depend on an effective technology maturity assessment.  The percentage of unproven technology and level of integration in the new product determines the degree of technical risk that can impact project cost, schedule, and quality.

The technology readiness level scale provides a means to assess the maturity of the subsystem building blocks in a new system. First developed by NASA as illustrated below the Technology Readiness Level scale uses nine levels as described.


The NASA TRL scale illustrated is for products used in space but the scale can be easily adapted for any operating environments for which the new product is intended.  The assessment scale is also used by the US DoD and has been adopted by the Canadian government for use in the Canadian Innovation Commercialization Program.

Product developers should deconstruct their product building blocks and assess the technology maturity level of the individual building blocks using the technology readiness levels.  Product developers need to assess whether technology proposed is ready to be used in their project. Typically subsystems should not be used unless demonstrated at TRL 7 or higher. Subsystems with TRL below 7 are really research projects presenting too much uncertainty for accurate customer schedule commitments. R&D projects can use the TRL scale to measure progress towards commercialization. Product portfolio strategies and roadmaps need to plan how new technology subsystem R&D projects will be coordinated, prioritized, and sequenced with sufficient time to reach TRL 7.

Integrated System Maturity Assessments

Product developers should also assess the technology maturity level of the integrated system. Integration problems can be as serious as individual subsystem immaturity issues if not more when the scope of the new product/project is large and often go unrecognized until well into new product development project.

The level of complexity of the integrated system drives the scope of the system level maturity assessment. The TRL scale is not very effective as system complexity increases. It is also important to recognize that complex integration can be present in both new systems (new systems with existing and new subsystems) where we would expect them but also legacy system upgrading (old systems being upgraded with new subsystems).  Limitations with the technology readiness level scale reported for major/complex projects include:

  • Emphasis on subsystems;
  • Nonlinearity of the scale particularly the large leap from TRL 6 to 7;
  • Not accounting for system integration and manufacturing; and
  • Does not indicate the degree of risk of moving up the scale.

The Risk Identification, Integration, and Ilities (RI3) approach has been proposed to  augment the technology readiness level system for manufacturing readiness and systems engineering ‘ilities’ . Another approach to assess the system level readiness is the UK MoD System Readiness Level method. The advancement degree of difficulty (AD2) method has been proposed to address the degree of risk of moving up the scale.  The cost effectiveness of applying these approaches depend on the complexity of the integrated system and size of the new product development project.

Product developers need to apply a disciplined technology maturity assessment early in any new product development project to proactively mitigate technical risks. Investment decision makers should consider impartial technical feasibility assessments based on subsystem and system technology readiness levels described in this post to remove bias from technology maturity assessments.

Set Based Design For Lean Engineering

Set based design (SBD) or set based concurrent engineering (SBCE) as it is also known is a powerful lean engineering method. Firms that design complex systems should consider this approach to deliver better designs more efficiently. A caution though that this is an advanced lean engineering method so is not appropriate for new design organizations.

What is Set Based Design

Set based design builds on concurrent engineering principles (multifunctional, co-located team design) by establishing a design space for design optimization to meet a challenging set of requirements. Set based design involves exploring many design alternatives up-front to allow for trade-offs particularly important for integrated systems with competing requirements.

Set based design improves on ‘point design’ with its’ many shortfalls – fixation on first design selected, time delay before feedback, and locked in cost too early in the design process. The differences between point design and set based design can be best understood visually.

Set Based Design

Set-Based Design: A Decision Theoretic Perspective, Paredis, etal, GIT

A key principle underlying set based design involves delaying design decision later in the design process to achieve optimal trade-offs by eliminating inferior or sub-optimal design alternatives. Although counter intuitive while the design decisions are delayed set based design involves front end loading the design stages of the project to develop the design alternatives. The front end loading facilitates early learning, early identification of risks, and early mitigation of risks. A key success factor is the discipline to identify all possible design alternatives up-front without allowing the design to move on with a favourite alternative – creativity, innovation, and practicality under pin this step.

In summary, the main advantages of set based design include:

  • Supporting concurrent engineering which eliminates waste
  • Delays design decisions until later in design process to avoid locking in costs early before important learning can occur
  • Facilitates partitioning of complex designs by functional specialist groups
  • Supports design flexibility particularly with respect to modularization and reuse

History and Applications

Set based design was originally developed by Toyota within the Toyota Production System but not as well advertised as lean manufacturing.  Set based design has been studied since the 1990s but is mainly applied in OEMs. Adopters have mainly begun their lean engineering journey and are exploring advanced improvement techniques. Set based design has been applied in automotive, ship building, EPC, and aerospace.

Moving forward the main challenge to implementation is establishing practical procedures. Most firms establish unique digital or hybrid manual/digital design spaces to handle product design of varying complexity. We are at the stage where a high degree of customization is required to adapt the principles to new product development.