Engineering-to-Business Alignment For Profitability

The business world and engineering world speak different languages and operate at different tempos with a shared imperative to meet the needs of customers.  Businesses that leverage technology innovation for competitive advantage need to find their ‘E2B Alignment Rosetta Stone‘ for the best results in their business context. How can the engineering leader facilitate effective alignment between engineering and the business?

Why is Engineering Work Different?

The business world operates according to the laws of social science, fraught with ‘short termism’, and the pressure to constantly perform, compete, satisfy customer needs while commercially relevant engineering work requires more time and functions in the presence of volatility, uncertainty, complexity, and ambiguity (VUCA) bounded by the laws of science. Engineering work involves solving difficult problems that arise in the business and the market place, creating new products to create new value for the firms, finding new ways to meet regulations to remain compliant and possibly creating competitive advantage, and optimizing design performance to achieve cost and quality. The answer to engineering problems is not known in advance and the time that a solution is ready is not known to any degree of certainty. Some engineering problems are simple while others are wicked and ugly problems. Engineering problems are almost always complex. While others may be unsolvable within the current state-of-the-art or beyond laws of physics. Novel solutions require creativity, experimentation, and learning that are difficult to schedule.  How can engineering leaders bridge these incongruent worlds?

 Common Goal – Increasing Profits

The answer rests in remembering the common goal.  The common goal of both business and engineering is to increase the profits of the firm.  Easily stated but accounting is the day-to-day language of business which enables them to clearly see how to increase profits through business actions with well defined measurements for feedback.  The engineering world does not speak accounting nor is it often clear how engineering decisions can increase profits.  Engineers ought to speak the language of accounting better, but practically speaking their education and professional development is often all consuming in the increasingly complex engineering world.  Apart from every engineer taking an MBA or second degree in accounting how can engineering leaders help their staff to understand how their actions increase profits? Engineering leaders need an E2B alignment Rosetta Stone to translate engineering decisions into profit impact.

E2B Alignment Rosetta Stone – Engineering Profit Decision Tool

Fortunately in all cases an engineering profit decision tool can be created to help engineers make sound business decisions and trade-offs that increase profits in terms they can understand. The problem is that most businesses don’t take the time in this fast paced world to develop one.

The engineering profit decision tool can be developed using the approach illustrated below. The resulting business model can then be the E2B Alignment Rosetta Stone to help engineers to translate engineering actions into profits.

Engineering Decision Rules

Engineering leaders need to facilitate the development of the engineering profit decision tool with help from the other business functions (marketing, finance, operations, and project management). The baseline profit/cost model is the P&L statement for the project, new product development, service line, etc. delivered by engineering.  Like any model key assumptions need to be captured. A sensitivity analysis is then performed on key cost drivers such as: time; unit cost; engineering operating expense; value; performance; and risk as appropriate for the context of the business. The sensitivity analysis can then be used to define profit impact parameters.  These profit impact parameters can then be stated in terms of engineering decision rules (that are understood by engineers).  As engineers go about their work key decisions arise that require trade-offs amongst competing alternative courses of action.  The engineering decision rules can help them to compare alternatives and decision on the best alternative that maximizes the profit to the company. Over time the results of the decisions become evident in the business results enabling feedback adjustments to the model.

The key to success is taking the time to build the first model, trial it on a pilot project, build buy-in, train the broader engineering team, and then refine and expand its use. This post has provided the high level picture and there is clearly more effort to perform each step in the process suitable for each firm.  Contact Alopex Management Consulting if you are interested in developing an engineering profit decision tool.

Top 6 Engineering Leadership Priorities

Engineering leaders need to devote time to 6 priorities for a vibrant and sustainable engineering capability that supports the strategic ambition of the business. Engineering leaders are often so drawn into the day-to-day demands of the operation that these 6 priorities are ignored to the detriment of the business. There are no absolute right or wrong ways to meet the 6 priorities but rather each must be decided as a collective package by the engineering leadership team in the strategic context of the business. The senior engineering executive should then integrate these decisions with those of the overall business at the senior management level and negotiate and adjust as necessary bringing back the rationale for any modifications to the engineering leadership team.


Engineering staff need to understand the purpose of the business in order to orient their efforts to support the success of the business. Engineering leaders need to clarify and communicate the purpose of the business, the purpose of engineering in the context of the business, and how individual and collective team efforts achieve the purpose.  The purpose is often expressed in the vision or expressed as the winning aspiration of the firm, as for example described by A.G. Lafley and Roger Martin in Playing to Win.

Inspiration comes from a deep connection between the purpose and meaning in engineering work. Engineering leaders need to help their staff to relate the meaning in engineering work to the winning aspirations of the firm to maximize engagement and productivity. Engineering leaders should work with the engineering supervisory team to assimilate how meaning in engineering work can be leveraged through recruitment, job assignment, and performance management.


Engineering leaders need to align the engineering effort with the strategic choices of  the business. Continuing on from the purpose, Lafley & Martin have defined an integrated cascade of strategic choices aligning from the winning aspiration of the firm to: where the firm will compete; how will the firm win in terms of value proposition and competitive advantage; what capabilities are required to win; and what management systems are required to support these choices. In the context of the integrated cascade of strategic choices engineering may be central to a firm’s strategic ambition or play a supporting role. Engineering may be heavily integrated with other business functions or stand-alone. Engineering leaders need to deeply consider how engineering is aligned and how it meshes with the firm’s strategic choices.

Labovitz and Rosansky provide an alignment framework for engineering leaders to operationalize the cascade of strategic choices in their book Rapid Realignment. Labovitz and Rosansky’s framework separates out vertical alignment and horizontal alignment to structure actions.

  1. Vertical Alignment – The vertical alignment seeks to align employees to the strategic choices of the firm by defining critical success factors, goals, focus areas that can be owned by each business function, such as engineering, and the precise activities and tactics required to deliver the critical success factors. The role of engineering leaders in the strategic alignment exercise is to contribute to the definition of critical success factors that support the strategic choices.  Engineering leaders then need to own the creation of the action plans to deliver the critical success factors.
  2. Horizontal Alignment – The horizontal alignment seeks to align value creating processes with the needs of the customer.  Value chains are clarified for both internal and external customers.  The role of engineering leaders are to understand what the customer wants and how they prefer to be served and establish process to meet and try to exceed customer requirements.


Engineering leaders need to foster and support a culture in engineering that aligns with the strategic choices of the business and maximizes the outcome required from engineering. Culture often emerges in a business based on its history of shared experiences and is reflected in the sum of the firm’s shared values, beliefs, and norms of behaviour.  Culture can be business wide with local differences in functions, business units, and locations.  Culture is rarely homogenous as firm’s grow. Major strategic changes can bring about large dissonance between the existing and desired culture.

The competing values framework is useful for engineering leaders to understand the current culture in engineering and to identify change emphasis to align with the strategic choices of the business. The competing values framework maps organization culture in two dimensions: vertically between stability & control and flexibility & discretion; and horizontally between external focus & differentiation and internal focus & integration.  The competing values framework defines four cultures coinciding with the map quadrants:

  1. Clan Culture (Collaboration or Human Resources) – A culture high on flexibility and discretion but internally focussed. Cultural descriptors are: participation and open debate; employee concerns and ideas; human relations, teamwork, and cohesion; and morale.
  2. Adhocracy (Create or Open Systems) – A culture high on flexibility and discretion but more external focussed. Cultural descriptors are: innovation & change; creative problem solving; decentralization’ and new ideas.
  3. Hierarchy (Control or Internal Process) – A culture high on stability & control but internally focussed. Cultural descriptors are: predictable outcomes; stability and continuity; order; and dependability and reliability.
  4. Market (Compete or rational goal) – A culture that is high on stability and control but externally focussed.  Cultural descriptors are: outcome of excellence & quality; getting the job done; goal achievement; and doing one’s best.

Organizations often exhibit characteristics of each of these four culture types but typically emphasize one type for the strategic choices of the firm. Leadership often relates to the right side (direction, inspiration, change, growth, competitiveness) of the map while management relates to the left side (planning, budgeting, controlling). Firms in stable markets with little change often become internally focussed and stagnate in clan and hierarchy dominant cultures. Firms in rapidly changing markets must be externally focussed with emphasis on adhocracy and market dominant cultures.

Engineering leaders need to look deeper into the culture of their organization and reflect on these observations. Engineering leaders need to ask whether their culture is appropriate for the expectations of the business and what tangible actions are needed to bring it into line. Most actions will involve leading by example. An external change, or change in leadership, may bring about a subtle shift in culture. Engineering leaders need to facilitate discussions in engineering to help employees understand why things need to change or why their shared values, beliefs, and norms of behaviour may be incongruent with the strategic choices made by the firm.

Value Proposition

Engineering leaders need to understand how engineering capabilities create value for customers to achieve horizontal alignment as previously described. Engineering may deliver value directly to an external customer or to an internal customer before value is delivered to the external customer.  Engineering leaders need to clarify how engineering supports the value proposition of the firm – or how engineering supports how the firm will win. The two well known fundamental ways to win, based on Porter’s Competitive Strategy, are: cost leadership and differentiation.

  1. Engineering Cost Leadership – Engineering delivered cheaper than the competition enabling the business to underprice the competition or reinvest the margin differential to support other aspects of the strategic choices of the firm.
  2. Engineering Differentiation – Engineering providing a source of differentiation for the business measured in terms of solutions compared with competition that: are faster, cheaper, safer, do more, do things better, do things that no one else can do, etc.

Engineering organizations may perform more than one value added activity (product design, consulting advice, sustaining engineering, manufacturing engineering, safety compliance, detailed drawings, etc.)  so it is up to the engineering leadership to identify them and decide how to organize effort to deliver them. Engineering leaders should avoid multi-tasking engineers with activities that may support separate ways to win. The nature of each way of winning can be very different.  As Lafley and Martin emphasize:

  1. Low Cost Strategies – Based on systemic understanding of costs and cost drivers, relentless reduction of costs, sacrifice of non-conforming customers, and commitment to standardization.
  2. Differentiation Strategies – Based on deep and holistic understanding of customers, intensive brand building, jealous guarding of customers, and commitment to innovation.

Engineering leaders therefore need to think deeply of how engineering is expected to contribute to the business aspirations profitability, growth, and competitiveness. Culture also supports these strategies where low cost strategies demand more internally focussed culture such as Hierarchy and Clan, whereas differentiation strategies demand more externally focussed culture such as Market and Adhocracy. The right culture needs to match the intended way to win. Complex engineering organizations may need sub-organizations with different dominant cultures.

External Change and Innovation

Engineering leaders need to be mindful how the firm is positioned in the external environment and how the external environment is changing. Engineering leaders need to be attuned to subtle shifts and craft possible solutions to create new value for the firm through innovation.  Engineering leaders should seek opportunities for their employees to spend time with customer’s and understand their issues and needs.  Changes sensed in the external environment become the ‘Why’ in any change initiative.  Firms with hierarchy and clan cultures which are inherently more internally focussed run the risk of missing subtle shifts in the market or customer preference.

The need for change can fall anywhere along a spectrum from small to disruptive. Responses to big external changes can only be actioned through a fundamental revisit of the strategic choices of the firm. Engineering cannot act unilaterally in this case but engineering can often act as the bell weather or early alarm for the business. Engineering can also help the firm to connect the dots in the presence of market ambiguity. Firms in slow changing markets may only need to make incremental adjustments but these markets are becoming rarer in a rapidly changing world.

In almost all cases innovation is the main response to external change. Engineering leaders need to decide the degree of need for innovation in the context of their industry competitive intensity and rate of industry change then foster the required environment for innovation to respond to external change. Innovation strategy should always be devised at the company level but engineering capabilities often play a leading role in executing innovation strategy. Investment is almost always required for innovation.   Categories of innovation strategy are: do nothing; adapt/adopt; incremental; transformational; and breakthrough.

Engineering leaders need to select and propose the appropriate innovation strategy in the context of industry competitive intensity and rate of industry change. Ignoring the do nothing innovation strategy, most engineering organizations implement some form of innovation strategy for example:

  1. Adapt / Adopt Innovation Strategy – Engineering leadership may acquire new CAD, CAE, analysis, or tools to gain advantage in saving time or improve performance. Although not recognized as such capital expenditures on engineering almost always brings new innovative business processes.
  2. Incremental Innovation Strategy – Engineering leadership may implement process improvement, product upgrades, or add-ons that provide small gains in time savings, new value creation, etc.
  3. Transformational Innovation Strategy – Engineering leadership may propose a step-change to a product or process that requires investment but the return for the firm can’t be ignored.
  4. Breakthrough Innovation Strategy – Although mainly the realm of new technology start-ups engineering leadership may propose a investment project that could create a new-to-the-world market or disruption to the an existing market.

Engineering leaders then need to establish an environment suitable for the selected innovation strategy. The environment not only needs to support the generation of ideas but one that implements ideas and measures outcomes. A culture of learning and experimentation is critical to an effective environment for innovation. Firms in rapidly changing markets therefore need to move to a Market or Adhocracy culture. Sticking with a Hierarchy or Clan culture is a recipe for disaster in rapidly changing markets.


Engineering leaders need to actively manage the balance between the short term operational demands of the business and long term sustainability of the firm’s value proposition. This is the balance between delivery and innovation.  The balance between tactical and strategic.  The balance between today and tomorrow. The balance between exploit and explore. The balance between leadership and management. Engineering leaders need to make time for long term, innovation, strategic, and tomorrow in spite of the pressures of the day-to-day. As John Kotter said ‘over managed, under led organizations are increasingly vulnerable in a fast moving world’. If engineering leaders can’t make the time to focus on moving the engineering capability in response to changes in the external environment and changing customer needs then they risk becoming irrelevant or exposed to the competition to exploit.

Leadership vs Management

How do these engineering leadership 6 priorities relate to engineering management. As Kotter explains leadership is about ‘taking the firm into the right future’, ‘finding opportunity and exploiting at an accelerated pace’, ‘defining purpose for meaning and buy-in’, ‘creating the right culture and environment to thrive’, and ‘producing useful change to make the future happen’. Kotter goes onto to explain that management is about ‘making complex organizations predictable, reliable, and efficient’, ‘executing a set of well known processes’, and ‘delivering products and services as promised consistently to quality, budget, and schedule’. As Drucker said ‘ Leadership is doing the right thing, while management is doing it right’. This also tells us that too much emphasis on management can leave the firm exposed and engineering leadership has a significant obligation to ensure that the right balance is struck between short-term and long-term view.

Engineering plays a critical role in new value creation, profitability, growth, and competitiveness for the business. The entire package of the 6 priorities need to hang together and fit the strategic intent of the firm and then adjust as the external market shifts. Together these 6 priorities provide a basis for discussion, alternative selection, and decision making for a vibrant and sustainable engineering capability that supports the strategic ambition of the business.

Engineering Productivity

Engineering leaders interested in improving their profitability need to understand how the Theory of Constraints can improve engineering productivity and perhaps most importantly under what business conditions. This post reviews the evolution of throughput methodologies from where they were first applied in the manufacturing environment to newer approaches evolving for engineering, new product development, and R&D where the business goals are improved profitability and new value creation for growth and competitiveness.

Theory of Constraints

Eli Goldratt’s book The Goal (1984) helped a generation of manufacturers understand the operational principles underlying the Toyota Production System and Lean Manufacturing.  Goldratt defined the goal as improved profits and clarified the operational rules for running a plant to be in order of priority throughput, inventory, and operational expense as opposed to pure cost cutting that lead to localized optimums and poor profitability results. He explained how the Theory of Constraints (TOCs) when applied through these operational rules can improve the profitability of a manufacturing operation with stable input demand. The TOC was first applied to manufacturing operations that can be characterized as a repeatable network of dependent events with processes that are subject to statistical fluctuations.  The TOC focusses on system constraints to improve throughput, inventory, and operational expenses in the total production system.  The key conditions that enable the TOC to achieve results in manufacturing are stable demand, moderate to high volumerepeatable processes, and a small range of products.

Unstable Production Environments

Eli Goldratt’s paper Standing on the Shoulders of Giants (published with The Goal) went on to clarify how certain production environments and conditions can become unstable leading to marginal improvement gains from applying TOC.   In this paper Goldratt described the Hitachi Tool Engineering case where the firm had limited success with lean manufacturing because of their unstable production environment conditions.

The three general conditions Goldratt identified that lead to unstable production environments are:

  1. Unstable Demand Per Product
  2. Unstable Overall Load On The Entire Production System
  3. Short Product Life

The first two unstable production environments fall within the means of a manufacturing company to manage because the production system can still be characterized as a network of dependent events with processes that are subject to statistical fluctuations.  Full productivity gains are not achieved because of how the production system throughput reacts to the unstable input demand due to dynamic mix of products, too many different products, or how dynamically the input demand of different types of products results in unstable overall load on the system. Goldratt explains how a time-based application of supply chain approach of TOC in a method called Drum-Buffer-Rope system can achieve improved performance for the first two conditions. Goldratt observed that low touch time production environments (Touch Time <<< Lead Time) provide enough margin to still exploit TOC benefits.

The third unstable production environment, short product life, emerged in the 1980s from the increased pace of technological change on manufacturing operations. The turn time (lead time) performance of engineering, product development, and R&D became a factor for product companies bringing attention to knowledge worker productivity.  Goldratt observed that product development systems do not exhibit processes that are ‘network of dependent events with processes that are subject to statistical fluctuations’. Each new product develop effort tend to have a unique network of dependent events with high variability which is consistent with a a project environment. Goldratt also observed that the project environments also exhibits time compression where touch time approaches lead time (lead time ~ 2 to 3 times touch time) of the project which degrades project environment throughput.

Unstable Project Environments

To solve the unstable project environment problem Eli Goldratt went on to develop the Critical Chain method in the 1990s.  The Critical Chain method adapts the TOC to unstable project environments with a particular emphasis on engineering development projects. In much the same format as The Goal his book Critical Chain (1997) explains how the Critical Chain method achieves improved project performance over Critical Path methods. The goal of Critical Chain method is to improve the flow (throughput) in project environments for stable and unstable project demand.  The mental jump from manufacturing production environments to project environments is helped when one considers that most project environments are multi-project environments.  Throughput in a project environment is understood to be the flow of projects (and their activities) of various degree of: sizes, durations, complexity, uncertainty and novelty.

The Critical Chain method seeks to maximize project environment throughput by managing feeding buffers and capacity buffers within the project and drum buffers and capacity buffers between projects.  The Critical Chain methods use of buffers (time & resource) to improve productivity by reducing Work In Process (Design in Process), manage bottleneck resources, not allowing multi-tasking of resources, staggering projects along the constraints, prioritizing projects, and resolve resource conflicts on the system level.

An interesting aspect of Goldratt’s Critical Chain method was how to consider behavioural issues in multi-project engineering environments. The Critical Chain method addresses:

  1. Tendency for engineers to ‘pad their estimates’ to give local safety margins that degrade the efficiency of the project environment by use lumped buffers (rather than activity-by-activity risk buffers) and focussing less on individual activity time performance.
  2. Overcome the tendency to think locally (within the project or a work area) by encouraging global thinking by avoiding multitasking.
  3. Manage ‘student syndrome’, the tendency for humans with time buffers to start their tasks later and waste safety margins.
  4. Manage ‘Parkinson’s law’, the tendency not to finish tasks ahead of time even they have a chance to by removing activity padding.
  5. Minimize the individual project owners pressure to execute first (local optimization at the expense of the global performance) by adopting a priority system.

An excellent review of the Critical Chain method can be found in a 2005 paper by Lechler, Ronan, and Stohr with some useful simplifications that make the method more practical.

Product Development Flow

Donald Reinertsen developed a parallel set of work to Goldratt that explored and clarified much of the underlying principles of lean product development from the perspective of achieving faster time-to-market in the project production environment. Reinertsen’s books Developing Products in Half The Time (1991) co-authored with Preston Smith, Managing the Design Factory (1997), and The Principles of Product Development Flow (2009) explored an economic model for design, queues in product development work, management systems, managing risk, lean engineering principles, and performance metrics more appropriate for the paradigm shift from the traditional utilization based management paradigm to a throughput management paradigm for engineering, product development, and R&D.

Reinertsen also defines Design in Process (DIP) in the project production environment since inventory is measured in terms of information in the knowledge work space. The abstract nature of information inventory and visualizing how it flows through a knowledge based work environment has probably been the single largest factor holding back the broader adoption of lean product development.

Reinertsen clarifies how the project production environment differs from the manufacturing production environment with repeatable network of dependent events with processes that are subject to statistical fluctuations to one with high variability (uncertainty, learning, experimentation), non-repetitive (every project network is different, sometimes completely), and non-homogeneous task durations (most tasks slightly different each time). Reinertsen’s most recent book Principles of Product Development Flow in particular explores the themes of cadence, synchronization, flow control, WIP constraints, batch size, exploiting variability, queue size, fast feedback, and decentralized control to maximized throughput.  Although these works provide a vast array of tools it is difficult to see the big picture framework suitable for practical implementation.

Lean Product Development

Ronald Mascitelli, Timothy Schipper and Mark Swets went onto develop fully integrated lean product development frameworks that operationalized the principles for engineering leaders who are responsible for new product development.  Most importantly they describe how to fully implement a multi-project production environment based on the all the preceding methods but appropriate for actual business environment.

Ronald Mascitelli’s Mastering Lean Product Development (2011) is perhaps the best integrated framework for the engineering, product development, and R&D leader to establish a throughput managed multi-project production environment. Mascitelli’s framework is an event-driven process incorporating practical lean methods to achieve the goals of improved profitability and new value creation for growth and competitiveness.

Timothy Schipper and Mark Swets published Innovative Lean Development (2010) to describe an equally powerful integrated framework that leverages fast learning cycles and rapid prototyping for project production environments with high uncertainty.

Agile Scrum

In the digital information age as products have become software driven and in many cases entirely software based the agile scrum methodologies have operationalized software product development emerging in early 2000s. The abstract nature of software development defied reliable engineering management methodologies before the emergence of agile scrum. With agile scrum software productivity is more manageable, efficient, and effective. Software driven products require the integration of the agile scrum methodologies within the project production environment framework just described.

The Lean Start-Up

Up to this point in the post we have looked at how established companies with existing demand can exploit the TOC for improving throughput, inventory, and operational expenses to improve profitability in knowledge work. Finally Eric Ries operationalized new-to-the world lean product development (particularly digital offerings) for start-up founders in his book The Lean Start-Up (2011). This is the extreme unstable demand case.  Ries describes how to measure productivity as validated learning for fast iteration and customer insight to find the scalable business model before cash runs out.  Application of lean principles such as small batch size in the form of minimum viable product, build-measure-learn loop for fast feedback, metrics, and adaptability to find product/market fit. Ries observes that The Lean Start-Up is also applicable within existing companies for use by intrapreneurs who may be creating new value with new-to-the-world products because this is also the extreme unstable demand case.

Productivity Methodology Selection Based On Business Environment

Selecting the right methodology to drive business productivity requires leaders to understand their business environment and the stability of their demand environment. The diagram below helps to characterize application & business environments.

Engineering Productivity TOC

The diagram illustrates that in both manufacturing and engineering that the nature of the work can fall into a range of demand conditions.

A key lesson from this review is that leaders should seek to throttle/smoothen (WIP Constrain) the input demand conditions if productivity improvements results are to be achieved.  All the available methodologies are based on the concept of flow and maximizing throughput and managing inventory (physical or information), and operational expense to achieve business the goals of improved profitability and new value creation for growth and competitiveness. As Goldratt emphasized time and again effectiveness of these methods depend the key underlying condition of stable input demand or constraining the process input demand to ensure stable flow. As demand conditions become unstable lean engineering methods have been developed by Goldratt, Reinertsen, Mascitelli, Schipper, and Swets. Ries has described how new cash flow streams can be created in a lean fashion in the extreme case where demand does not yet exist.

Finally a common theme throughout these works is the fact that cost accounting methods and data tools are ill suited to measure throughput, inventory, and operational expenses to achieve business the goals of improved profitability and new value creation for growth and competitiveness. Goldratt explores this issue at length in The Goal why a blind focus on cost reduction leads to bad performance.  This problem has continued as throughput and TOC methods have evolved in the information age as pointed out by Reinertsen of the invisibility of DIP because of how R&D expenses are recognized at the time the money is spent. Information inventory and intangible assets remain as a problem for cost accounting and business performance management. This will be a topic of future posts.

Mind The Gap

Canada’s innovation performance is weak compared with leading industrial nations with an increasingly clear gap between Canadian business innovation and the country’s strong science & technology capabilities. The gap has confounded decision and policy makers trying to understand why Canada’s strong science & technology capability has not translated into economic growth, improved productivity, and prosperity. The country has relied on an “R&D Supply Push” model by heavily investing in post-secondary research investment that has not translated into any meaningful commercialization.

The importance of this issue is paramount for the future prosperity of Canada as developed countries emerge from the financial crisis with weak growth. Although Canada came through the crisis relatively unscathed due in large part to a highly regulated financial system and strong resource sector the nation’s growth is beginning to fall behind other industrial nations who from their own visceral experiences during the financial crisis recognize that competing on innovation is essential to drive future growth in a new global economic structure.

The Council of Canadian Academies has published as series of studies between 2009 and 2013 exploring Canada’s weak innovation performance. These key studies are Innovation and Business Strategy: Why Canada Falls ShortThe State of Science & Technology in Canada 2012, The State of Industrial R&D in Canada, and Paradox Lost: Explaining Canada’s Research Strength and Innovation Weakness. The most recent, Paradox Lost, is perhaps the most important as it summarizes the results of previous studies to get to the heart of the gap problem in Canada.

The Council of Canadian Academies has identified three main reasons why Canadian business leaders have not adopted innovation as a strategy:

  • Canada’s Role In An Integrated North American Economy – Canada is integrated in North American value chains offering “comparative advantages as upstream suppliers of both commodities and cost-competitive manufactured products” where “acquiring needed innovation from the US has simply been easier and cheaper“.
  • Size of the Domestic Market – Canada has a small domestic market with low level of international competition dominated primarily by competition in the US in an upstream supplier role.
  • Commercial Success of Canadian Business – Competing in the upstream supplier niche Canadian firms have had little or no motivation to change so “have settled into a ‘low-innovation equilibrium’ that has conditioned business habits and ambitions“.

The Council of Canadian Academies suggest though that the underlying conditions are changing that will force Canadian firms to seriously consider adopting innovation as a strategy because of: declining growth rates in highly developed countries including the US; environmental challenges of global development-driven resource demand; adoption of genomics and nanotechnology by competitors that could leave Canadian firms behind; and aging population forcing up labour costs in Canada.

Although policy makers are becoming more aware of this issue business leaders and the population in general have not felt the need to consider the implications because, as the Council points out, there has not been a “visceral realization needed to motivate a meaningful change in strategy“. Canadians experience this problem differently depending on their region since Canada is composed of two very different economies: the east dominated by manufacturing and the west dominated by resource sectors.  Central Canada with a strong dependence on manufacturing is perhaps feeling the most pain and this region has often relied on a weak Canadian dollar as a competitive pressure relief selling into the US. With a thickened border with the US it is difficult to predict if central Canada will be able to return to the past without international market growth. Western Canada has felt the increasing competitive pressures of environmental challenges which is certainly driving innovation but the underlying high production cost of oil & gas in particular has not been addressed. As the Western energy producers are exposed to international markets in competition with lower cost producers production cost issues will need to be solved for the young Western energy supplier base to survive, thrive, and grow.

Moving forward the Council of Canadian Academies suggest that Canadian innovation policy will need to become more ‘firm-centric’ and according Bob Fessenden, one of the key authors noted that “science & technology will be necessary but not sufficient” to drive economic growth. The emphasis will change in Canada from the traditional “R&D supply-push” approach to a “business pull” on Canada’s strong science & technology capabilities.  He noted recently that innovation policy in Canada will need to move to a new paradigm where the Canadian government will need to take a “whole of government approach” aligning trade, procurement, regulatory, and championing “visionary initiatives” or “grand challenges” to drive business growth through innovation.  The new innovation policy should more broadly cover and align these government influenced market signals, input costs, innovation ecosystems, and science policy.  Innovation policy is therefore moving closer to “industrial strategy” which is something that the country has been sorely lacking to align the R&D investments with Canada’s comparative advantages in the new global economy and emerging competition.

The Council also noted that “Canada’s fundamental challenge is to transform its commodity-based economy to one based on providing a greatly expanded number of markets with an increased variety of goods and services where firms must compete primarily through product and marketing innovation“.  Pending some new black swans, perhaps Ontario and Quebec becoming “have-not” provinces with persist high unemployment may be just the visceral realization necessary to make this change happen.

The Missing M in SME

Canadian industry data reveals a recent trend in the falling number of medium sized firms (100-499 employees) in the Canadian economy – referred to as the ‘Missing M in SME’ problem.

The Globe & Mail raised the alarm in 2012 with the article Canada’s Vanishing Mid-Sized Firms based on BDC’s report on medium sized firms.  According to the Globe & Mail Between 2007 and 2010, 527 mid-sized firms exited the economy representing a 3.6% reduction.  Canada is managing to sustain about 40 large and multinational Canadian owned businesses as reported by the Institute For Competitiveness and Prosperity based on data reported in  2009 for firms exceeding $1B. The importance of small businesses to Canada’s economy has received more attention lately as reported by Industry Canada’s small business statistics because as of 2012 small businesses represent 98.2% of all Canadian firms with medium firms making up 1.6% of firms and large making up 0.2% firms. So if the economy is composed primarily of small firms why is ‘The Missing M’ problem important?

Why Is ‘The Missing M’ Problem Important

As the Globe & Mail observed medium firms ‘are more productive, hire more Canadians, and have more clout on the international stage‘ and in 2012 ‘mid-sized businesses, which represent 12 per cent of Canada’s gross domestic product and 16 per cent of the jobs’.  Mid-sized firms grow into large firms that can compete better in the global economy.  The Institute for Competitiveness and Prosperity trend data from 1985 to 2009 does reveal that the number of large firms has increased over this time period, but only slightly, as some firms have exited.  Canada is an exporting country with about 75-80% of GDP derived from export trade so if Canada is not growing more medium sized firms the country’s growth will remain slow. Emerging economies represent tremendous opportunities for Canadian firms but if firms are not large enough to enter these markets and compete the benefits will go elsewhere.

What Is ‘The Missing M’ Problem

What is ‘The Missing M’ problem? Is it a company growth problem? Is it a national productivity or competitiveness problem? Is it the number of medium sized firms or is it the revenue contribution of the medium firms what matters?   Was this a short-term phenomena as a result of the 2008 financial crisis? Is this a result of global economic structural change? ‘The Missing M in SME’ problem needs to be clarified.

What Is Causing The Missing M Problem

What is causing the ‘The Missing M’ problem? Is this phenomena because of the shift from goods production to service delivery economy? Or is it because of the pivot to a more resource-based economy from a manufacturing-based economy? How does this problem manifest itself in different industry sectors or different regions of the country?  Is the Canadian economy comprised of more private firms whose data is more difficult to see? Does the problem reflect in other business measures such as R&D expenditure where there is a distinct ‘U-Shaped’ phenomena in Canadian industry data as reported in a previous post?

Various causes suggested, but not fully substantiated, include:

  • Lack of business leadership growth ambition particularly internationally;
  • Risk adversity;
  • Preferences for ‘Life-Style’ companies;
  • ‘Branch-Plant’ effects where foreign firms acquire mid-sized businesses to gain foot-holds;
  • Canadian M&A activity;
  • Inability to raise capital in medium revenue range;
  • Investor liquidity influences;
  • Management experience;
  • Effects of international competition;
  • Currency effects of a high Canadian Dollar;
  • Tax policy somehow disadvantaging medium sized firms;
  • Small domestic market size;

At the moment no one has fully connected the dots to reveal a clear understanding of the problem nor is there a sense of urgency to fix this problem. Canada’s future economic growth is dependent on the country solving this problem and increasing the number of medium sized firms.

How Does Canada Compare With Other Resource Economies

Growth in emerging nations is radically altering the global economy in particular the demand for resources to support among other things an expanded middle class. The demand for resources has increased dramatically increasing the number of resource-driven economies from 58 to 81 countries. How nations effectively translate resource endowments into long term prosperity was the subject of McKinsey Global Institute study Reverse the Curse: Maximizing the potential of resource-driven economies.

The McKinsey study primarily explores the socio-economic aspects of how non-OECD countries have failed to fully reap the benefits of resource endowments and how to improve the injustices of resource exploitation by other countries or their own internal problems. The study also provides an important methodology to benchmark resource driven economies and provides a unique independent view of resource-driven economy best practice and how Canada stacks up against upper-middle income and high income countries. The data presented portray the full spectrum of national approaches to effectively translate resource endowments into long term prosperity from the best to worst. The study also does a good job of removing biased agendas using ‘Dutch Disease’ or extreme environmental arguments replacing with a more objective rationale for how to properly benefit society in low income resource-based countries from increasing resource demand. What the study does not do however is look at the broader implication of what population growth and global middle class on the capacity of the planet to support the level of demand in the long run.

Resource Economy Growth Model

McKinsey suggests that resource-driven countries (particularly low income nations) need a new growth model with six core elements:

  1. building the institutions and governance of the resources sector;
  2. developing infrastructure;
  3. ensuring robust fiscal policy and competitiveness;
  4. supporting local content;
  5. deciding how to spend resource windfall wisely; and
  6. transforming resource wealth into broader economic development.

McKinsey applied these elements to rank resource driven economies to evaluate their national effectiveness at translating resource endowments into long term prosperity. McKinsey structures these metrics in three key areas : Develop Resources (Building Institutions and Governance), Capture Resource Value (Fiscal Policy and Competitiveness), and Transform Value Into Long-Term Development (Spending the Windfall and Economic Development). McKinsey defined a resource-driven economy as one whose oil & gas and mineral sectors account for more than 20%  of exports, generate more than 20% of fiscal revenue, and resource rents are more than 10% of economic output.

Main Conclusions

McKinsey concluded that in 2011:

  • 81 countries have resource-driven countries up from 58 in 1995;
  • Those 81 countries account for 26% of global GDP up from 18% in 1995;
  • 69% of people in extreme poverty are in resource-driven countries;
  • 90% of resource investment has historically been in upper-middle-income and high-income countries;
  • Half of the world’s known mineral and oil & gas reserves are in non-OECD and non-OPEC countries;
  • $17 Trillion of cumulative investment in oil & gas and mineral resources could be needed by 2030 or more than double the historical rate of investment.
  • 540 million people in resource-driven countries could be lifted out of poverty by effective development and use of reserves;
  • Opportunities to share $2 Trillion of cumulative investment in resource infrastructure in resource-driven countries to 2030;
  • There are 50%+ improvement potential in resource-sector competitiveness through joint government and industry action.

How Does Canada Compare

How does Canada stack up on the six elements of the McKinsey resource-driven economy growth model compared to 81 resource-based economies?

  • Building Institutions and Governance: 2nd (Behind Norway)
  • Developing Infrastructure: 1st
  • Robust Fiscal Policy and Competitiveness: 1st
  • Supporting Local Content: 1st
  • Spending Resource Windfall Wisely: 3rd (Behind Norway & Australia)
  • Transforming Resource Wealth Into Broader Economic Development: 5th (Behind Norway, Qatar, Australia, Iceland)

These rankings and their underlying basis are helpful to evaluate where Canada needs to improve beyond the domestic partisan debates.   In a global context though Canada is within the top 5 resource-based economies out of the 81 resourced-based economies. When compared to high income peers the country is very fortunate compared to less stable low income countries but Canada ought to be doing better in transforming value into long-term development (spending wisely and economic development). Other leading countries will strive to improve so Canada should not be complacent and target improvements particularly in transforming value into long-term development or Canada risks falling behind in prosperity.

Improving Canada’s Performance – Transforming Value Into Long-Term Development

Looking deeper into the McKinsey metrics for transforming value into long-term development spending the resource windfall is based on quality of budgetary process, level of savings, and effectiveness of delivery while the economic development is based on the McKinsey Global Institute economic performance score. The McKinsey economic performance score is based on 21 metrics categorized under five dimensions of: productivity, inclusiveness, resilience, agility, and connectivity.

In terms of spending the resource windfall McKinsey observed that there are five ways to send the resource windfall:

  • invest the money abroad;
  • invest the money domestically;
  • allocate money to specific regional areas;
  • consume the money or resources in the domestic economy; and
  • direct transfers to citizens.

McKinsey suggested that there are six broad principles to guide effective spending of resources revenue: set expectations; ensure spending is transparent and benefits are visible; smooth government expenditure; keep government lean; shift from consumption to investment; and boost domestic capabilities to use funds well.

In terms of economic development McKinsey observed that most resource-driven economies have found it difficult to reap a permanent or longer lasting dividend from their endowments due to boom-bust cycle. Canada however was identified along with Norway, Oman, and Indonesia as examples of sustained growth post the 1970s oil price spike. Interesting though that Canada did not view itself as an Oil & Gas superpower at that time with very different economic drivers (ie. proximity to the US, strong manufacturing, and NAFTA). Today this is a very different story with a declining manufacturing sector, over-reliance on the US, and stagnant NAFTA growth. McKinsey suggest that resource-driven economies focus on five distinct groups of sectors that operate differently from one another and require different interventions:

  • Resource sector itself;
  • Manufacturing sector;
  • Resource riders (transport, construction, professional & technical services, real estate, wholesale goods, and utilities) sector;
  • Local services sector (Financial services, retail, information media and telecoms, hospitality, and administrative support); and
  • Agriculture.

McKinsey also explores the concept of benefaction in the context of economic development as a strategy that leverages an existing sector to create additional jobs and economic activity in subsequent (down-stream) stages of the value chain.  McKinsey notes that although benefaction is attractive there are potential downsides including: subsidizing economically unfeasible activities; and increased regulation that may undermine the global competitiveness of the extraction sector. McKinsey suggest that governments consider the following lessons when attempting to capture downstream value:

  • Understand the potential value of moving down-stream;
  • Understand the fit with local capabilities;
  • Establish supporting regulations;
  • Don’t just regulate but build enablers; and
  • Monitor and enforce.

Specific data how Canada performs according to these measures was not provided except in a couple case examples but it would be useful for Canada and indeed regions such as Alberta, BC, Saskatchewan, and Newfoundland to assess their current performance and set targets for improvement. In a broad sense Canada has implemented well along these various aspects of transforming value mainly because the economy was largely diversified and well developed when resource income began expanding rapidly in the 1990-2000s time frame. The five sectors all have flourished (particularly in western Canada) but Canada has not fully developed benefaction in terms of down-stream value chain activity.  Canada understands its fundamental constraints in terms of fit with local capabilities in areas such as skills mismatch and transportation but is taking steps to solve these problems. Arguably work on supporting regulations, enables, monitoring and enforcement is proceeding but interprovincial political differences/barriers remain problematic.

Innovation Demand Side Research Matching

Matching the supply side of innovation with the demand side can be difficult for university research. TEC Edmonton has hosted a series of  Reverse Trade Shows with the Glenrose Rehabilitation Center for university entrepreneurs to understand practical rehabilitation problems in need of new solutions.

The reverse trade show approach demonstrates how to improve economic outcomes for university research stuck in the lab.  Researchers often have difficulty: connecting with industry; identifying where to direct their commercialization focus; and understanding industry needs. By bringing the innovation demand and supply sides together entrepreneurs can refine their product development thinking, target pivots, and ultimately shorten the time-to-market while governments can improve their return on research investments with better economic outcomes.

For Alberta’s early stage Advanced Technology Sectors broader application of the reverse trade show approach should be encouraged to improve alignment between Alberta university research and each of the province’s jurisdictional advantages in: energy; the environment; petrochemicals; forestry; agriculture; and healthcare leveraging research strengths in biotechnology, nanotechnology, and ICT.