ACCELERATING THE SPREAD OF CAPABILITIES FOR INNOVATION IN COLOMBIAN FIRMS THROUGH THE USE OF AN OPEN INNOVATION POLICY FRAMEWORK
1 ACCELERATING THE SPREAD OF CAPABILITIES FOR INNOVATION IN COLOMBIAN FIRMS THROUGH THE USE OF AN OPEN INNOVATION POLICY FRAMEWORK March 15, 2013 -DRAFT - Rafael Vesga Professor, Universidad de los Andes School of Management email@example.comINTRODUCTION Latin American countries, and Colombia in particular, are struggling to findways to accelerate the application of modern innovation management strategies byfirms in the private sector. Available indicators of innovation activity by firms showvery low levels. For example, in a large-sample innovation survey in Colombia, only0.6% of manufacturing firms reported that they developed a new product for theinternational markets in 2009-2010 (DANE, 2012). The Colombian government hasearmarked substantial resources for the purpose of increasing innovation in businessorganizations, to the extent that a Constitutional amendment was passed in order toensure that 10% of the royalties that oil companies pay to the Colombian State areassigned to enhancing innovation. There is vast work to do ahead to ensure that thismoney is put to productive use and the goals are attained. Colombia enjoys a short window of opportunity to achieve these goals. At thepresent time, the country has a favorable position in its balance of payments and canuse these substantial resources to invest in transforming its own future. However,positive circumstances should not last forever. Sooner or later, the low end of thecommodity price cycle will come back and oil incomes will fall. If Colombia does nottake advantage of the present conditions, dire consequences may become apparentafter only a few years. If Colombian policy makers and business leaders do not figure
2out how to accelerate a structural shift from commodities towards innovative, highvalue products and services, history will repeat itself. However, appropriation of modern innovation capabilities, processes, andpractices by Colombian firms is low. In recent years, following President Juan ManuelSantos’ call to make innovation one of the major engines of economic growth, interestin adopting modern innovation techniques has spread among business managers.Several leading international thinkers in the field of innovation have visited the countryand engaged in conversations with the business community, explaining the basicprinciples of that rule the creation of innovation capabilities in a modern economy.Many firms have expressed their intention to apply such modern techniques in orderto accelerate change within their organizations. The government, in turn, hasstrengthened the public agencies charged with providing support for this task.However, the fact remains that major change is needed to accelerate the evolution ofcapabilities for innovation in Colombian firms. This essay presents the idea that public policy for innovation in Colombia isrestrained by a limited perspective of the problem. The conceptualization of theinnovation process of private firms is limited and highly influenced by the linearprogression view, where research and development precedes the ideation oftechnology, which precedes the launch of innovative products in the market. Thisproblem of a limited conceptualization of innovation, which is not typical only ofColombia, does not mean that policy makers actually believe that this linear sequencehappens, or should happen, in reality. In fact, it is widely accepted that the linearparadigm is obsolete. The problem is that there are quite few alternative modelsavailable for policy makers to use when they set out to achieve the objective ofstimulating innovation in private sector companies. Moreover, since the key metrics inuse to frame the problem of innovation in the policy discussion were developed underthe linear paradigm, the discussion itself ends up being defined by the limitations ofthe linear model. Even if policy makers in Latin America and Colombia recognize thatinnovation is a systemic problem, the metrics, still locked in the linear paradigm, pointto R&D as the essential tenet of innovation. The metrics frame the discussion andmake it very hard to have a dialogue about innovation policies outside of these limits.
3 A brief consideration of the role of metrics illustrates the point. For example, arecent review of innovation activity in Latin America by the Inter AmericanDevelopment Bank (Navarro, Zuñiga, 2011) focused on the backwardness of theinnovation performance of Latin American firms in comparison to those of otherregions of the world. The authors explicitly argue that the linear model is not a goodexpression of true innovation dynamics. However, the empirical discussion is focusedon differences in R&D, availability of Ph.D. graduates, and other indicators that aretypical of the linear paradigm. Clearly, this happens because there are no other metricsavailable for the authors to gauge progress of private firms towards innovation. Thus,the state of the art is an analysis where R&D is of paramount importance for examininginnovation in a region where, given the key sectors in the economic structure, R&D isquite limited. The focus on this kind of metrics is also typical of the innovationindicators used by the OECD. Although this organization has done substantial effortsrecently to introduce new indicators that reflect other views on innovation (OECD,2012) such indicators are far from mainstream use. Meanwhile, business leaders who adopt modern innovation managementtechniques set their priorities using very different metrics. Managers talk about thecomposition of their innovation portfolios, the contribution to the bottom line ofproducts launched over the previous 18 to 36 months, the number of ideas in thepipeline, and so on. Very few business leaders in Latin America, in very few sectors,have high priorities for R&D, although they may have ambitious innovation goals interms of new products, services and business models. In a region where services andnatural resources sectors contribute more than 70% of GDP in several countries,business people find hard to digest the notion that in order to achieve high aspirationsin innovation they need to focus on R&D. This creates a substantial gap in the dialogue between policy makers andbusiness leaders. While the policy discussion remains adhered to linear paradigmmetrics, private sector firms have switched their attention to different ways ofunderstanding the problem of innovation and to a growing variety of metrics. As aconsequence, what is measured in the policy sphere is of low importance to mostbusiness leaders. Also, what is important for business leaders is difficult to measure at
4a meso and macro levels. Thus, there are substantial transaction costs in theinteraction between firms and policy makers, which reduce the impact of policyefforts. This affects the quality of the public-private dialogue and weakens the abilityto make effective progress in the matter. This is not an academic discussion about intellectual paradigms. It is clear thataccelerating the appropriation of knowledge about innovation management practicesand processes is urgent in Latin America and Colombia. The fact that the discussionabout policy instruments remains confined in an R&D paradigm makes it harder toaccelerate the appropriation of innovation management techniques and tools acrossfirms. This is truly a gap between distant mental models used by different people whoactually seek the same objectives. If innovation is not synonymous to R&D for most managers, then, how do theyapproach the issue? Innovation is not just a process but a capability, a combination ofroutines and systems that need to work work harmoniously within the firm and allowit to achieve competitive advantage in the market through the generation of distinctiveproducts and services, creating value for customers through novel combinations ofattributes. Innovation is not a linear process and demands several contradictoryabilities from the firm. Deploying a capability for innovation requires that firms engagein processes geared towards exploring latent customer needs and designing productsthat will only be available in the future. At the same time, firms need to keep a focuson execution processes, oriented at extracting value from the businesses that theyexploit in the present. Scientific and technological innovation is only a part of thispanorama and is more important in some firms than in others, depending on thesectors in which they compete. Only some firms care about R&D, but all firms shouldcare about developing capabilities for innovation and overcoming the tensionsbetween exploration and exploitation (March, 1991). This essay sets forth the idea that the adoption of an Open Innovationframework for policy making could provide a substantial contribution to bridging thegaps that today separate policy makers and business leaders on these issues. Within anOpen Innovation framework it would be possible to develop a common language anduseful metrics for innovation public policy and business firms. Such an environment
5would be more effective in helping firms overcome the barriers to the absorption ofmodern innovation management tools and techniques. The Open Innovation framework offers several advantages in dealing with theproblems described above. Open Innovation is “the use of purposive inflows andoutflows of knowledge to accelerate internal innovation, and expand the markets forexternal use of innovation, respectively” (Chesbrough, 2006). The focus is on the flowsof knowledge to and from the organization. This concept can be applied to innovationas defined in different ways, so it is relevant for efforts focused on R&D and also forinitiatives that deal with product and service innovation. The Open Innovation framework also offers a way out of the “black box”problem, where the inner workings of private firms are unknowable, or beyond thescope of analysis, for policy makers. Policy makers tend to understand firms asmonolithic entities. However, firms are anything but monolithic. In fact, they areconstellations of resources and individuals that operate at three levels at the sametime: the firm, the group and the individual. Innovation initiatives and strategies withinfirms proceed as systemic affairs which will fail if the weakest link in the chain fails. Theweakest link may reside at the firm, group, or individual level. There is no reason whypublic policy should not acknowledge this fact and help firms learn from theexperiences of each other at the different levels. It is critical that both policy makersand firm leaders are both able to understand this and act accordingly, in order toanalyze weak links and find solutions. For firms, the appropriation of capabilities for innovation is essentially aproblem of organizational learning, that is, it can be understood and solved onlythrough the appreciation of past experience and the incorporation of new routines,overcoming inertia and barriers to change. For policy makers, engaging firms in aroutine of sharing information about these processes and applying lessons is quitedifficult, not only because of confidentiality concerns, but because there is quite littlein terms of a shared language that could help firms codify what they are doing. Withinan Open Innovation policy framework, this common language and the associatedmetrics could be developed in a concerted effort by private and public actors.
6 This essay is organized as follows. The first section is this introduction. Thesecond section presents some evidence showing that the level of absorption ofinnovation practices and techniques by Colombian firms is low, although they showhigh rates of adoption of managerial techniques geared at the replication of processes.The third section describes the gaps between the mental models, frameworks andmetrics used by policy makers and business people to deal with innovation and showshow the absorption of innovation management techniques and tools is a problem oforganizational learning for firms. The fourth section presents an argument favoring theadoption of the Open Innovation model as a general framework for analyzing andacting on initiatives to accelerate the development of innovation capabilities by firmsin Colombia.ABSORPTION OF INNOVATION PRACTICES BY COLOMBIAN FIRMS The development of innovation management and processes in firms dependscrucially on the ability to assimilate and replicate new knowledge gained from externalsources. Any firm that desires to create competitive new products and services in asystematic, scalable way needs to open up to knowledge and information coming fromthe environment and held by customers, competitors, suppliers, partners and the like.The level and quality of absorptive capacities are defining characteristics of any firm,since they are developed over time in a path dependent process, where new abilitiesdepend on the level and quality of previous abilities; thus, absorptive capacities speakof the history and achievement of a firm. They are crucial in explaining why somecompanies are systematically superior to others in understanding customer needs andcreating winning responses in the form of innovative product and services (Cohen &Levinthal, 1990). There is limited available evidence on the level and quality of absorptivecapabilities in Colombian firms. Few standard measures aimed at this purpose arecalculated with any regularity or depth.
7 A first step in approaching the problem is to consider the output of absorptivecapabilities, that is, the extent to which Colombian firms are able to developinnovative products and present them to customers in the market. Information from amanufacturing survey on innovation and technological development in Colombianfirms for the years 2009-2010 shows that the performance of Colombian firms in thisarea is weak (DANE, 2012). According to this survey, only 0.6% of Colombianmanufacturing firms were classified as innovators “in a strict sense”, a term thatdescribes firms which developed a new product or service for the international marketin the period. According to the same source, 33.8% of Colombian firms can beclassified as innovators “in a wide sense”, which means that they developed at leastone new product for the domestic market during the period. At the same time, a full60.5% of manufacturing firms were classified as not innovative, meaning that they didnot develop, and were not working to develop, a new product for any market (seeTable 1). Table 1 Colombia: Distribution of Manufacturing firms according to Innovation Performance (% of total) 2009-2010 2007-2008 2005-2006 2003-2004 Innovators in a "Strict Sense" 0.6 4.6 11.8 2.3 Innovatoris, "Widely Understood" 33.8 33.2 21.9 24.5 Potenitial Innovators 5.1 5.3 9.2 21.2 Not Innovators 60.6 56.8 57.1 52.0 100.0 100.0 100.0 100.0 Source: DANE, 2012 The low proportion of firms working to develop products that can beconsidered as new in the international market is particularly worrisome. Thispercentage fell from a high of 11.8% in 2005-2006, to 4,6% in 2007-2008, to below 1%in 2009-2010. Several macro factors may explain this falling performance, including thefact that the Colombian economy has gone through a number of years of continuedappreciation of the domestic currency, which have pushed firms in the manufacturingsector to a difficult position in terms of their international competitiveness. This may
8help explain why the interest in creating new products for the international markets isdecreasing among Colombian manufacturing firms. At any rate, these results can beinterpreted as evidence of weakening absorptive capabilities in Colombianmanufacturing. The ability to use knowledge for the purpose of developing productsthat can compete in demanding international arenas, through innovative valuepropositions, is waning not strengthening with time. Another approach to the issue of absorptive capabilities in manufacturing firmsis provided on Table 2. Firms in the same survey are asked to report if they collaboratewith others in attaining objectives in different areas. This act of collaboration can beunderstood as a proxy for a deliberate policy to enhance the flows of knowledge in andout of the firm. The percentages of firms declaring that they cooperate with others arequite low. The highest percentages refer to the management of machinery andequipment, where 17,2% of the surveyed firms have cooperated with suppliers and11,8% say that they have held relationships with organizations that offer technicalassistance. Beyond this, the indicators of collaboration presented in Table 2 indicatethat business leaders give a low priority to this kind of effort. Table 2 Colombia: engagement by firms in cooperation with other organization for developing Science, Technology and Innovation projects (Percentage of firms that report participating in collaborations with other firms) Other Firms Suppliers Clients Competitors Consultants Universities Technology Research Technology Regional International Development Centers Parks Productivity Organizations Centers CentersResearch & Development 5.0 7.3 8.2 1.3 5.4 6.0 1.5 1.2 0.5 0.6 1.0Machinery & Equipment 3.6 17.2 2.7 1.1 2.5 0.5 0.3 0.1 0.1 0.1 0.4Information and Telecommunications Technologies 2.6 5.8 2.1 0.5 3.2 1.0 0.4 0.2 0.3 0.2 0.2Marketing of Innovations 2.7 4.5 9.0 1.6 3.0 1.4 0.3 0.1 0.2 0.3 0.4Technology Transfer 3.0 3.8 1.6 0.9 2.3 1.2 0.5 0.2 0.3 0.2 0.5Technical Assistance 4.2 11.8 5.1 0.9 9.8 4.1 1.2 0.7 0.3 0.6 1.1Engineering and Design 2.3 5.0 3.2 0.6 3.0 2.1 0.4 0.2 0.1 0.3 0.3Training 3.1 6.3 2.9 0.4 5.5 4.0 1.0 0.3 0.3 0.4 0.9 Source: DANE, 2012 A third perspective on the problem of absorption can be obtained by usinginformation from the Global Innovation Index for 2012, or GII-2012 (Dutra, 2012). Theindex combines information from a wide variety of sources. These variables are usedfor identifying statistical factors that are related to innovation performance. The GII-
92012 uses data generated by authorized statistical sources in each country, and alsoinformation gathered through a survey of business people in the participatingcountries. Table 3 presents some of these measures. While some of the variables expressabsorptive capabilities in an obvious way, others need to be understood as proxies forunderlying absorptive capabilities. By ordering the variables according to the percentile rank in which Colombianfirms are located in the general classification among the 141 countries underexamination, a revealing perspective begins to emerge. Table 3A Colombia: Ranking in variables related to knowledge absorption by firms. Variables ranked above the country’s general position Global Innovation Index 2012 Rank Percentile Global Innovation Index - Colombia 65 Firms offering formal training 8 0.93 High-tech imports 13 0.90 Creative services exports 20 0.83 ISO 9001 quality certificates 26 0.82 Foreign direct investment net outflows 23 0.81 Country-code top level domains (ccTLDs) 37 0.74 State of cluster development 38 0.72 ICT and business model creation 38 0.72 University/industry research collaboration 40 0.70 Generic top level domains (gTLDs) 44 0.69 ICT and organizational models creation 46 0.66 Computer and communications service imports 64 0.53 Growth rate of GDP per person engaged 55 0.53 Foreign direct investment net inflows 69 0.51 Creative goods exports 66 0.51 Source: Dutra (2012)
10 Table 3B Colombia: Ranking in variables related to knowledge absorption by firms. Variables ranked below the country’s general position Global Innovation Index 2012 Rank Percentile Global Innovation Index - Colombia 65 Wikipedia monthly edits 64 0.50 Video uploads on YouTube 70 0.50 Joint venture / strategic alliance deals 74 0.48 Royalty and license fees payments 65 0.45 Royalty and license fees receipts 59 0.45 Recreation and culture consumption 56 0.44 Patent Cooperation Treaty applications 64 0.42 Employment in knowledge-intensive services 62 0.41 National office trademark registrations 52 0.41 New business density 61 0.40 National office utility model applications 39 0.38 Computer and communications service exports 83 0.38 High-tech exports 77 0.37 Total computer software spending 63 0.35 Daily newspapers circulation 90 0.34 GERD financed by abroad 63 0.32 Scientific and technical journal articles 98 0.30 GERD performed by business enterprise 66 0.26 GERD financed by business enterprise 67 0.26 National feature films produced 79 0.21 National office patent applications 91 0.17 Share of patents with foreign inventor 102 0.00 Source: Dutra (2012) Colombia was ranked in the 65th position in the general classification accordingto the GII-2012. Table 3A and 3B show a number of selected variables used in theindex. Table 3A shows the variables in which Colombia´s ranking is higher than theposition obtained by the country in the general classification. These variables areinterpreted here as making a positive contribution to the country’s overall position.Table 3B shows the variables in which Colombia obtained a ranking that is lower thanthe position achieved by the country in the general classification. These variables areinterpreted to contribute negatively to the overall position. Thus, variables on Table 3Aare pushing Colombia forward in the general effort to attain higher capabilities forabsorbing and applying knowledge, while variables on Table 3B are acting as brakes inthis process.
11 Table 3A show that Colombian firms rank fairly high in some variables that areclearly related to the ability to seek and absorb information from the environment. Forexample, Colombia appears in the 0.93 percentile rank among 141 countries in thesample regarding the importance that private firms give to providing formal trainingfor their employees. In other words, only 7% of the countries in the sample showed abetter performance than Colombia in this variable. Other indicators show a distinctively positive performance of Colombia incertain topics related to knowledge absorption by firms. For example, Colombia ranksabove 83% of countries in the sample regarding the performance of creativeindustries. Quite significantly, Colombian firms rank above 82% of the countries in thesample in terms of their ability to obtain ISO 9001 quality certificates. According to theexecutives surveyed by the creators of the GII-2012, Colombia also ranks high in termsof the use of information and communication technologies (ITC) in the development ofnew business models, in the state of cluster creation (above 72% of the countries inthe sample in both cases), and in university-industry collaboration (above 70% of thecountries in the sample). All these indicators point to the fact that there must be asignificant number of Colombian firms which are routinely engaged in creating andstrengthening knowledge-based relationships with their environment. Taken as awhole, these indicators show a country that should be performing in the higher ranksof the distribution in terms of absorption capabilities. However, these indicators refer to an ability to absorb knowledge, notnecessarily an ability to produce new knowledge and innovate. Other indicators in thelist (Table 3B) show that Colombian firms are not performing quite well according tothis last perspective. The GII-2012 incorporates several variables that refer to R&D. The performanceof Colombia in these variables is generally poor. For example, when it comes todomestic patent applications, Colombia is only above 17% of countries that lay at thetail of the distribution. Regarding R&D financed and performed by private firms,Colombia is superior only to 26% of countries at the bottom. In high tech exports,Colombia’s ranking is somewhat higher, standing before 37% of the countries in thedistribution, which is itself interesting, given that the country’s performance is so poor
12regarding R&D (other capabilities must be in action around these exports, allowing thecountry to achieve a ranking that is significantly above that of R&D). It is true that R&D should not be regarded as the only or ultimate metric forinnovation. However, other variables that indicate high-level innovation capabilitiesshow similar results. With regards to employment in knowledge-intensive services, thecountry is above 41% of the countries in the distribution. In royalty and license feesreceipts, Colombia is above 45% of the countries in the distribution, while in jointventure and strategic alliance deals it ranks above 48% of the countries in the list. Each of these indicators is somewhat isolated and partial. They were compiledby the authors of the GII with the objective of offering a general view of businesssophistication and the ability to assimilate and use knowledge by countries in thesample. Therefore, these indicators cannot be interpreted as conclusive evidence inany way, but rather as an exploratory effort to shed light into a very complex matter. Having said this, it is also true that a picture of Colombia as a country that islocated at the crossroads of contradictory forces begins to emerge. In brief, thebehavior of some of these indicators reveal a productive sector that is interested inreaching up to international standards in order to be competitive. This is the case ofthe extended adoption of ISO 9001 certificates, or the penetration of formal trainingfor individuals at work. However, these efforts are not enough to counteract thestrength of other indicators in which Colombia is ranked at low levels, such asemployment in knowledge intensive services, income from royalties, new businessdensity, national office trademark registrations, or computer and communicationsservices exports. A synthesis of this situation could be expressed in this way: Colombian firms areabove average in the international scene when it comes to acquiring knowledge forreplication; are somewhat below average in reference to generating knowledge andinnovation that is not related to R&D; and are definitely at the lower echelons in thedistribution regarding the creation of knowledge through R&D.
13THE MENTAL MODEL GAP This section examines the distance that separates the perspectives and metricsused by policy makers and private business managers when addressing innovationstrategies. The goal is to consider the magnitude and consequences of this gap uponthe objectives of accelerating the absorption of knowledge and developing innovationcapabilities by firms. The policy-making view In Latin America and Colombia, the action of government is of great importancein creating an environment that is supportive of the increase of knowledge-absorptioncapabilities for innovation by firms. Thus, there should be growing interest from bothpolicy leaders and private firm managers in gaining deeper understanding of how eachother sees this problem and makes decisions about it. Referring to the general role ofpolicy and private actors in the process of creating a modern industrial policy, theeconomist Dani Rodrik expressed this condition in the following words (Rodrik, 2004): “…the task…is as much about eliciting information from the private sector on significant externalities and their remedies, as it is about implementing appropriate policies. The right mode…is not that of an autonomous government applying Pigovian taxes or subsidies, but of strategic collaboration between the private sector and the government with the aim of uncovering where the most significant obstacles to restructuring lie and what type of interventions are most likely to remove them. Correspondingly, the analysis of industrial policy needs to focus not on the policy outcomes—which are inherently unknowable ex ante— but on getting the policy process right. We need to worry about how we design a setting in which private and public actors come together to solve problems in the productive sphere, each side learning about the opportunities and constraints faced by the other, and not about whether the right tool for industrial policy is, say, directed credit or R&D subsidies or whether it is the steel industry that ought to be promoted or the software industry”. This “coming together” with an agenda focused on identifying and removing“the most significant obstacles” assumes that there are common grounds for dialoguebetween public and private actors in the conversation. However, in this case the
14language and the metrics used to understand the problem probably contribute moreto separate the actors than to unite them. Policy makers tend to view the problem from the perspective of a nationalinnovation system, where key actors in society interact with firms in the private sector,providing innovation inputs to firms. These firms, in turn, produce innovation outputs,closely related to R&D, to satisfy market demand. A commonly used synthesis of thisprocess is provided in Figure 1 (Arnold and Kuhlman, 2001). In this view, the key inputsare human capital and research, which are transformed by private firms into productsthat fit the demand by customers. Other supporting roles correspond to financing andgeneral activities by government. Figure 1 A National Innovation System Source: Arnold and Kuhlman (2001). A synthesized view of key variables that are associated to inputs and outputs inthis view is presented on Table 4. Inputs are essentially human capital and researchresources, while outputs are innovative products as well as research results.
15 Table 4 Variables used in Public Policy for measuring progress in Science, Technology and InnovationInnovation Inputs Innovation OutputsExpenditures in Scientific and Technological Activities Scientific papers published in Indexed JournalsR&D Expenditures Patents filedNumber of researchers by Sector Patents grantedNumber of researchers by Field of Science Patents acquiredSources of financing for Scientific and Technological Activities TrademarksNumber of individuals with Masters and PhD degrees working in industry New to Market product innovationsCollaboration on innovation New to the world product innovations Product Innovations (New to the World, New to the Firm) Exports by Technology Intensity Source: Hatzichronoglou, 1997 However, Table 4 leaves out many elements that are relevant in any discussionof innovation. It is recognized today that innovation activities by firms are notrestricted to R&D and that the process of knowledge absorption that leads toinnovation covers a large variety of activities beyond R&D (Oslo Manual, 2005). TheOECD has acknowledged this fact and is working to develop a new set of indicatorsreflecting the degree of innovation that is prevalent in different sectors in theeconomy (OECD, 2012). The importance of this shift can be appreciated on Tables 5and 6 below. Table 5 shows the order of manufacturing sectors according to R&Dintensity that was used by the OECD in presenting its innovation reports until a fewyears ago (Hatzichronoglou, 1997). This order reflects an estimation of thecontribution of R&D to value added in the different sectors.
16 Table 5 High Innovation sectors according to R&D Intensity, OECD 1996 Classification ISIC code Sector High Technology Industries 3845 Aerospace 3825 Office & computing equipment 3522 Drugs & medicines 3832 Radio,TV&communication equipment Medium-High Technology Industries 385 Scientific instruments,385 3843 Motor vehicles,3843 383 - 3832 Electrical machines excl. commun., 351+352-3522 Chemicals excl. Drugs 3842+3844+3849 Other transport, 382 - 3825 Non-electrical machinery Medium-Low Technology Industries 355+356 Rubber & plastic products 3841 Shipbuilding & repairing 39 Other manufacturing 372 Non-ferrous metals 36 Non-metallic mineral products 381 Metal products 353+354 Petroleum refineries & products 371 Ferrous metals Low-Technology Industries 34 Paper, products & printing 32 Textiles, apparel & leather 31 Food, beverages & tobacco 33 Wood products & furniture Source: Hatzichronoglou, 1997 When considered from this perspective, the most important sectors from thestand point of innovation are Aerospace, Computing, and Drugs and Radio-TV-Communications equipment. Medium-high sectors include Scientific instruments,Motor Vehicles, Electrical Machinery and Chemicals. Thus, an implicit assumptionbehind Figure 1 is that if countries wish to move forward in innovation, they shoulddevelop these sectors, where there is substantial R&D-driven innovation. Thisassessment can be expected to find little echo from business managers in a countrylike Colombia, where 62% of GDP is provided by services and where the high andmedium-high technology manufacturing sectors presented in Table 4 hold a minimalshare of GDP. Recently, the OECD has presented a new, and still experimental, classificationof productive sectors according to Innovation Intensity (OECD, 2012). Thisclassification opens the way for a broader definition of innovation that overcomesvarious limitations of previous measurements (Table 6). The new classificationacknowledges that there are many sectors where, even though scientific research isnot an investment priority (since it does not create competitive advantage), there are
17significant innovation capabilities being deployed as a key component of businessstrategy. In these sectors, innovations are evident in the development of products,services, organizational systems and marketing solutions. R&D activities are only onecomponent within a broad framework. This approach is more faithful to the spirit ofthe Oslo Manual, which recognizes that innovation can take different materialexpressions as product or process innovations, organizational innovations andmarketing innovations (OECD, 2005). Table 6 Top-10 Innovation sectors according to Innovation Intensity, OECD 2011 ISIC Code Sector 73 Research and development 24 Chemicals and chemical products 66 Insurance and pension funding, except compulsory social security 23 Coke, refined petroleum products and nuclear fuel 32 Radio, television and communication equipment 65 Financial intermediation except insurance and pension funding 72 Computer and related activities 33 Medical, precision and optical instruments, watches and clocks 34 Motor vehicles, trailers and semi-trailers 64 Post and telecommunications Source: OECD, 2012 This new OECD methodology introduces the criterion of Innovation Intensity,which considers four key variables: a) product and process innovations, b) expenditurerelated to innovation, c) organizational and market innovations, and d) intellectualproperty rights. The methodology gives a score to each sector in each of these areas,and establishes a new order among sectors. This order was obtained empirically, basedon information from firms in OECD member countries, using measurements from theCIS innovation survey (the Eurostat Community Innovation Survey). Table 6 presentssome of the ranked sectors. This ranking is different from the R&D-based ranking in Table 5. For example,manufacturing of motor vehicles, trailers and semi-trailers (ISIC 34) is considered ashighly innovative when using a categorization based on R&D, but ranks only asmoderate (ninth in the overall classification) when the categorization is based onInnovation Intensity. Similarly, the Computer and Related Activities sector (ISIC 72) is
18not listed among the 10 most innovative in the classification based on R&D, but itreaches position 7 in the Innovation Intensity ranking. These results make it clear that a new interpretation of Figure 1 is needed. Keyhuman capital is not limited to Ph.D. degrees. Intellectual property is not only patents,but includes many other forms of appropriation of the benefits of innovation, such asbrand value and trademarks, and does not flow exclusively from research atspecialized institutes or universities. Many more sectors in the economy are involved,including several key services sectors. This should lead to a major re-interpretation ofthe role and characteristics of innovation actors in the economy. Given this perspective, and having knowledge absorption for innovation inmind, a view of different modalities of innovation such as the one presented in Table 7can be quite useful (Pavitt, 1984; Tidd et al, 2001; Arnold et al, 2012). Innovation canhappen not only in manufacturing, but also in services sectors. Innovation can bepresent in several degrees, from incremental to radical, can be driven by differentfunctions within the firm, and can be protected and appropriated through a diverserange of mechanisms, not only through the use of patents.
19 Table 7 A taxonomy of Sector Innovation Main sources of technical Means of Category change Focus of innovative activity Size of innovating firms appropriation Supplier- . Suppliers Main focus is process Firms are typically small and Appropriation is rarely dominated . Production learning innovation in pursuit of cost found within traditional based on technological reductions manufacturing sectors such as advantage but instead on Firms are almost entirely Innovation strategy is to use to textiles, agriculture and professional skills: dependent on their suppliers of technology from elsewhere to services . Design machinery and other production inputs for new technologies support competitive advantage. . Trademark Limited in-house innovation Process innovations are created . Advertising activity is undertaken but some in supply sectors and embedded . Marketing learning from in-house production within the inputs to production activities Scale- . Production engineering Both product and process Firms are characterised by Appropriation by: intensive . Production learning innovation but a significant focus large-scale mass production . Process secrecy and on production improvements. where significant economies of know-how . Design office Innovation strategy is focused on scale and division of labour are . Technical leadership . May include in-house R&D incremental improvements as present. . Some patenting . Suppliers implementing radical change on The products & production Innovations are largely complex products and processes systems are complex developed in-house, which may is highly risky integrations of technologies. include an internal R&D. Some Sectors include: automobiles, innovation also sourced from extraction & processing of bulk specialised suppliers of materials & consumer durables equipment and components Specialised- . Design function Innovation focused on product They are generally small in size, Appropriation by suppliers . Operational knowledge performance improvements. manufacturing high- . Design know-how These improvements are often performance inputs to other . Input from advanced users . Relationships with, and developed to meet the high complex products and knowledge of users specification requirements of production processes – inputs key users. They are later such as machinery, . Some use of patents transferred to other users components, instrumentation and software Science-based . In-house R&D Focus on product innovation Innovation is highly dependent Appropriation by: . Basic research from external where fundamental discoveries on developments in the . R&D know-how sources (in basic science) lead to new relevant science base and new . Patents . Input from advanced users products and markets and products are diffused widely as corresponding new production consumer goods or inputs to . Process secrecy and These firms invest heavily in and organisational processes other sectors know-how internal R&D to create innovative . Internal dynamic Innovation strategy requires Firms are typically large and in new products and have close ties learning monitoring and exploiting sectors such as to the research base to access developments from the pharmaceuticals, chemicals, new knowledge, skills and research base electronics, materials techniques Information- . In-house systems & software The focus of innovation is to Firms are in service sectors that Appropriation by: intensive departments improve, and even redefine, rely heavily on technology to . Process know-how . Suppliers methods of service delivery process large quantities of . Software IP Innovation comes from internal and to create entirely new information for efficient and (copyright) and external sources, and is based service products effective service delivery: sectors such as finance, retail, . System design on IT hardware improvements, know-how software developments and insurance, travel and systems integration publishing, telecoms Sources: Pavitt, 1984; Tidd et al, 2001; Arnold et al, 2012. This view of the problem of innovation is definitively more comprehensive andinclusive of the different sectors and modes of innovation that exist in private firms.Therefore, it represents a significant step forward. A framework like this should beused to consider the definition of the role of government in fostering innovation and increating a set of tools and instruments for this purpose.
20 The private sector view Private companies use a wide set of metrics to measure progress towardsinnovation goals. Although there are many available metrics, only a small number ofthese are generally used. Firms also classify metrics into two large groups: input andoutput metrics. Some examples are presented in Table 8. Table 8 Some Innovation Metrics used in by firms in the private sector Source: Boston Consulting Group, 2009; Morris, 2011 As can be seen in the table, output metrics are focused on financial and brandimpact results. Input measures, on the other hand, focus on the resources that havebeen put to use in the innovation effort and also on efficiency, seeking to identify the
21amount of resources involved and the possible redundancies or over-costs in the useof these resources. Beyond this, other innovation indicators seek to characterizeemployee interactions, and therefore try to capture information about the state ofculture and team work. A quick comparison of tables 4 and 8 allows to identify key areas whereindicators used by policymakers and private firms share common grounds, as opposedto other areas where they do differ substantially. Is it clear that an important commontopic is the interest for measuring if innovations developed by the firm are new to theworld and (or) new to the firm. Beyond this, however, the policy and private sectormetrics split towards different directions. The set of indicators used by policymakers isfocused on human capital and technology-related investments. Meanwhile, theindicators used by private firms only pay attention to R&D if it is an importantcomponent of the firm’s innovation strategy. As mentioned before, there is no reasonto expect that this would be the case beyond a minority of situations. The question of which are the right metrics for innovation is generating growingdiscussions among firm managers. There is a concern among companies about thevalue that is being created through their innovation efforts. A survey of firms in fourcontinents (Boston Consulting Group, 2009) found that only 52% of respondents weresatisfied with the performance of their investments in innovation and only 32% ofrespondents were satisfied with their companies’ innovation metrics. While 73%believed that innovation efforts should be measured as rigorously as processes in thecore business, a full 63% of these were not sure which metrics to use or believed thatthis this issue had not been given the priority they felt it deserved. Finally, the surveyidentified that the measures most widely used by firms in the sample were related toprofitability (79% of the respondents used metrics related to this topic), customersatisfaction (75%), incremental revenue from innovations (73%), time to market (59%),idea generation (55%), and R&D efficiency (49%). These results show that there are substantial issues to be solved from theperspective of firms, regarding the measurement of innovation strategies andprocesses. This compounds the problem. Not only the metrics used by policy makersare seen as irrelevant, but the metrics used by the firms themselves are seen as
22incomplete and unsuitable. The policy-private information gap cannot be solvedsimply by adapting private metrics for policy purposes, because firms are not satisfiedwith the metrics that they are using. It seems that a new understanding of the problemmust be achieved and new metrics for innovation must be produced. If private firms are not quite sure about which metrics to use, what can be donefrom a policy perspective? In order to close the gap between the ways in which publicand private actors understand the problem of innovation by firms, it will be necessaryfor both to work together to create a common view, a common language and commonmetrics. Following Rodrik’s call to action, this is clearly an area in which a new settingneeds to be designed where private and public actors can come together to solveproblems, “each side learning about the opportunities and constraints faced by theother”. An answer to this invitation could be found by using the instruments providedby the Open Innovation approach. However, before exploring that avenue in moredepth, it is important to present some considerations regarding the challenges that areawaiting in the design of innovation metrics. There are important problems in measuring innovation management, whichcannot be ignored. As Langdon Morris pointed out (Morris, 2011), it is quite possiblethat the very efforts that firms make in order to measure innovation may significantlyimpede the process itself. Morris offers three reasons for this. First, the pursuit ofinnovation necessarily involves a venture into the unknown, and it is quite possiblethat trying to define the unknowns too early in the process may make it harder torecognize good opportunities or solutions. For example, trying to calculate the value ofevery idea too early on in the process may end up generating misleading numbers.Second, misapplied metrics can undermine the spirit of learning and discovery that aninnovation process requires, because they may lead a team to choose a particularversion of a concept too soon. And third, argues Morris, the discussion of metrics caneasily become a form of intimidation used to demean the ambiguity of the innovationprocess, particularly when an organization needs to choose between assigningresources to innovation initiatives or to the well-known core business.
23 At the center of any innovation process lays a process of discovery. Given theamplitude of the arenas where innovation can be productively used by firms, theproblem can become extremely complex quite easily. Firms need to make thiscomplexity manageable. At the same time, they should beware of frameworks whichquickly adopt an overly limited perspective. It can happen that, in order to avoid theambiguity and doubt that comes with the discovery process, firms end up closingpossibilities and paths for action before the process has even begun. During the discovery stages, innovation should not be treated as a linearprocess that generates a neatly measurable output. An innovation managementsystem needs to be conceived as as a set of principles, practices and tools which servesas an enabler of business strategy and needs to be subject to permanentexperimentation. Metrics are necessary, but no static measures can capture the fullscope of the innovation process at the discovery stages. Managers cannot expect thatby focusing on similar metrics for all their projects they will obtain the desired results.As a firm moves forward, achieving innovation goals and consolidating its learning ofinnovation, the metrics should change, based on the firm’s experience. Figure 2 illustrates this concept. The two essential questions of businessstrategy are where to compete (defining segments, geographies, products,technologies, channels and the like), and how to compete (that is, the specific,distinctive approach that will be used to create an engaging value proposition andobtain competitive advantage). Figure 2 presents these questions in the two axes ofthe diagram. As the firm moves away from the origin in Figure 2, it abandons existingways of doing things and engages in new practices. This happens by executing specificprojects of different magnitude throughout the organization.
24 Figure 2 The essential questions of business strategy and the role of innovation An innovative firm is one that continuously experiments, seeking to push thelimits of the existing way of doing things, in a constant drive away from the origin inFigure 2. The firm may seek to achieve a position like point A, in which it tries newanswers to the where question and seeks to conquer new segments, geographies,channels, etc., while maintaining a value proposition that is similar to the precedingone. Or, it may choose a position like B, developing new approaches to the howquestion and presenting new value propositions to existing customers. Or, it may trynew approaches on both of the key questions at the same time, as in position C. Thefirm may try many other possible combinations in this map. The actual way in which is this is done consists in developing new projects thatlead to the creation of innovative products, services, processes or business models.The firm learns lessons from each of these experiences and applies these lessons insuccessive projects that gradually expand the frontier of achievement. Along thissearch, a capability for innovation emerges. This is similar to the development of amuscle by an athlete. It demands intense observation of how the process works in thepresent, identification of opportunities and barriers, formulation of solutions,
25application of new methods, verification of what works, and so on. This cycle becomesa routine for the organization, allowing it to achieve larger leaps in the path away fromthe origin in Figure 2. The process needs to be kept flexible because it is essentially a discovery andsearch process. What works in the move from one position to the next in the map willnot necessarily be equally effective as further steps are taken. Metrics are necessary,but the application of metrics can become counterproductive if they are associated toan urge to repeat thoughtlessly what worked in the past. Therefore, organizations need to reflect deeply about what a process ofdiscovery really is and why it is different from other forms of learning. The frameworkin Figure 3 helps to understand this (Yeung et al, 1999). Figure 3 Learning Styles of Firms Source: Yeung et al, 1999 There are four distinct learning styles which companies can use to generate thecapabilities needed to develop new products and services. These four learning stylesappear as the result of combining two ways of using experience for learning; and two
26ways of focusing attention, either on the exploration of new possibilities or theexploitation of existing markets. On the horizontal axis in Figure 3, the framework presents an oppositionbetween learning from the firm’s own experience or from the experience of others. Onthe left end of the axis, workers gain knowledge through their own experience,performing a set of activities and reflecting on cause-effect relationships. On the rightend, the firm learns from the experience of others, obtaining skills through acquiringother companies, recruiting experienced workers, hiring consultants and educationalinstitutions, observing, scanning, benchmarking, and imitating successful products andprocesses developed by others. Organizations are more likely to learn from directexperience when their environments change rapidly, competition is based on productdifferentiation, and the future basis of competition appears to be uncertain. On the vertical axis, the framework presents an opposition betweenexploration and exploitation, as outlined by James March (1991). According to thisview, organizations may focus their attention either in the exploration of newopportunities, or in the exploitation of known resources. Exploration involvesexperimentation with new competencies, technologies, and paradigms. Exploitationseeks to consolidate the use of well known resources and involves leveraging existingproducts, processes, and practices. Organizations differ on the degree to which they engage in exploration asopposed to exploitation. They they tend to lean towards one of these ends, because tobe successful in any of the two modalities demands intense attention and depletion ofresources. Switching between exploration and exploitation is not easy. Organizationstend to locate at the exploration end when their industry is young, major technologicalchange occurs, and competitive advantage is derived from technological leadershiprather than cost leadership (Yeung et al, 1999). Four learning styles emerge from the crossing of the two axes:Experimentation, Competency Acquisition, Benchmarking and ContinuousImprovement. The research developed by Yeung et al (1999), which engaged 411 firmsin 40 countries, shows that companies tend to rely on one of these styles to developthe capabilities that give them advantage in their competitive environments. While
27Competency Acquisition and Continuous Improvement are the most commondominant learning styles, Yeung et al (1999) obtained evidence showing thatExperimentation is the learning style that is most effective for enhancing businessperformance. It is also the one that is most closely related to innovation. This discussion is quite relevant to the central topic of this essay. The processesthat lead to innovation need to be deeply ingrained in the routines that determineorganizational learning inside organizations. In order to turn innovation into apowerful enabler of business strategy, allowing organizations to reach new answers tothe where and how to compete questions, firms need to engage progressively in theExperimentation learning style, where they commit increasing resources to try newsolutions based on their own experiences. The greatest challenge is to do thiscontinuously, resisting the pressure to abandon experimentation when early solutionsclose to the origin have been achieved. In fact, some Colombian firms find that going through the discovery processsuccessfully is one of the most difficult components of an innovation strategy. In aworkshop carried out with a group of representatives from major Colombianbusinesses, members of the Private Competitiveness Council were asked to identifytheir most urgent concerns regarding innovation. These are companies which haveformal innovation systems in place and could be considered as leaders in the countryin terms of building capabilities for innovation (Vesga, 2012). These were the mainconcerns that were discussed in this workshop: Achieving greater productivity in the discovery processes. Innovation systems within companies include discovery stages where needs are identified and creative solutions are shaped. Firm representatives expressed that these processes take too much time and are too erratic. Participants in the meeting agreed that for them, increasing the productivity of their processes at this early discovery stage is a high priority. This involves improving the methodologies used; opening larger spaces within the organizations routine for working on this stage of the process; achieving an increase in the number and quality of the experiments carried out by innovation teams; improving the
28accuracy and speed in intellectual property searches; and multiplying thenumber of innovative business models that are effectively identified eachyear. The key to progress in this area does not begin by setting newmetrics, but by accelerating experimentation initiatives. The metrics arecreated afterwards. Ensuring access to talent. At this time, the number ofpeople who have the knowledge, skills and experience required tosuccessfully lead innovation processes is very limited in Colombia. Thedifficulties in finding and bringing this talent on board are seen as asignificant barrier to expanding the scale and impact of innovation effortsby these firms. It is necessary to increase rapidly the availability of peoplewith these skills, to accelerate and scale up progress towards a greatervolume of innovation projects. Strengthening capabilities for the execution of innovationprojects. For businesses, it is very important to strengthen executioncapabilities to materialize the fruits of discovery processes. Strengtheningthe conditions for the maturation of projects and talent; reducingdevelopment time (time to market); accelerating and deepening themeasurement processes that enable the comparison of results; andhaving better mechanisms to improve the availability of detailed andfrequent geographic information; are some of the elements that wouldcontribute to the achievement of fundamental objectives. Strengthening Open Innovation activities. For the vastmajority of participants, Open Innovation has become an issue of greatimportance within strategy. For these firms it is clear that it is quiteimportant to engage with other actors from the environment, in order toadvance their own innovation strategies. The issues that were mentionedin this regard include: strengthening and deepening contact with theother actors in the ecosystem; strengthening synergies with otherbusinesses for the purposes of creation; increasing the productivity ofcreative spaces in solid, long standing relationships with universities; and
29 achieving more ambitious goals in their links with Academia and Government. A public policy that seeks to spread absorption of capabilities for innovationwould probably be wise to assume that these concerns will be widely shared byColombian firms. As more firms enter discovery processes and seek to leap away fromthe origin in Figure 2, it will be evident that a collective learning process needs to takeplace, where firms can learn from each other’s experiences and can move forward tocreate relevant metrics and apply them when appropriate. It is necessary to developinstruments that can effectively create spaces for experimentation, where firms canlearn from their own experience in reference to the experiences of others, movingquickly from observation to design, test and verification of results, sharpening theirlearning cycles. This environment should operate on the basis of a common, simple andevolving language, where the basic definitions of what innovation is and how it can bedone are easy to understand. Each firm should be able to relate quickly to thislanguage, and to visualize how these principles can be applied to reach the next step intheir own path away from the origin in Figure 2. It should always be possible for eachfirm to visualize the next step as a goal that lies within reach, regardless of the level ofthe firm’s capabilities for innovation at the outset. Bringing such a policy to reality is a demanding endeavor that cannot be solvedby one brilliant government. It requires concerted, hard work by all the stakeholders.This is where the tools and instruments of the Open Innovation framework can beuseful to achieve the desired goals of innovation policy in a country like Colombia.
30THE OPEN INNOVATION MODEL AS A SOLUTION As Henry Chesbrough defined it, Open Innovation is “the use of purposiveinflows and outflows of knowledge to accelerate internal innovation, and expand themarkets for external use of innovation, respectively” (Chesbrough, 2006). The termbecame widely used, with the most important interpretation of its possibilities andinfluence referring to the idea that businesses can access a much larger number ofideas and innovative projects if they open the gates and allow externally generatedinnovations, in different stages of development, to access their R&D pipelines. Somecompanies like Procter & Gamble exemplified this trend (Huston & Sakab, 2006). It wasessentially a way to achieve a larger output of technology-based innovative products,with a resource endowment that would be quite similar to that the past. As time passed, the concept of Open Innovation itself expanded its meanings.Chesbrough’s work moved beyond technology and studied the implications of OpenInnovation on business models and services (Chesbrough, 2006, 2010). This changedthe terrain of the discussion, from a process focused on enlarging the productdevelopment pipeline to a deeper understanding of the connections between firms,their business models and strategies, and of the essential nature of products asservices-experiences. Today, businesses are “pushing more of their business issuesinto the open innovation domain” (Chesbrough and Euchner, 2011). One of the reasons why the Open Innovation model can be so powerful is thatit accelerates learning and knowledge absorption (Van Haberbeke et al, 2007; Cohen &Levinthal, 1990). Firms differ in their ability to appreciate and exploit new knowledgegenerated elsewhere and, in this sense, they are path dependent (meaning that theirpast and their history determine what they will be able to appreciate and exploit in thepresent and the future). The discovery process that allows firms to move away from the origin in Figure2 requires an increase in absorptive capacity. In this process, firms need to rise theircapacity to know- what (to recognize and value external knowledge); know-how(assimilate and use valuable external knowledge); and know-why (understand well
31how using and commercializing external knowledge allows the firm to achieve its ownorganizational objectives). Operating within an open innovation model increases firms’absorptive capacities (Van Haberbeke, 2007), because it forces firms to expand theirspan of attention and endows them with access to larger stocks of knowledge, whichhelps them to identify more (and more varied) connections between their presentstate and possible evolution alternatives. In particular, the tools of open innovationallow firms to move faster through the discovery process. Options reasoning, forexample, allows firms to consider more alternatives, select among them and place avariety of bets while reducing the overall risk of their innovation portfolios. If it is true that firms operating under an Open Innovation framework canincrease their absorptive capacities for discovery, then many practical advantages ofhaving large numbers of firms doing the same thing should become apparent. Thefollowing are some examples: 1. In Chesbrough’s definition, Open Innovation refers to “the use of purposive inflows and outflows of knowledge”. The focus is on the flows of knowledge to and from the organization, not on the definition of what is innovation. This concept is relevant for efforts focused on R&D and also for initiatives that deal with service innovation (and other definitions in between). This, there is no need to stall on the endless question of what is an innovation or to fall prey to the traps of limited conceptualizations of innovation. The essence of the definition refers to the flow knowledge and the value that knowledge can create. Most of the stakeholders of a country or a region’s innovation policy could easily agree with such an assertion. 2. In a region endowed with an innovation policy environment focused on accelerating the spread of absorption capabilities, the key objective would be to enhance the learning and discovery processes of firms. The instruments and tools of policy would be chosen because their effectiveness at expanding the inflows and outflows of knowledge between firms, and between them and the ecosystem. Metrics, of course, are of key importance, but the most useful metrics should be defined as part of the process, not assumed to
32 be understood at the outset. The most important element is that the region should be able to foster a productive conversation among firms and policy makers regarding strategy, the assumptions that should be met in order to turn strategic goals into reality, and the role of innovation in strategy. The stronger emphasis should be devoted to clarifying the strategic issues, not to simplistic perceptions and metrics. Firms that have successful in developing powerful strategies and supporting them with strong capabilities for innovation rely in this kind of dialogue to configure activity systems and to ensure their effectiveness. An example of how such mechanism works has been described by AG Lafley, former CEO of Procter & Gamble (Lafley, 2013): “We actively fostered this approach to communication at P&G, encouraging dialogue in the strategy review sessions, in one-on-one meetings, and all the way to the boardroom. The goal was to create a culture of inquiry that would surface productive tensions to inform smarter choices. The explicit goal was to create strategists at all levels of the organization1. Over the course of a career, P&G leaders gain practice designing strategy for brands and products lines, categories, channels, customer relationships, countries and regions, and functions and technologies. The idea is to build up strategy muscles over time, in different contexts, so that as managers rise in the organization, they are well prepared for the next strategic task. As they succeed, the reward is a bigger, tougher, and more complex strategic challenge. This practice-makes-perfect approach to learning strategy explains why so many P&G alumns go on to become CEOs”. Creating this kind of environment for discussion is of critical importance in any explanation of the performance innovative firms. It is necessary to create a similar environment for discussion among the stakeholders of innovation policy. Regions and cities would be wise in “taking a page” from the innovation routines of companies like P&G and follow this approach to create solid strategy and innovation capabilities among stakeholders. The task is to induce a process of discussion and learning among actors in the policy arena that is similar to the one that takes place in successful innovative firms.* : Not italicized in the original.
33 An Open Innovation framework for policy making, validated by all the interested parties, would be an appropriate scenario to set objectives, rules of engagement and knowledge sharing mechanisms, in order to accelerate the development of innovation capabilities across firms. It may seem like a dauntingly difficult task but, surely, none of this was easy in the case of a USD$83 billon dollar sales global firm like Procter & Gamble either. 3. Solving the innovation policy metrics problem will be easier in regions that work within an Open Innovation framework. Innovation policy is caught in a dilemma when it comes to measurement: since the optimal performance of innovation policy is difficult to measure, then the system resorts to available indicators , such as the R&D metrics discussed above. These available measures quickly come to define the whole field of activity. Actions that may contribute to the optimal state, but whose effects cannot be easily measured through indicators, fall into disuse. In such a situation, a measurement bias induces suboptimal performance (Marr, 2008). The available metrics will necessarily determine how results are evaluated and how decisions will be made in the future. The fact that there are limited metrics in the present to establish progress towards an apparently fuzzy objective, such as the spread of the appropriation of innovation capabilities by firms, should not lead policy makers to forget that this is one very important objective. All firms involved should be aware of the dangers of measurement bias. This awareness is more likely to exist if firms are participating in an Open Innovation initiative than if each is trying to solve the problem on its own. 4. If metrics for the appropriation of innovation capabilities by firmsare not readily available, then the concerned regions will have to develop suchmetrics. In order to do this, both policy makers and private actors need to keepa focus in the important questions that need to be answered. Again, policyactors can adopt a tool that was developed in the space of corporateperformance management: Key Performance Questions, or KPQs. This is a toolthat allows firms to focus on the performance factors that really need to be
34assessed instead of proceeding mindlessly to the use of performance indicatorsthat may be standard practice, but do not refer to the specific needs of thesituation. By using KPQs, managers keep a focus on what needs to be discussedwhen reviewing performance. The process starts with KPQs and only thenfollows to developing indicators. Questions should follow a sequence like this:‘What do we really need to know? What information do we require? Whatare therefore the best Performance Indicators we need to collect to help usanswer our key performance questions? (Marr, 2008). Creating the appropriate environment to ask the right questions iscritical for innovation. This is how the process is described by Eric Schmidt,former president of Google: We run the company by questions, not by answers. So in the strategy process we’ve so far formulated 30 questions that we have to answer [ … ] You ask it as a question, rather than a pithy answer, and that stimulates conversation. Out of the conversation comes innovation. Innovation is not something that I just wake up one day and say ‘ I want to innovate. ’ I think you get a better innovative culture if you ask it as a question (Marr, 2008). In seeking to scale up this approach from a firm to a region in order tospur innovation, operating inside an Open Innovation policy environmentwould facilitate the process. Actors would follow the rule of focusing on howknowledge flows in and out of organizations. Proceeding from Key PerformingQuestions to new Performing Indicators should be a natural process in thisenvironment. 5. In the prevalent state of the innovation policy discussion in LatinAmerica and Colombia, most events and phenomena occurring within the firm,at the group or individual levels, are considered to be exogenous or beyond thescope of the analysis. Innovation policy assumes that the firm is monolithicentity that responds unambiguously to incentives from the environment. TheOpen Innovation view allows to move past this intellectual construction andgives policy stakeholders and firm managers the tools to openly discuss barriersto the innovation process that exist within the firm. Within the OpenInnovation framework it is possible to analyze phenomena at the firm level and
35also at the team or individual level (Vanhaverbeke, 2006). Issues such asbarriers to change stemming from team inflexibility and inertia can beexamined carefully and dealt with as an integral part of the task. This is anextraordinary advantage. It is not unusual that worthy policy initiatives failbecause the push towards action is broken when weak links insideorganizations fail, even after managers of firms have agreed to pursue thechosen path, grinding the full effort to a stop. Within an Open Innovationframework, these weak links can be explicitly considered. Complementaritiesamong actors can be summoned to action in order to solve these barriers. Allthe actors can have the necessary elements to understand and follow theadvancement of proposed initiatives and not just assume that importantblockages will be overcome in some unspecified way. 6. When firms try to create a capability for discovery, it oftenhappens that resources for this purpose are in short supply. Firms find itdifficult to assign resources to the discovery process for many reasons.Discovery is associated to ambiguity, movable goals and shifts in direction thatneed to be undertaken before a clear fit between opportunity, project, andfirm capabilities can be finally configured. Thus, it is difficult for any firm toengage in this process while at the same time excelling at the execution featsthat are needed for succeeding at day-by-day operations. Acquiring capabilitiesfor discovery can be a frustrating quest at execution-minded firms, since it isdifficult for individuals to simultaneously perform well in discovery-mindedprojects and execution-minded projects. It is difficult to assign financial andtechnical resources for both kinds of projects at the same time, because theyperform quite differently when compared using standard criteria for decisionmaking (particularly when only standard financial metrics are used). However, if a region has many firms operating within an OpenInnovation framework spurred by policy, some critical resources in theenvironment would become visible and available and could be utilized withlower costs. For example, for execution-minded companies it can be quite hardand costly to find individuals who are properly skilled and could be leaders of
36discovery processes. This happens because the human resource units at thesefirms are used to hiring individuals for execution processes and have littleexperience in selecting for discovery (where the set of required skills includesuch things as abilities for acute observation, desire to question the status quoand fluidity at creating new solutions). Their common processes are useless andthey do not know how to validate these new searches. Within an openinnovation setting, however, individuals who have acquired experiencediscovery processes would become easily visible. Small “pockets of talent”could be on call to attend temporary needs of a variety of businesses, reducingthe costs associated to search and validation for each individual firm. The samecan be said for many fixed costs. Infrastructures such as laboratories, forexample, could be shared among many firms whose demand peaks do notoccur exactly at the same time. 7. The Open Innovation model facilitates the dialogue among firms(as well as among firms and other institutions) which may be located in verydifferent positions in a continuum of innovation capabilities. Open Innovationallows for the collaboration of firms with no regard to the frequency of newproduct announcements or the degree of R&D intensity that they manage. Theframework facilitates absorption of knowledge by small firms, or by firms whoare only initiating their development as innovators, without imposing greatrequirements on the capabilities that they should have at the outset. In orderto engage in an open innovation model, firms need to do some solid thinkingabout how far have they advanced in the process described in Figure 2 andwhat kinds of goals can they achieve, given the place where they are located inthe spectrum of possibilities. In other words, firms are forced to interiorize thestate of their path dependency; this self-reflection should increase their successprobabilities of in the long term. 8. Research on Open Innovation is generating a growing inventoryof tools and instruments that can be used by firms when they search for,utilize and share knowledge on all aspects of operations that may be related toinnovation, from user-led design to guidelines for leveraging shared IPresources. This makes faster organizational learning possible, where newly
37identified problems can quickly lead to new interpretations andconceptualizations, with experimentation and testing of novel solutionsfollowing in quick sequence. 9. The analysis of real options has acquired new significance andusefulness in the context of Open Innovation. Real options analysis allows firmsto stage their financial commitments in new projects, tying disbursements tothe completion of project milestones. This creates the possibility for firms toinvest in a wider variety of projects and only follow-trough with those thatshow the highest promise. In an open innovation environment where there aremany firms, this creates new possibilities for any participant to extract valuefrom projects that do not make the cut along the development pipeline. Forexample, if a firm decides not to follow a project beyond the earliest stages ofdevelopment, because other projects in its portfolio have shown more promise,it can cede the rights to continue with the project to another firm in exchangefor a portion of the revenues that the project would attain if successful. Thisopens possibilities for new revenue streams that do not exist under a closedinnovation model, reducing the expected losses attached to investments ininnovation. 10. If a region or a cluster embraces an open innovation approach, itshould be expected that issues of governance would become more explicit -and could be dealt with through discussion and negotiation. Since an openinnovation environment allows to deal directly with issues that affect firms atmany different levels, it also allows to clarify the interests that each firm hasand creates a richer environment, with many alternatives over the table, whereeach actor should find it easier to obtain desired objectives throughnegotiation. Open innovation and real options analysis allow each participantto build more varied negotiation packages and increases the probability ofachieving positive results.
38CONCLUSIONThis essay has developed an argument favoring the use of an Open Innovationframework for public policy initiatives aimed at accelerating the absorption ofknowledge and the development of innovation capabilities by firms. Some evidencefrom the case of Colombia has been presented, but the arguments should be relevantfor several countries in Latin America.The key argument follows from the realization that a limited perspective on theproblem of innovation has lead to the use of a limited set of metrics, making it hard formany firms to understand their own position regarding innovation capabilities and toengage in a productive dialogue on the topic with policy makers. The argument statesthat this limited-perspective problem can only be solved if firms find ways toaccelerate experimentation and discovery and learn from their own and their mutualexperiences. This learning should happen faster in an Open Innovation environment,where firms can relate their own experiences to those of others and can resort toassets and knowledge developed by other firms.Capabilities for working in an open environment are diverse and hard to acquire.However, firms would become more adept at these capabilities with frequent use. Inan Open Innovation environment, collective learning should be codified and offered tonew actors. Public Policy should leverage on firms’ efforts to foster the development ofthis environment. Once the basic principles are shared and understood, policy effortsshould focus on the spread of the knowledge developed by pioneers and the toolsderived from this knowledge.Open Innovation principles could serve as a general framework for fosteringinnovation policies in Colombia and other countries in Latin America. This paperoutlines the need for such a general framework and presents some basic elements thatcould be taken into account. Developing such a framework in detail will involvesubstantial contributions from many actors, from the public and private arenas. Such afocus on collective learning may offer a productive way ahead. It is certainly worthexamining.
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