A manufacturing innovation overview: concepts, models and metrics

ABSTRACT

This paper aims at performing an overview of the Innovation notion and the selection and discussion of appropriate innovation metrics and challenges, mainly in the context of manufacturing. This review has been performed through literature, on the notion of Innovation and its classification, according to various dimensions/aspects affecting manufacturing.

KEYWORDS:

• Innovation notion
• innovation metrics
• models of innovation
• innovation in manufacturing

1. Introduction

Manufacturing companies operate in a high competitive context as they are sometimes subjected to fierce global competition in terms of new products, production technologies, new materials, legislative or organizational or business model developments and usually rely on innovation only in order to cope with the competition or rarely to obtain competitive advantage through increase in productivity (or cost reduction) and increase in other manufacturing relevant figures, such as flexibility or agility. The evolution of the literature, regarding innovation, has been exponential since the 1950’s, after the basis for the Innovation notion as have been set by Joseph Alois Schumpeter, who had stated that ‘Carrying out innovations is the only function, which is fundamental in history’ (Schumpeter 1943).

The overview of the literature has been carried out through extensive research in books, scientific papers, conferences proceedings, specialized press or websites, relevant to the notion of innovation and particularly related to manufacturing, using keywords such as ‘manufacturing innovation’, ‘innovation metrics’, ‘innovation models’, ‘innovation types’, ‘Product innovation’, ‘Process innovation’, ‘open innovation’, ‘business model innovation’, ‘user innovation’, ‘Breakthrough innovation’, ‘Frugal innovation’, etc. In addition, the search tools of ‘google scholar’ and ‘books.google.com/ngrams’ have been used for the quantification of the researched terms appearance over the past 100 years.

From the above literature research, the conclusion derived shows that although there is a huge variety of scientific publications and extended publicity regarding ‘innovation’, there was no extensive overview regarding the facets of the innovation notion and its use in manufacturing.

The scope of the current paper is to assemble the basics of the innovation notion, with all the recent developments in a theoretical research, along with its practical applications to manufacturing, providing a useful overview on manufacturing innovation.

2. The innovation notion

A comprehensive definition of innovation is “The process of translating an idea or invention into a good or service that creates value or customers to be paid for it. In order for an idea to be referred to as innovation, should be replicable at an economical cost and should satisfy a specific need. Innovation involves the deliberate application of information, imagination and initiative for the derivation of greater or different values from resources, including all processes by which new ideas are generated and converted into useful products. In business, innovation often results when the company’s ideas are applied in order for the customers’ needs and expectations to be further satisfied.¹

More modern approaches for a classification of innovation types can be distinguished according to its properties; the application area or even the procedure, the extent, the timing or even its sources are widely dispersed among the perspectives of various scholars or business consultants (Garcia and Calantone 2002).

2.1. Classifications of innovation types in relation to manufacturing

An overview of various classifications of selected Innovation types, relevant only to manufacturing, is shown in the following Figure 1:

Figure 1. Overview of the classification of innovation types relevant to manufacturing.

According to the Field of Application Process, Innovation refers to the implementation of a new or significantly improved production or delivery method (including significant changes in techniques, equipment and/or software) for the acquirement of a new or the increase of the current production or service capability, in a manufacturing or logistical system, which must lead to added value for the firm (company value) and its value chain (value chain value) (Romero et al. 2017)

According to its impact, Innovation can be also distinguished into the following categories (Bogers and West 2014):

(1) Breakthrough, that involves pushing the boundaries of science and technology for its implementation in a manufacturing system.

(2) Sustaining, that improves the performance of established manufacturing systems. Sustaining technologies are often incremental and not disruptive to markets or industries, although sometimes the opposite is possible (KAIZEN) (Kaizen 2017). Furthermore, the term ‘Permanent Innovation’ describes the process of innovating continuously, as a matter of strategy, method, and habit (Morris 2011).

(3) Disruptive is a technological innovation that eventually overturns the existing dominant technology or the status quo in the market. They can be broadly classified into lower-end and new-market disruptive innovations. A new-market disruptive innovation is often aimed at non-consumption, whereas a lower-end disruptive innovation is aimed at mainstream customers, having been ignored by established companies.

According to its extent, Innovation can be also distinguished into the following categories (Morris 2011):

• Incremental innovations (or continuous innovations) that are generally modifications to the existing products and services that improve functionality, reduce cost

• Technology breakthroughs are significant or radical departures from whatever is already available on the market. They are sometimes referred to as ‘discontinuous innovations’ or ‘rupture innovations,’ because they disrupt the marketplace, which is the desired effect, or because they disrupt the organization coming with them, which is usually not the goal

The above classification is very important to the decision-making process of a manufacturing firm towards the management of Innovation. These decisions have a rather strategic characteristic and can affect the company’s existence in the long run, especially if a company falls into the trap of being unable to foresee the implications of disruptive technological innovations in their market (Christensen 1997)

Further to the above, two more categories of a technical innovation have been suggested: one is the changing of the technology system that affects certain industries and the other is the changing of the technoeconomic paradigm that has a broader effect on the economic and societal environment. (Kodama 2004)

The terms of modular innovation (complete redesign of core components, while leaving linkages between the components unchanged) and architectural innovation (changes the nature of interactions between core components, while reinforcing the core design concepts) are also used to characterizing the extent of an innovation. (Henderson and Clark 1990)

A classification of the term Radical (or disruptive) Innovation is (Dyer, Godfrey, and Jensen 2016):

• Low-end disruptive innovations

• High-end disruptive innovations

• Application of mass customization

According to the timing of an innovation’s adoption or diffusion, the manufacturing companies can be classified as (Rogers 2003):

• Innovators (2.5%), who are venturesome risk-takers, serving as gatekeepers for those who follow,

• Early Adopters (13.5%), who are opinion leaders, being the first within their group to be adopted, and are willing to maintain their position by evaluating innovations for the others,

• Early Majority (34%) including those users who were more watchful and mooted the adoption of an innovation,

• Late Majority (34%) being adopted after the mean (average) part of the population, with its main characteristics being scepticism and cautiousness,

• Laggards (16%) that always doubt the adoption of an innovation at first, but eventually succumb to peer pressure (Wani and Syed Wajid 2015).

The adoption of ‘radical’ manufacturing technologies (i.e. those that changed competitive dynamics in the industry) was a significant predictor of survival. Bundles of adopted technologies and a comprehensive technology set were associated with increasingly high likelihoods of firm survival (Sinha and Noble 2008). The so-called ‘not invented here syndrome’ finds perfect application to many manufacturing companies’ failures to meet the contemporary needs, showing a high level of negative attitudes to the acquisition and sharing of knowledge (Burcharth and Knudse 2014).

Currently, in developing countries or in sustainable conscious developed markets, the idea of ‘frugal innovation’ emerges as a new business model that aims at reducing the complexity and the total lifecycle costs of a product, while providing high value, targeted and affordable solutions to customers of different, and possibly divergent, markets (Mourtzis 2018). In India, the term ‘Jugaad (or hack) Innovation’² may be also applied to finding a low-cost solution to a problem in an intelligent way. In advanced economies, the term dematerialization is referred to as innovation seeking to “do more (output) with less (input)” (Chryssolouris et al. 2018).

An ‘innovation’ in the way that novelties are brought to light, is the involvement of ‘non-experts’ in the development or even the production phase. The so-called “Maker’s Economy” that uses the widely available technological development and information technology (Anderson 2013; Piller 2013), is expected to revolutionize the way products are made and conceived (von Hippel 2014) by involving the user more and more in the design or even the manufacturing process.

The process of innovation is being considered in contemporary manners more than a plain linear process (Godin 2005) and since good ideas are rather rare, company leaders tend to acquire radical approaches concerning innovation management by adopting the ideas of ‘open innovation’ (Chesbrough 2011) or “user innovation” (von Hippel 2014), for compromising the failure sources in the various stages of innovation path. Even the notion of free innovation (von Hippel 2016) has also been proposed. These ideas contradict to the way that the intellectual capital of an organization is being managed and new paradigms of knowledge generation, sharing and management are proposed. Manufacturing leaders are also in the hunt of recognizing or hiring ‘Intrapreneurs’ (Tripathy 2006) that will be able to manage the implementation of the new ideas in the complex of a manufacturing system.

2.2. Models of innovation process

Modelling of the innovation process is essential for the conception of specific and useful metrics. The attempt for the modelling of the innovation process, has evolved from the linear ones of the first generation (1950’s technology push), the second generation (1960’s market pull), the third generation (mid-1970’s interactive pull), up to the non-linear models of the fourth (1980’s integrated – chained) and the fifth (1990’s integrated, flexible, IT enhanced) (Žižlavsk 2013) and beyond the models, such as the Diamond Model, the idea management model, the Innovation Funnel Model, the Ten Types of Innovations Model, and the model of Dulkeith and Schepurek (Hao, van Ark, and Ozyildirim 2017) or the extended innovation funnel (Hobcraft 2011). The possibility of ‘standardizing’ the very complex procedure of innovation (sometimes described as art) (Kawasaki 2014; Heleven 2012) is considered being a special sector both in the literature and the consulting industry.

Most importantly, as always, for the maximization of an organization’s outcome, is the optimization of its entire structure or ‘business model’; the way that the organization is configured so as to meet its ‘customers’’ current or future needs (Morris 2009), building the contemporary concept of the extended manufacturing systems.

3. Metrics for innovation in manufacturing

In order to be able to ‘measure’ something, it is essential that one should understand its nature and the attendee of the result of this measurement, according to the extent of the Innovation System’s model, currently described as Penta-helix model (Hill 2016) (Figure 2).

Figure 2. The Penta-helix model © OSMOS Network (Hill 2016).

The ‘attendees’ of the innovation ‘measurement’ can vary and could be one of the following:

• Economy Policy makers (at regional or country level)

• Investors interested in macroeconomic or microeconomic data

• Financing Organizations

• Companies’ strategists (CEO’s, CTO’s, etc.) or managers (Project managers, CFO’s, Investment officers, etc.)

• Future Technologies consultants

The ‘content’ of the innovation ‘measurement’ also varies, as it could be:

• Economy’s innovation performance at regional, country or sectoral level

• Economy’s innovation potential or capability at regional, country or sectoral level

• A Company’s (or a departments) innovation performance

• A Company’s (or a departments) innovation potential or capability

• An existing product’s or manufacturing system’s innovation performance

• A new product’s or project’s innovation potential and its return prediction

The fact that innovation is a rather complex procedure and its ‘modelling’ is not straight forward, leads to a variety of possibilities in the conception of the appropriate indicators, mainly in the form of Key Performance indicators (KPIs).

The aspects to be distinguished, regarding the selection and use of indicators, can be the Macro (Country or similar economy level), Meso (region or metropolitan area or sectoral economy level) and Micro (economic unit level – household or business) ones with the latter to be mostly affecting manufacturing.

he above ‘classical’ political economy approach could be transferred to the manufacturing organization analogue, where macro could be at ‘company level’, meso could be at ‘manufacturing department level’ and micro could be at ‘project level’.

In general, the existing tools that affect manufacturing can be categorized as follows:

• Innovation capacity evaluation of a company or a department

• Innovation capacity evaluation of personnel

• Innovation performance (or quality) of a company or a department

• Evaluation of a (new) process regarding its innovativeness

• Innovation performance of a new process or project and its return prediction

The tools that can be mainly used:

• Investment and risk evaluation metrics

• Simple or composite indicators for the characterization of intangibles

• Indirect metrics

A very important basis for an organization’s ‘proper’ evaluation of its innovation performance, at micro level, is the understanding of the innovation process (or model) that it is being applied or the one that should be applied, according to the particular characteristics of an industry, company’s size or type and business environment particular characteristics. The current approach to the innovation process modelling is no longer linear, as it comprises many, sometimes volatile components.

In the literature, there have been more than one definitions for the term ‘innovation performance’, namely: ‘a measurement of the performance of an adopted new approach or a new measuring criterion to gauge its organizational performance’, ‘the propensity of a firm to actively support new ideas, novelty, experimentation, and creative solution’, ‘the annual growth rates of innovation input and output, knowledge stock, and research productivity’, ‘how fast, how well ideas are implemented and how much value is created’ or ‘provisions for assessing the effectiveness of the innovation activity, in terms of business success’ (Lendel and Varmus 2013).

Central factors that influence the innovation performance of an organization are (a) strategy, (b) structure, (c) culture and (d) external environment. The importance of gauging the innovation performance is twofold. First, the information having derived from measurements, serves as feedback to a firm’s current standing in innovativeness. Second, the gaps in performance trigger a systematic process of continuous improvement.

An overview of the selected metrics classification, affecting manufacturing, can be seen at the following Figure 3.

Figure 3. Classification of Innovation Metrics at the microlevel.

3.1. Innovation performance index and organization’s innovation maturity level

Without performance measurement, the process of innovation will not be managed effectively and any improvement will be sporadic (Lendel and Varmus 2013).

As there is not ‘just one size that fits all’, the ‘maturity’ of an organization, regarding its way of operation in innovation, can be classified into five levels: Chaotic, Insufficient, Acceptable, High and Excellent.

Although the innovation process is multifaceted and complex, the idea of using an overall index, mainly serving internal purposes, it is widely used and it is very desirable to have a value that would be representing the overall level of innovation performance in a business: the innovation performance.

In determining the method of calculating the innovation performance index, weights (v) have to be conceived in order to represent the importance given to the elements, which affect the company’s innovation and its performance and can be calculated as follows:

(1) $v_i=\frac{w_i}{{\sum }_{i=1}^N{w}_i}$(1)

where:

vi – weight of the i-th element

wi – measure of the importance of the i-th element

N – Number of elements affecting the company’s innovation performance

The index of innovation performance in the company is calculated by the following formula:

(2) $\mathrm{I}{\mathrm{p}}_{\mathrm{i}}=\frac{{\sum }_{\mathrm{i}=1}^{\mathrm{N}}{\mathrm{v}}_{\mathrm{i}\mathrm{j}}{\mathrm{x}}_{\mathrm{i}\mathrm{j}}}{10{\sum }_{\mathrm{i}=1}^{\mathrm{N}}{\mathrm{v}}_{\mathrm{i}\mathrm{j}}}\ast 100\left[\mathrm{\%}\right]$(2)

where:

Ipi – index of the innovation performance of i-th Company

vij – weight of the i-th element

xij – performance achieved by the i-th element

10 – refers to the range used (scale 1–10)

N – number of elements affecting the company’s innovation performance.

The overall index of the innovation performance is the average of all of its individual indices using the index of innovation performance, it is the gradual improvement that is sought after by reducing the difference between the rate of importance of various elements and evaluating their performance.

The first step in measuring the innovation performance (IP) in manufacturing businesses is the formulation of appropriate elements (criteria). Based on these criteria and on assessing the importance of their achievement, it is impossible to be ascertained as to what extent the company is ready to deal with innovation successfully.

Where are the areas of improvement, what are the priorities and what elements are most important, from the management’s perspective, in achieving innovation performance? The latter is affected by five basic (key) elements and it can be written in the form of a function with five affecting variables:

(3) $I_p=f\left(A_i,I_{BE},P_D,I_{PM},H_R\right)$(3)

where the elements together with a description of covered activities are:

A_i Approach to innovation: Clearly defining the vision and mission of the business.

I_BE Interaction with the business market environment: The extent of the effective use of partnerships and investigation into new opportunities.

P_D Product development: A certain percentage of the business income is from new or improved products/services.

I_PM Innovation process management: the established mechanisms for the selection of good business ideas and processes to allow for the realization of innovative projects. This includes cost savings due to process or to the manufacturing system’s improvement.

H_R Human resources: The extent that a business structure provides ample decision-making capabilities for the implementation of innovative projects at every level.

A comparative table (Table 1) on the basis of its innovation performance index is the following (Table 1):

3.2. Sectoral innovation dimensions

The industry sector is also important for the selection of relevant measures (Adams et al. 2008), although some common ones can be proposed in order for a cross-sectoral benchmarking to be achieved. Measures and their definitions, being relevant to two main selected manufacturing sectors are:

A.Aerospace and the defense sector

• Financial performance: Profitability from new products and income generated from patents and licenses

• Technology development: Number of patents filed, licenses, etc.

• Knowledge utilization: Proportion of new knowledge assets (<3 years old) incorporated into new products or processes

• Exploitation of knowledge stocks over time: Returns from products/processes incorporating their own patents >5 years old, not having been used before.

• Process improvement: New Product Effectiveness Index = (Total value of engineering output/Cost of engineering department) * 100%

B.High-tech manufacturing sector

• Product advantage: Extent to which the product/service is superior to the competing products, in terms of meeting customers’ requirements

• Strategic importance of innovation: Extent to which strategic objectives have been met by the innovation

• Innovativeness: Number of patents, new product ideas, new product launches

• Financial performance: Proportion of sales and profits from new products less than n years old

• Business performance: Number and value of new customers acquired from the innovation and, new market niches entered

An overview of the use of various measurement categories, per industry sector, is depicted in Appendix A (Table A1 Overview of the use of the various measurement categories).

3.3. Funnel model approach

According to the innovation model concept utilized, useful tools along the stages of the innovation process can follow the concept of the funnel model (Morris 2008). The funnel model distinguishes the innovation procedure in nine stages that are:

(INPUT) −1: Strategic Thinking, 0: Portfolio Management & Metrics,

(PROCESS or THROUGHPUT) 1: Research, 2: Ideation, 3: Insight, 4: Targeting, 5: Innovation Development, 6: Market Development (or application area in the case of manufacturing) and

(OUTPUT) 7: Selling (or application in the case of manufacturing)

For each of the above stages, certain Qualitative Metrics, Provocative Questions and Quantitative Metrics are conceived. Thus, a comprehensive metrics system is built for the entire innovation pathway.

The entire metrics system is presented in Appendix B (Table B1, The stages of Innovation process and adequate metrics).

Table 1. Levels of innovation performance index(Lendel and Varmus 2013).

Level	Index of innovation performance (%)
Chaotic	0–30
Insufficient	31–50
Acceptable	51–80
High	81–90
Excellent	91–100

Table 2. Innovation Readiness Level (IRL)/Key aspects (Tao, Probert, and Phaal 2010).

	Technological development				Market evolution
IRL/Key aspects	Pre-IRL	IRL 1 Concept	IRL 2 Components	IRL 3 Completion	IRL 4 Chasm	IRL 5 Competition	IRL 6 Changeover/ closedown
Technology		Potential improvements of existing technologies or products identified and reported; Technology feasibility confirmed For radical innovation: Determine the innovation is radical, Unique advantage identified; Progressive identification of technical goals-	Individual components tested; Prototypes demonstrated; IP protected	Actual system demonstrated; External test completed; IP protected; Technology/product documented; Launch	Expertise formed; General availability to the market; Aftersales support	Lower R&D activities; Technology maintenance enabled; Technological service provided	Re-innovate or exit
Market	On-going market research; Identify and develop the opportunities	Market research conducted; Working with leading customers; Customer needs and demands observed For radical innovation: Locate the initial market	End-customer identified; Detailed market launch plan issued	Specific needs and requirements of customers known; Market segment, size and share predicted; Pricing & Launching issued	Positioning in the market; Business model established; Customer intimate marketing (feedback); Competitors identified; Partnership is an option to break into market	Products differentiated; Service and solutions provided; Periodical review conducted; Business model refined; Partnership is an option to compete	Declining market confirmed; Market research conducted for approval to reinnovate or exit
Organization	For radical innovation: Place responsibility in an independent organization-	Strategy fit confirmed Informal, loose structure (mainly R&D team) For radical innovation: Define the strategic significance of the For radical innovation: Free communication channels-	Business analyzed and plan issued; Key individuals involved	Formalizing organization	Formal organization established	Improved effectiveness and cooperation; Necessary restructure made
Partnership		Potential partners identified	Partners selected; Calibration established	Partnership formally established	Cooperation within dynamic network; On-going management		Cease partnership (Academic partners sought)
Risk		Technology risk considered	Technological risk assessed (alternative solution considered); Market risk assessed; Organizational risk considered (investment plan initiated and investment started)	Technological risk assessed; Organizational risk assessed (profit predicted; large investment issued)	Organizational risk periodically assessed (especially financial indicators)	Organizational risk periodically assessed (especially financial indicators)	Re-innovate or exit considered; Changeover or closedown plan issued

Table 3. Integration Readiness Levels (Sauser et al. 2010).

IRL	Definition
1	An interface (i.e. physical connection) among technologies has been identified with sufficient detail to enable the relationship characterization
2	There is some level of specificity to characterize the interaction (i.e. ability to influence) among technologies through their interface
3	There is compatibility (i.e. common language) among technologies for the orderly and efficient integration and interaction
4	There is sufficient detail in the quality and assurance of the integration among technologies
5	There is sufficient control among technologies necessary for the establishment, management, and termination of the integration
6	The integrating technologies can accept, translate, and structure information for their intended application
7	The integration of technologies has been verified and validated with sufficient detail to be actionable

Table 4. Manufacturing Technology Readiness Levels (Peters 2015).

MTRL	Definition
1	Manufacturing principle described
2	Concept of machinery equipment to run the process in series production described; general EBITpotential estimated; interaction with material analyzed
3	Manufacturing principle tested (e.g. in laboratory); impact on product design described
4	Technology capability proven; material proven
5	Concept of plant and production line designed (incl. capacity planning); suppliers identified; EBIT potential further validated
6	Series capability proven
7	Suppliers and materials certified
8	Low rate production demonstrated (pilot run)
9	Start of (series) production
10	Overall equipment effectiveness at comprehensive level (e.g. C85% as benchmark)

Table 5. A model of four types of MPI (Yamamoto and Bellgran 2013).

Area of focus	Structural	MPI type I e.g. Install new production equipment externally available	MPI type III e.g. Develop new production equipment and apply it in a factory
	Infrastructural	MPI type II e.g. Introduce available work methods such as Six Sigma and Lean.	MPI type IV e.g. Develop new work methods and apply them in a factory
		Locally innovative	Radically innovative
		Innovativeness of change

Table 6. Major approaches to change within the manufacturing organization (Dooley and O’Sullivan 2000).

Decade	Approach	Early authority
1690	Division of labor	Adam Smith
1890	Scientific management	Frederick Taylor
1900	Mass production	Henry Ford
1920	Industrial engineering	F. Gilbreth and F. Taylor
1930	Human relations movement	E. Mayo
1950	Japanese quality movement	J. M. Juran and W. E. Deming
1950	General systems theory	K. Boulding
1960	Materials requirements planning	W. Orlicky
1960	Socio-technical design	E. L. Trist
1970	Manufacturing resource planning	O. Wright
1980	Factory focus	W. Skin ner
1980	Total quality	P. Crosby
1980	Just in time	T. Ohno
1980	Computer integrated manufacturing
1980	Optimized production technology	E. Goldratt
1980	ISO 9000	NSAI
1980	World class manufacturing	R. Schonberger
1980	Benchmarking	Rank Xerox
1990	Lean manufacturing	Jones and Ross
1990	Learning organisation	P. M. Senge
1990	Business process reengineering	M. Hammer and T. Davenport

3.4. Return (or Restraint) On Investment (Innovation)

Innovation is a company investment, as it requires the occasional allocation of very serious amounts of resources (financial, equipment and personnel). The classic approach to the evaluation of an investment is the use of tools of the Net Present Value (NPV), the Return on Investment (ROI), the Cash Flow ROI, the Internal Rate of Return (IRR) or the Payback Period (Erményi 2015).

As short-term pressure for results, leads to the trap of sacrificing the long-term health of organizations, any innovation work-in-progress should not be gauged according to the standard ROI calculations, since many times, the innovative spirit has been demolished by the question, ‘what would the ROI be on a project that was far too young to be known, resulting in killing it’. From the perspective of innovation killing, it should be noted, ‘ROI’ stands for ‘Restraint On Innovation’ rather than ‘Return On Investment.’ (Morris 2011)

This is due to the fact that the specific calculations require the knowledge of both flows of value (outgoing and incoming) and if the expense flow could more or less be forecasted, the benefits of the development of a totally new market would be rather impossible or very difficult. (Chang et al. 2013)

An important issue is also that future cash flows of the existing applied configuration of a technology or technology mix is considered being stable and is the baseline for any proposed innovation that will change a company’s status quo. Following the Parmenides fallacy³ concept, the reality is that any future income for the ‘doing nothing’ scenario is diminishing for reasons mainly connected to the evolution of the market or the actions of competition. This is depicted in Figure 4 (Christensen, Kaufman, and Shih 2008).

Figure 4. The future income for the ‘do nothing’ scenario (Christensen, Kaufman, and Shih 2008).

These problems have been addressed with the use of probabilistic tools for the forecasting of future revenues, having derived from a project. However, these models do not predict the future, since the basis of the probability theory is that the definition of certain scenarios and their probability are evident. Nevertheless, in the case of valuating innovation, the future is most of the times unknown and is characterized by uncertainty.

It is important that the Innovation Manager of a company support his/her idea on tools and use the language that is usually understood by (Chief) Financial Officers, in order to provide them with the ‘green light’ for the particular project or even strategy. In contemporary businesses, the role of the (C)FOs tends to become more strategic than a mere accounting function and an important link of the innovation decision-making chain. (Doraisamy 2017)

3.5. Return on product (process) development expense

An approach to the quantification of the feasibility of the innovation efforts is the application of the method of the ‘Return on Product Development Expense or RoPDE™’ (Malinoski and Perry 2011), which through using the company’s available data can cover the (C)FO’s demands, as it can:

(1) be derived from standard accounting data

(2) serve, at multiple levels as a drill-down measure: (1) As a Tier 1 (enterprise) and Tier 2 (business unit) strategic measure, (2) As an operational measure of innovation performance of a product/service/program, (3) As a measure on a single innovation project

(3) be integrated into any stage gate system or project life cycle management process

(4) be a more powerful measure than a traditional ROI approach, without requiring any additional accounting systems or reports. It also alleviates the traditional disputes over allocations and the treatment of expenses related to innovation

The RoPDE, is a comprehensive KPI (key performance indicator) for gauging the performance of a product/service innovation and development. To establish the RoPDE’s thresholds, a comparison is made with the profitability metric, such as Operating Income Margin, EBIT or EBITDA (Earnings Before Interest, Tax, or/and Depreciation, Amortization).

On an enterprise balanced scorecard, ‘Improve Product/Process Innovation’ would be gauged via an aggregate version of the RoPDE charted by fiscal periods and can be compared with an acceptable range of Operating Income Margin of 0–10% (0–10% is a typical range which would be adjusted for the context of each individual business).

The RoPDE is calculated by using the following formula:

(4) $\mathrm{R}\mathrm{o}\mathrm{P}\mathrm{D}\mathrm{E}=\left(\left(\mathrm{G}\mathrm{M}-\mathrm{P}\mathrm{D}\mathrm{E}\right)\right)/\mathrm{P}\mathrm{D}\mathrm{E}$(4)

where

GM is the Gross Margin and may also be called gross profit, determined after the cost of sales is subtracted from the revenue. The cost of sales or the cost of goods sold (CoGS), normally includes the material, labor and overhead, associated with delivering a production unit and can be adapted to Government and NonProfit accounting standards.

PDE is Product/process Development Expense and will typically include the engineering, technician, product marketing and associated management labor expense, fully burdened (benefits, facilities, IT, depreciation).

The RoPDE can be also used as an operational measure, throughout the stages of the innovation process. During the development and implementation stages of innovation, the RoPDE can be used in order to monitor the effectiveness of individual products/services/programs as compared to the aggregate (e.g. compared to how the organization’s entire portfolio of innovative initiatives is performing) as well as to the acceptable performance threshold, based on the Operating Income Margin (OIM).

In the Ideation, Evaluation, and Selection phases of innovation, the RoPDE can also be used for the evaluation of individual innovation opportunities under consideration. By applying an expected gross margin percentage, the planned RoPDE can be established and charted against an acceptable threshold. As the execution of the plan progresses, the actual PDE and the sales revenue can be compared with the plan, in order to be determined whether or not the RoPDE trajectory will meet the financial performance expected.

3.6. Kano Model analysis

As customer’s satisfaction is one of the most important metrics for a company’s success, the Kano Model (Developed in the 1980’s by Professor Noriaki Kano) of Customer (Consumer) Satisfaction, tries to classify product attributes, based on the way they are perceived by customers and their effect on them (Verduyn 2013). These classifications are useful for the guidance of design decisions, in that they indicate when a commodity is good enough, and when more of them would be better. The model though, can also be applied to other innovation activities. Obviously, the same is relevant if we substitute the term ‘Product’ for the term ‘Process’.

Figure 5. The KANO model (Verduyn 2013).

The Kano Model is useful to project activities that Identify customer requirements, Determine functional requirements, Develop concepts and Analyze competitive products (or processes in the case of manufacturing)

Other tools, in conjunction with the Kano Model, are useful for Eliciting Customer Input, Prioritization Matrices, Quality Function Deployment, Value Analysis.

The Kano Model of Customer satisfaction (Figure 5) divides product attributes into three categories: threshold, performance, and excitement. A competitive product meets basic attributes, maximizes performances attributes, and includes as many ‘excitement’ attributes as possible, at a cost that the market can bear.

Threshold (or basic) attributes are the expected attributes or a product’s ‘must’ without providing an opportunity for product differentiation. Increase in the performance of these attributes provides diminishing returns in terms of customer satisfaction; however, absence or poor performance of these attributes results in extreme customer dissatisfaction. Threshold attributes are not typically captured in QFDs (Quality Function Deployment) or other evaluation tools, since the products are not rated on the degree to which a threshold attribute is met; the latter is either satisfying or dissatisfying. The more the performance attributes are the better it is, because they generally improve customer satisfaction. Conversely, lack in a performance attribute or a weak one, reduces customer satisfaction. Most of the customers’ requirements fall into the category of performance attributes. The latter will form the weighted requirements against which the product concepts will be evaluated.

The price, which any customer is willing to pay for a product is closely associated with the performance attributes. Excitement attributes are uncharted and unexpected by customers, but can result in high levels of customer satisfaction; however, their absence does not lead to dissatisfaction. The excitement attributes often satisfy latent needs – the customers’ real needs, which they are currently unaware of. In a competitive marketplace, where manufacturers’ products have similar performance, the excitement attributes that address ‘unknown needs’ may bear a competitive advantage.

The products have often got attributes that cannot be classified according to the Kano Model. These attributes are often of little or no consequence to the customer and do not constitute a factor in consumer decisions.

The information obtained from the Kano Model Analysis, specifically regarding performance and excitement attributes, provides valuable input for the Quality Function Deployment process and has been developed in usable software tools (Rashid et al. 2010) or multidimensional models (Ben Rejeb, Boly, and Morel-Guimaraes 2008) for the evaluation of a product during the critical Front/End phases.

Furthermore, especially for the manufacturing sector’s products, other tools have been developed for feedback gathering from the customers or the users via modern equipment, such as mobile devices that support 3D animation or even VR (Mourtzis et al. 2018).

3.7. Innovation readiness level

Based on the existing theories, the approaches to managing an innovation process is more focused on the technological development phase, such as the Stage-Gates Game Plan (Cooper 2010), the Technology Readiness Levels (TRL) or the System Readiness Level (SRL) (Sauser et al. 2006). As these theories do not embrace the entire lifecycle of the technological innovation, from inception to obsolescence, the new approach of Innovation Readiness Level (IRL) (Tao, Probert, and Phaal 2010), as a model framework, which separates the comprehensive lifecycle of innovation into six phases (readiness levels) and addresses the management of the process of innovation by considering five key aspects. The IRL framework is intended to be used as a management tool of the process of innovation. In general, IRL is a descriptive scale, rather than a prescriptive one and its essential feature is the cross-functional collaboration.

The six innovation ‘phases’ of IRL are: Concept, Components, Completion, Chasm, Competition and Changeover/closedown

A detailed framework that focuses on an incremental or a radical innovation project can be seen at the following Table 2.

3.8. The integration readiness level of a technology and manufacturing technology readiness level

Building on the Technology Readiness Level as originally developed by the National Aeronautics and Space Administration (NASA) for the rating of technology readiness for possible use in space flight, the concept of Integration Maturity Metric (IMM) which leads to seven Integration Readiness Levels has been developed  as shown in Table 3.

3.9. Manufacturing Technology Readiness Level

The TRL concept has also been extended to meet contemporary evaluation issues in emerging manufacturing technologies, such as Quality aspects, Flexibility aspects (volume/scalability and variants) and economic aspects (Capacity planning or financial performance such as company’s EBIT) (Peters 2015) into a ten Manufacturing Technology Readiness Level model as shown in Table 4.

3.10. The Innovation Readiness Model – Innovation Readiness Assessment

A practical answer to the question whether companies are able to innovate or to effectively respond to competitors’ innovations is provided by a unique and specialized niche of the business consultancy industry, which based on theoretical models of the innovation process, provides a practical examination or organization assessment. This is performed by creating composite indexes, comprising several aspects of the complex innovation process, usually through the utilization of on-line innovation assessment tools.

A well-founded approach is the ‘Berkeley Innovation Index’⁴ which focuses on the factors that impact innovation: (a) Strategy and Leadership, (b) Innovation Culture at an Organizational Level, (c) Company Operations and Measures across Functional and Tactical Areas, (d) the ‘Mindset’ of a Company’s Individuals and (e) Tactical measures.

It is worth recognizing that innovation metrics are often past-oriented and do not give a correct overview of the future abilities of the firm to be innovative.

3.11. The full value approach

There exists a paradox that even if the value of an innovation is recognized as a multi-dimensional concept, the literature often focuses on a specific dimensional value – often financial – and neglects the others. The concept of ‘full value’ – in analogy with the ‘full cost’ concept – comes as an integrative index to define the value of an innovation (Maniak 2010). This particular approach finds very sound ground at ‘projectified’ firms that offer complex product systems (CoPS) namely, those of the automotive or the aircraft building industries, since they have to carry out internally a sequence of complex projects for the development and selling of such products.

The ‘full value evaluation framework’ is an integrated view of the value of a specific innovation for the project-based organization that designs and launches it on the market and consists of the following dimensions: Direct profit, generated by the feature of the first product or for future uses, Value of the product, due to its enhanced features, Volume of the product sales, Brand value increase, Intellectual property to be used for internal and external purposes, Competence building in the company that will mainly affect future projects. This framework is rather a ‘mapping’ and not a ‘measurement’ framework yet and could be further developed with financial data.

Another important aspect is that of the timing that the valuation takes place, since according to the cycle of diffusion of innovation (Rogers 2003), the importance (weight) of each valuation dimension differs and the ‘full value’ has a rather dynamic character.

The secondary effects of innovations upon an organization may be greater and more profound than those related to their immediate application. These may be impacts on the value, having derived from any changes to the organization, its structure, culture, markets, other innovations, and client or supplier relationships.

Lastly, the ‘value of failure in innovation’ should not be neglected (Townsend 2010) as there is a variety of reasons why an innovative idea never becomes realized in the marketplace.

4. Innovation in manufacturing systems

Manufacturing systems can be uniquely classified, because they show certain particularities regarding the development and adoption of innovation, due to the fact that they are important, complex, expensive and difficult to replace systems (Chryssolouris 2006). Furthermore, the current developments for the manufacturing systems towards ‘mass customization’ (Mourtzis, Doukas, and Psarommatis 2013) and the developments as described, under the term ‘Industry 4.0’, make the use of metrics even more necessary.

If seen from a process perspective, product innovation (or development) and production innovation (in equipment or processes), follow more or less, independent pathways that are only synchronized through respective project milestones (Vielhaber and Stoffels 2014)

Business leaders and policy-makers have to keep track of more than 60 technologies and philosophies, impacting production systems today and should have the following considerations when implementing technologies (World Economic Forum 2017) and have to answer to the following groups of questions:

• Level of Integration for design engineering, for marketing and concept proof, for prototyping, for scaled production alongside traditional processes, for In stand-alone factories, for vertical integration and Make vs Buy decisions

• Adoption speed regarding the questions: Start from scratch and develop expertise? Acquire an existing player? A partner with a technology producer? Create a dedicated group for implementation within the firm?

• Organizational structure alignment regarding the questions: Should we adjust as we learn? Should we realign? Should there be a shift in the structure?

The importance of a company’s manufacturing system has led to numerous approaches for the implementation procedure of changes (innovations), in manufacturing systems which should fulfill the following challenges (Fornasiero and Carpanzano 2017):

• Close the loop between design and production to enable customer-driven manufacturing

• Support product customisation to include consumer tastes and requirements for functionalisation aspects in design and production

• Changing manufacturing technologies for small series and customised production

• Increase vertical and horizontal integration at factory and value chain levels

• Integrate companies along sustainable supply networks to ensure agile value chains

Align innovation at product, process and network levels to assure easy reconfiguration of production systems and value chains.

Especially the European Commission in order to meet the challenges and at the leading innovations development, towards intelligent manufacturing systems, has coined the public–private partnership (PPP) of the Factories Of the Future (FoF) (Jardim-Goncalves, Romero, and Grilo 2017), where the variety of research fields has been coordinated. Similar initiatives have been developed in various broader or regional territorial areas such as the ‘Massachusetts Manufacturing Innovation Initiative’,⁵ the EU initiative to digitalize the manufacturing industry (I4 MS),⁶ the USA’s National Network for Manufacturing Innovation (NNMI)⁷ or the ‘Made in China 2025’⁸ strategy. Important approaches, regarding innovation in manufacturing, are presented below.

4.1. Manufacturing Process Innovation

A production process is the system of process equipment, work force, task specifications, material inputs, work and information flows, etc., that are employed for the production of a product or service. (Utterback and Abernathy 1975)

The manufacturing process innovation follows the definition of process innovation, an organization-wide effort that involves fundamental rethinking and radical redesign of manufacturing-related processes and systems to achieve dramatic improvements, in manufacturing performance measures such as cost, quality, service, and speed. In MPI, the changes are made not only in the processes of transforming raw materials into products, but also in other support processes and systems related to them; for instance, production planning, logistics, purchasing, administration, engineering, and management. Since MPI is an organization-wide effort, it is usually conducted in a form of a project or an initiative. The Manufacturing Process Innovation (MPI) follows the Phases of activities (Yamamoto and Bellgran 2013):

1. Preparation: Securing management commitment, identifying processes to be improved, aligning with corporate and business strategies, establishing process vision, setting stretched targets, forming a promotion organization and/or a steering committee, formulating projects, providing education

2. Design: Analyzing focused processes, exploring alternatives, designing new processes, prototyping and evaluating new processes

3. Implementation: Implementing new processes, training employees, monitoring performance measures, continuing improvements

The Manufacturing process innovation can be two dimensional, regarding the ‘area of focus’ (structural or infrastructural) and the ‘Innovativeness of change’ (locally or radically innovative) and can be classified into four types  as shown in Table 5.

MPI type I (structural – locally innovative): The primary focus on this type of MPI is to bring about basic changes in the structural area. It mainly adopts solutions being externally available. For instance, increasing the level of automation in a factory by adopting off-the-shelf technologies, belongs to this type of MPI.

MPI type II (infrastructural – locally innovative): The primary focus is to bring about basic changes in the infrastructural area. This MPI type mostly involves the adoption of solutions being externally available. A typical example is that of importing packaged company-wide improvement initiatives, such as the Lean manufacturing and Six Sigma.

MPI type III (structural – radically innovative): Basic changes occur in the structural area and new-to the-state-of-the-art solutions are adopted in a factory. An example of this type is the novel automation systems, being developed and applied to a factory.

MPI type IV (infrastructural – radically innovative): Basic changes occur in the infrastructural area and new-to-the-state-of-the-art solutions are adopted in a factory. In this type, novel work processes, production flows, or other kinds of unique solutions, related to the infrastructural area, are created and used in a factory.

4.2. Aachen innovation management model

The Aachen Innovation Management Model (AIM) has been developed at the Fraunhofer IPT with reference to the St. Gallen Concept of Integrated Management. It represents a reference framework  (Figure 6) for the issues of innovation management and enables the identification of integration gaps and main focuses on adjustments (Eversheim 2009).

The goal of the AIM is to achieve stable innovation ability  (Figure 7). Within the decisive field of activities and its detailing by means of influencing factors, the enterprises are able to position themselves. Another step of the model enables the statement of the nominal condition, which is oriented towards the corporate development. Due to the discrepancy between the nominal and the actual condition, strategic actions and the corresponding goals can be educed. The result is a holistic innovation management, oriented towards the corporate development.

Figure 6. The Aachen Innovation Management Model AIM (Eversheim 2009).

The AIM involves all the phases, namely, the Innovation planning, the innovation organization, the Innovation Leadership and the operational level.

Figure 7. Examples of an as-is- and to-be-profile of innovation planning (Eversheim 2009).

AIM by determining the Innovation Portfolio is the basis for the Aachen Strategy Model for Product Innovation and the InnovationRoadMap methodology.

4.3. Systems innovation approach

The process of a system’s change is a complex activity, which is often underestimated as ‘hidden’ elements (culture, personal schemas, resistance to change, politics, fears) often have a greater impact on a system’s success, than that of the ‘visible’ elements (facilities, processes, materials, schedules). The reasons for the failure of change projects, suggest the need for an improved approach to fostering a change. As the existing approaches to manufacturing innovation do not satisfy the total requirements of a system redesigning a holistic, a practical and an effectively integrated approach to redesigning manufacturing systems has been proposed in the form of the model of Systems Innovation Management (SIM) (Dooley and O’Sullivan 2000), which is based on addressing holistic requirements for the management of innovation. SIM has been developed upon five broad levers that provide a firm theoretical foundation for the new model along with supporting the realization of a system’s innovation process:

• Organisation and group leadership: It is the application of the lessons learnt from the benefits accrued from operating in groups and teams, both at a senior management level and throughout the organisation.

• Strategy and performance: this lever addresses the need for the development of a general direction to progress, during a 2 ± 5 year period, in order for its corporate goals to be achieved.

• Empowerment and groups: this lever addresses the need for full utilisation of all personnel, in the active development of the organisation.

• Reengineering and improvement: the establishment of the mental acceptance, requiring the need for initiatives of both incremental and transformational rates of improvement in order to adequately progress the organisation.

• Learning and communications: the acceptance of the need for the development of the organization’s human resources, and the establishment of an effective communication infrastructure for the entire organisation.

4.4. Fusion innovation

The use of a multitude of technologies in the manufacturing sector is mandatory. For this reason, the development of a novel manufacturing process, model or platform has to rely on as many technologies since it can be verified by many examples in the recent years (e.g. mechatronics, Flexible Manufacturing Systems – FMS, optoelectronics, etc.).

The manufacturing sector benefits from the fusion of the existing technologies into hybrid technologies. Technology fusion is not effective only with the component technologies being available. In order to be effective, disruptive component innovations are necessary. The existence of disruptive innovations is a required condition for the realization of technology fusion. Only after technology fusion has been realized, can the market’s needs be met and the demand for disruptive component technologies be articulated and pulled into the market. (Kodama and Shibata 2017)

Technology changes in one of the industry sectors are increasingly dependent upon the progress of other sectors, whilst the importance of inventors and lone inventors has been over emphasized as modern technologies are characterized by their complementarities, cumulative impact and inter-industry relationships. Technology fusions can lead to the gradual growth of innovation across cooperating industries, and it is very much dependent on the way companies define R&D.

Breakthrough innovations are mostly driven by defense requirements, while technology fusions are driven by market/industry demands. Sources of the requirements can be: Customers, Domain experts, Legacy materials and Product life-cycle data (Kusiak 2009).

In order to cope with this challenge, the concept of the Digital Innovation Hubs (DIH) initiative has been developed by European Union as one-stop-shops that help companies to become more competitive with regard to their manufacturing processes, using digital technologies. DIH are based upon technology infrastructure (competence center) and provide access to the latest knowledge, expertise and technology in support of their customers with piloting, testing and experimenting with digital innovations (Rissola and Sörvik 2018).

4.5. Modular and convergence innovation

The developments in the ICT and their application have introduced new models to the Management of Technology and Innovation, particularly in manufacturing. In the 1990’s, there was a trend towards the modularization of the technological systems; thus, the innovations had to follow this concept. From the 2000 onwards, the manufacturing sector, after the heavy application of ICT in all the technological fields, has had to follow the concept of Technology-service convergence. Consequently, the digital union of telecommunications, the information technology, and the Internet and consumer electronics, are similar to that (even if not so high tech as today) of the nineteenth century, when industry had to confront a similar collection of technical problems, such as power transmission, control devices, feed mechanisms, friction reduction, etc.

The innovation processes have to recognize these facts and to adapt accordingly, in order to cope with the new challenges of the future manufacturing systems. (Kodama 2014)

4.6. Organizational Innovation in Manufacturing

For a manufacturing system, the most important aspect, in view of competitiveness, beside those of the cost leadership or differentiation strategies, is also of the organizational innovation that aims at coping with the challenges of the technological development in manufacturing equipment and/or methods. The organizational innovation in manufacturing has three dimensions, those of the administrative, product and process innovations. These innovation forms have shown to be relating to work redesigns and work systems, skills enhancement, management systems, changes in incentives and design of innovations, and introduction of the ideas of Total Quality Control (TQC) and Just In Time manufacturing (JIT). Innovation appears to have had a great impact on work productivity and on the organization’s overall performance. (Yamin et al. 1997).

Since the dawn of industrialization, there have been some important waves of innovation, regarding the introduction of organizational innovations in manufacturing, which can be depicted in the following Table 6.

The lean approach has also been applied to the Product and Process Development in order for the design process, from the concept stage to the detailed development of products and their related manufacturing processes, to focus on the creation of value and the elimination of waste through the application of the concurrent engineering principle and tools such as the Digital engineering, Quality Function Deployment, Design concepts matrix or Design structures functional plan (Khan et al. 2013).

Furthermore, in the light of the requirements of the 4th Industrial Revolution (Industry 4.0), the term Inclusive manufacturing has been proposed as the inclusion of the innovations and advancements in the manufacturing domain. This is for finding out the solutions of societal (employment, education, healthcare, labor, etc.), economical (cross-border business, trade policies, cost of products and services, and manufacturing contribution in GDP), and environmental (natural resources, energy, air quality, clean water availability, recyclable and sustainable products) issues by composing the resources in a geographically distributed environment with the support of advanced manufacturing technologies (IT systems, Artificial Intelligence, High-Performance computation, CPSs, etc.). This is carried out through the integration of semantic web and internet of things in order for the objective of minimum market time, better quality, low cost, faster services, and environment-friendly manufacturing to be achieved (Singh, Mahanty, and Tiwari 2019).

5. Discussion – Societal and adoption aspects of innovation in manufacturing

As described above, innovation is critical for the existence of any organization and particularly, more for a manufacturing company, which is exposed to the fierce competition in terms of products, process (technology) or even organizational and business model innovation.

The diffusion of innovation in manufacturing despite the mechanistic approach, based on widely used managerial tools, it should also be seen from a techno-economic paradigm change point of view. While the technological change is more rapid, there is often inertia when it comes to changes in social institutions. Hence, it calls for co-evolution of technology and social institutions. Building on the concept of ‘network externalities’, in fact, a more important dimension of technological diffusion, is institutional (or educational) and not technical.

Several cases of diffusion demonstrate the importance of institutional changes, or changes of laws in order for the prompt diffusion of these technologies to be possible. Further, the size of adopted companies is not taken into consideration in the rate and timing of adoption. Adoption of innovation seems to be of high importance to manufacturing companies since they are characterized not by the ‘creation’ of innovation but rather by the fact that they are mostly end-users of innovative processes that are developed by other companies (suppliers, etc.).

It is often believed that while the rate of a technological change can be quite high, the societal diffusion rate is much lower due to the institutional inertia. In high technologies, such as information and communications, this does not have to be the case. Probably, there can be a ‘coevolution’ of computer-based technologies and social institutions. If these computers are used for new activities, then the diffusion can be rapid with the institutions quickly coevolving in the same way. In particular, the developments of contemporary and future manufacturing systems, towards their decentralization and requirement for even more flexibility and agility, poses certain demands regarding the methodology of their assessment (Mourtzis, Doukas, and Psarommatis 2012). The initiatives described in paragraphs 4.1 and 4.4 initiatives are conceived so as to be coping with these challenges, but the efforts and preparation should be also performed at a manufacturing company’s level.

6. Further research

Building on the research performed for the current paper, the fields for further research on innovation aspects, especially in the manufacturing sector can be: a. the conception of specific innovation tools or guidelines, according to a company’s level of sophistication, the size or type, by evaluating the level of understanding the innovation notion, throughout a project’s value chain or innovation process (by applying the Macro-Meso-Micro concept as transferred to the manufacturing company level in paragraph 3) and particularly, the way that the innovation adoption rate is affected, especially at the boundaries of the components of a manufacturing system, b. the correlation of the level of special training or education, in innovation management or innovation tools to an organization’s innovation performance, c. a correlation of the innovation models to the concepts of the innovation (triple or quadruple or N-tuple) helices taking in consideration the socio-economic issues as described in paragraph 5 and finally d. the conception of a mechanical analogue to the innovation process spiral.

7. Conclusions – outlook

In this paper, there was performed a presentation of an overview of the various aspects of Innovation notion, particularly its implications in manufacturing. The plethora of definitions and the popular (or contemporary) use of the term innovation, most of the times, leads to misconceptions among the stake holders of an innovation system, usually having originated from the three (or four or even more) components of the innovation helix (academia-state-industry-society-diaspora-globalization). Even employees of the same company, according to their background or function, do not have the same perspective of the way innovation is applicable or valued, despite the fact that everybody agrees to its usefulness and necessity. In particular, manufacturing requires the serious founding of innovation projects, especially when they involve serious alterations to the production systems, which will affect their future competitiveness. Thus, innovation especially for manufacturing companies has usually got basic strategic characteristics, such as defensive (comply to competition) or even offensive (taking advantages to competition). These serious and usually long-term decision or monitoring processes have to be well founded on methods and metrics and not on vague data or plain imitation of the competition or worse only on plain hunch.

Finally, the human aspect and leadership for the initiation, promotion/propagation and organization of innovation projects in a manufacturing company should not be neglected.

Acknowledgments

This paper is supported by European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No 780265, project ESMERA (European SMEs Robotics Applications).

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. http://www.businessdictionary.com/definition/innovation.html.

2. http://lexicon.ft.com/Term?term = jugaad-innovation.

3. https://en.wikipedia.org/wiki/Parmenides_(dialogue).

4. https://berkeleyinnovationindex.org.

5. https://m2i2.masstech.org/mass-manufacturing-innovation-initiative.

6. https://i4ms.eu/.

7. https://www.manufacturing.gov/.

8. https://en.wikipedia.org/wiki/Made_in_China_2025.

9. See also KANO method.

10. See also RoPDE.

Appendices

Appendix A.

Table A1. Overview of the use of the various measurement categories (Adams et al. 2008).

Measure/sector	Aerospace- Defense	Business Services	Construction	Creative industries	Financial services	High-Tech Manufacturing	ICT	Pharmaceuticals	Public sector	Retail & wholesale distribution	Telecoms	Transport
• Financial performance	√	√	√	√	√	√	√	√			√	√
• Innovativeness		√			√	√	√	√	√	√	√	√
• Technological application			√						√	√	√
• Business performance		√			√	√	√
• Process improvement	√	√			√							√
• Reputational enhancement				√	√						√
• Knowledge utilization	√						√
• Market performance								√				√
• Product advantage						√		√
• Business model innovation				√							√
• Reinforcement of innovation• orientation									√	√
Strategic importance of innovation						√				√
• Timeliness		√			√
• Commercialization		√
• Content creation				√
• Exploitation of knowledge stocks over time	√
• Future business value			√
• Innovation collaborations			√
• Innovation index								√
• Knowledge conversion							√
• Outreach									√
• Public impacts									√
• Technology development	√

Appendix B.

Table B1. The stages of Innovation process and adequate metrics (Morris 2008).

	Stage	Qualitative Metrics and Provocative Questions	Quantitative
INPUT	−1: Strategic Thinking	a. Are we targeting the right parts of our business for innovation? b. Can we change as fast as our markets can? c. Are we flexible enough? d. Is our strategy clear enough to be translated into innovation initiatives? e. How well do our strategies match to the way the market is evolving? f. Do we have an effective innovation dashboard? g. Do we measure innovation adequately?	Metrics a. Time senior managers invest in innovation b. Time required from the development of a strategic concept to its operational implementation c. Money invested in innovation
	0: Portfolio Management & Metrics	a. How does our portfolio compare with that of our competitors? b. Do we have the right balance of incremental and breakthrough projects? c. Are we introducing breakthroughs at a sufficient rate to keep up with or be ahead of a change? d. What are our learning brands, the ones we use to push the envelope to track the evolution of the market? e. Are we developing new brands at an adequate rate? f. Do our metrics evoke the innovation behaviors expected by the people in our organization? g. Are our metrics aligned with our rewards and reward systems?	Portfolios a. Ratio of capital invested in the early stages vs. return earned in sales stage b. Actual portfolio composition in the sales stage, compared with the planned/intended portfolio composition in the planning stage Metrics: a. Expected metrics vs. actual performance achieved
PROCESS (THROUGHPUT)	1: Research	a. How well do we understand the tacit dimensions of our customers’ experiences? b. How well do we understand the implications and applications of new technologies? c. How well do we understand the emerging future? d. How accurate have our past predictions been at an anticipated change? e. Does our research help with targeting the right innovation opportunities?	a. Number of customer groups that have been examined b. Applications of research results to new products, services, and processes c. Breadth of participation throughout our organization in the research process (broader is generally better) d. Time invested in research e. Money invested in research
	2: Ideation	a. Do we have a broad enough range of models of technology possibilities, tacit knowledge models, and societal trends? b. How competent are we at creating an open sandbox to accommodate a tremendous range of possible concepts and ideas? c. Do we encourage people sufficiently enough to share their ideas?	a. Number of ideas developed b. Number of ideas contributed by our staff c. Number of ideas introduced d. Percentage of ideas from outside e. Number of people in the organization who participate in the ideation process f. Number of people outside the organization who participate in the ideation process g. Number of ideas collected in the ‘idea gathering’ system h. Number of collected ideas that were further developed i. Number of collected ideas that were implemented
	3: Insight	a. Are we getting enough solid insight/concepts? b. Are the insights developed across a broad enough range of business ideas?^9	a. Unsuccessful technology and customer mash-ups attempted b. Successful technology and customer mash-ups achieved
	4: Targeting	a. Is our innovation portfolio balanced correctly? b. Do we use the right management processes for the different types of innovations that we are working on?	a. Percentage of investment in non-core innovation projects. b. Total funds invested in non-core innovation projects c. Senior management time invested in growth innovation
	5: Innovation Development	a. Are the right people involved in the innovation process? b. Is the number of failures low in order to assure that we are pushing the envelope sufficiently?	a. Prototyping speed b. Number of prototypes per new product c. Average time required to get from Stage 1 to Stage 5 d. Number of patents applied for e. Number of patents granted f. Percentage of ideas funded for development g. Percentage of ideas turned down
	6: Market Development	a. How well are we balancing our attempts to reach the existing versus new customers? b. How well do we really understand our customers? c. Do we have the right attitude towards any changes in our customers’ beliefs, ideals, etc.?	a. Return on marketing investment b. Number of new customers c. Growth rate of customer base
OUTPUT	7: Selling	a. How well does our sales process match to our customers’ requirements?	a. Now we can talk meaningfully about ROI.^10 Did our total innovation investment, managed through portfolios, to yield the appropriate results, in terms of sales growth, profit growth, and overall ROI? b. Gross sales revenue c. Gross sales margin d. Expected results compared with the actual results e. Percentage of projects terminated at each stage f. Successful results per type of innovation. g. Cost savings achieved in the organization due to innovation efforts. h. Number of new customers. i. Percentage of sales from new products/services? j. Average age of products/services? k. Number of new products/services launched l. % of revenue in core categories from new products/services m. % of revenue in new categories from new products/services n. Percentage of profits from new products/services o. Percentage of new customers from new products/services p. Time to market from research through to sales q. Customer satisfaction with new products/services
Transversal Metrics		a. Innovation Training provided to a number of people b. Participation in the use of online innovation tools c. Linkage among metrics, performance assessment criteria and process, and reward systems