Digitalization and Big Data Supporting Responsible Service Business Co-Evolution

Transcription

1 Digitalization and Big Data Supporting Responsible Service Business Co-Evolution Mikko Mäntyneva, Vesa Salminen, Heikki Ruohomaa Häme University of Applied Sciences, Finland Digitalization is rapidly increasing and enterprises must find new ways to innovate for business advantage. This article introduces a strategic concept, responsible service business management, for utilizing responsibility as a business and innovation driver to facilitate the transition of industrial business towards the new service economy. Responsibility is creating significant impact and opportunities where business, technology, and innovation intersect. Big data, which is resulting from digitization, can be considered as a major opportunity to support responsible business co-evolution. The case business area in this article is circular economy. 1. Introduction The management of responsibility in value network and the entire society is becoming an important business driver. Most companies do not have a strategy or analysis on aligning the business to responsibility. Being green to achieve mitigation, clean to reach up to optimization and smart to manage the transformation is the integrated, evolutionary approach. Responsibility is an opportunity integrator on the path. Integrating novelty with technology brings new opportunities for more responsible business models. The transformation towards responsible business takes a long time and that is why it is important to fully understand the strategic concept, identify the key issues and harness the associated opportunities. Most of the companies, which are moving towards service business, need new concepts to manage life cycle business on the responsible way. From initial compliance or carbon footprint thinking, steps can be taken which can concurrently be used to optimize enterprise-wide business processes and perhaps even begin creating strategic differentiation and offering enhancement. Knowledge is scattered and distributed in business networks. Competence areas have become more complicated and single human capacity cannot cope with all the needed competence to create new opportunities for businesses. This article intends to demonstrate that responsible service business is not only the goal but also the means. It introduces a strategic concept, responsible service business management, for utilizing responsibility as a business and innovation driver to facilitate the transition of industrial business towards the new service economy. Responsibility is creating significant impact and opportunities where business, technology, and innovation intersect. The case business area in this article is circular economy. 1

2 2. Digitalization and big data Digitalization is a current megatrend, implying that digital technologies are integrated into our ordinary life. The utilization of advanced digital technologies empowers the connection of various services and automating several processes supporting them. Despite the fact that digitization itself is a vital technological (r)evolution, it empowers much more fundamental change: datafication (Ylijoki; Porras, 2016). An expanding number of peripherals, devices, and sensors are continuously connected to the Internet. They deliver wide assortments of digital data. This data generation phenomenon is known as datafication (Mayer-Schönberger; Cukier, 2013). Datafication can be defined as a "sense-making process", which accentuates the value generation viewpoint (Lycett, 2013). Datafication and digitization make it conceivable to catch distinctive activities, situations, or even series of events as data. An obscure term "big data" depicts the data resulting from datafication (Ylijoki; Porras, 2016). Digitalization and industrial internet can then be used when increasing the efficiency of processes. Industrial internet enables functional optimization of entire value network and increasing use of material side flows (material and energy efficiency). It is possible to anticipate beforehand the disturbance situation of value network and their repair operations. Collected data from whole the value network can be used for its functional development or forecasting purposes. New entrepreneurship and new digital services can be created through digitalization activities. Industry 4.0 standard architecture can be applied to a common framework when starting a business on circular economy. Big data, which is resulting from digitization, can be considered as a major opportunity, see for example (Davenport, 2014; Manyika et al., 2011; Schmarzo, 2013). Datafication and big data are disruptive technological phenomenon that have widespread implications for the society and industries. The public sector, privately owned businesses, technology vendors, consumers, and policy makers, among others, have interests in the field. In addition, as the quantity of stakeholders parties involved expand, the basic comprehension of the phrasing and concepts turns out to be increasingly important (Ylijoki; Porras, 2016). Big data might be characterized as far as volume or scale (Zikopoulos; Eaton; DeRoos; Deutsch; Lapis, 2012), examination strategies (Chen; Chiang; Storey, 2012), or effect on organizations (McAfee; Brynjolfsson; Davenport; Patil; Barton, 2012). The ascent of mobile and digital networking has made the world turn out to be more associated, arranged, and traceable and has lead the accessibility of such huge scale sets of data (Rainie; Wellman, 2012). Big Data is a freely characterized term used to depict data sets so vast and critical that they get to be ungainly to work with utilizing standard statistical software (Snijders; Matzat; Reips, 2012). 2

3 Given the data assessing capacities that are set up with regards to checking physical resources, chances of success are greater from an industrial perspective (Shah, 2016). Big data is likewise characterized as a key empowering influence that can be utilized to generate value in privately owned businesses and public organizations (Ylijoki; Porras, 2016). The revolution of big data is in its initial days, and the vast majority of the potential for the creation of value is still unclaimed. However, it has set the industry on a way of quick change and new revelations; stakeholders that are focused on innovation will probably be the first to reap the rewards (Groves; Kayyali, Knott; Van Kuiken, 2013). Examples of the benefits related to digitalization and big data incorporate creating opportunities for new business, enabling innovation related activities, and supporting managerial decision making (Lee; Kao; Yang, 2014). The amount of scattered and structured data around us is increasing dramatically. It is a great business opportunity to benefit that data for business purposes. Datadriven service operations aim to harness insights from the data for planning and optimization. Recent research provides cases of the big data analytics to smart service related innovation (Opresnik; Taisch, 2015/7). Utilization of big data can encourage a commonly beneficial relationship amid a firm, its clients, and perhaps society in smart service systems (van Riel; Kandampully; Kumar, 2013). A smart service system is "a service system capable of learning, dynamic adaptation, and decision making based upon data received, transmitted, and/or processed to improve its response to a future situation (Medina-Borja, 2015). Smart service systems are a sort of human-centered service systems, implying that knowledge, capabilities, and value are all controlled by the people in the system (Maglio; Kwan; Spohrer, 2015). A key issue in innovating smart service systems lies in taking the benefit of analytics of big data to create human value (Maglio; Lim, 2016). 3. Responsible service business and circular economy co-evolution Sustainability is no longer a question of if, but of when, and to what extent it will affect a specific business sector. It is no longer a negative reactionary tactic to moderate environmental climate change, but a positive proactive strategy to accelerate longterm business climate prosperity. It is not just about risk, reductions, and recycling, but an industry-changing paradigm integrating innovation, differentiation, and transformation. Antonio Tajani, EU Commission Vice President on Industry & Entrepreneurship stated, "there will be no sustainability without competitiveness, and there will be no long-lasting competitiveness without sustainability. And there will be neither of them without a quantum leap in innovation." (Eppinger; Hopkins, 2010) have discovered that the link between sustainability and innovation is commonly mentioned, but not commonly made. 3

4 Sustainable growth and responsible business management are not possible to achieve by the way of a linear economy but by circular economy (MacArthur, 2013). Circular economy with interrelated bio and mechanical cycle consists of huge amount of data. The data of waste from one partner means material for the other partner. Understanding the value proposition in growing value networks is essential. Management and analysis of data coming from various sources is routed through the datato-service process in business co-evolution of circular economy, Figure 1. Creation and optimization of new operational functions and responsible business co-evolution requires democratic innovation and decision culture. Fig. 1: From data to services process in business co-evolution of circular economy (Salminen; Ruohomaa; Pöykkö, 2016). A circular economy is restorative and regenerative by design and aims to keep products, components, and materials at their highest utility and value at all times. The concept distinguishes between technical and biological cycles. As envisioned by the originators, a circular economy is a continuous positive development cycle that preserves and enhances natural capital, optimizes resource yields, and minimizes system risks by managing finite stocks and renewable flows. It works effectively at every scale. There is a world of opportunity to re-think and re-design the way we make stuff (European Commission, 2016). Re-Thinking Progress explores how through a change in perspective we can re-design the way our economy works - designing products that can be 'made to be made again' and powering the system with renewable energy. It questions whether with creativity and innovation we can build a restorative economy (EU environment, 2016). 4

5 Circular economy and industrial internet are rather new topics and there are few experiences on driving of benefit out of them both in enterprises and universities. That is why co-operation serves to develop on the collaborative way. Digitalization is rapidly increasing and enterprises must find new ways to innovate for business advantage. Through digital transformation with increasing intelligence and automation enterprises can capitalize on new opportunities and optimize existing operations to achieve significant business improvement. The collection of the enormous amount of scattered data, clustering it for analysis, visualizing it for decision making and using the selected data in new service development and execution is most important in the concept of responsible business leadership. Most of the innovations are created at customer interface and co-operative development on the common platform, research and learning environment is an essential basis in succeeding on business co-evolution. Good co-operation requires management engagement, trust building, information, and experience delivering. It happens on various levels of operation; e.g. forecasting and roadmap-projects, applied research and development projects, on bachelor and masters thesis works or creation of research and learning environment for experimentation and piloting. It is ought to be continuous at various organization levels. Co-operation and learning together on research and learning environment supplied by a university is basis for innovations and continuous development. Lean and digitalized value networks build developing of superior competitive power through principals of circular economy. It is important to succeed in benefiting multidisciplinary competence and open information sharing. There is a new logic behind open innovation, which embraces external ideas and knowledge in conjunction with internal R&D (Chesbrough, 2003). This offers a novel way of creating value. Miller and Langdon (1999) introduce how to manage disruptive innovation by managing platform, product and process innovation in continuous cycles. Nidumolu, Prahalad and Rangaswami (2009) explain widely why sustainability is now the key driver of innovation. Salminen (2008) has discovered that when new value for the customer is created in the form of a product or service offering and it results in sustainable innovation, it is essential to know whether there is also a transition into a new business model of circular economy. At the same time, the business innovation must be built on the essential business structures (operational systems, contracts, network structures, competence, etc.). Tammela and Salminen (2008) introduce the interoperability concept through which common innovation of sustainable products and services can be accelerated by an open semantic infrastructure. The open innovation process requires the definition of interoperability in order to achieve a critical level of network dynamics to create new products and services. Skyttner (2005) introduces new systems theory with self organization and evolution. Gharajedaghi (2011) argues that system thinking is the art of simplifying complexity. It is about seeing through chaos, managing interdependency, and understanding the choice. Concepts are important to explain chaos. Sanchez (2004) have proposed an open systems model of firms. Improving organizational competence also requires increasing managers own cognitive flexibilities to imagine new strategic logics for creating and realizing new kinds of value-creating product offers and new ways of managing processes for creating and realizing new and existing product offers. 5

6 Succeeding on circular economy co-innovation requires data-to-service management process and creation of adaptive multidisciplinary co-operation model for solution development. Same operation model and framework suit for the re-use chain planning and execution as for normal supply chain management.it is obvious that supply chain and re-use chain will unite into circular value chain (Figure 2), when component and material re-use is taken into account until from product planning phase. Fig. 2: Integrated Planning of Supply Chain and Re-Use Chain towards Circular Value Service Network Enabling forces for the development of circular value service network are * Life cycle planning and calculation, which create economic base for effective operation * Utilization of efficient and modern digitalization in all phases of operation * Formalization of value chains and networks, which creates efficiency by streamlining network operations, new innovativeness and entrepreneurship * Legislation, which directs and control operations by restrictions and laws or by incentives connected on taxation. * Business opportunity for many companies in inter-professional co-operation * Created value for whole society in responsible way 6

7 Figure 3 describes the conceptual model of adaptive development towards circular economy by benefiting responsible service business, proper digitalization, and data analysis/management. The objective of circular economy is efficiency on the use of material and energy. The purpose of digitalization is to increase effectiveness of planning and optimization. The objective of the responsible service business is to apply responsibility as a business and innovation driver. The trend in succeeding on circular economy is that these functions will be continuously increasingly overlapping. The increasing digitalization and management on data-to-service-process are key enablers in business co-evolution. Fig. 3: Proper implementation leading on more intensive overlapping 4. Discussion and managerial conclusions Manufacturing industries have started to adopt the circular economy framework with a regenerative model of manufacturing. In this model, products, components and material are re-used multiple times by circular value chain. Combining the principles of circular economy to value network thinking and digitalization of functionality of whole the network give an opportunity for remarkable competitive advantage in business. In order to sustain competitive advantage, manufacturing companies are expanding their product offering to also provide lifecycle services. By doing so, these leaders are expanding their value proposition multidimensional by concurrently creating strong potential through developing more sustainable customer-engaging products, co-innovating sustainable services together with their partners, and collaborating to create integrated new sustainable business technologies. Companies today are facing increasing complexity to execute profitably on continuous sustainable business transition. Resource and energy efficiency is possible to achieve by eliminating waste through the superior design of materials, products, systems and business models, improving the reuse of products and by recycling of materials. Recognition of actual customer 7

8 needs combined with life cycle calculation creates opportunities for life cycle services, but it gives also economic fundamentals and reason to observe also the value of disposed products and re-use opportunity. That requires combining of various theories but the main challenge is in the utilization of transdisciplinary knowledge and implementation work. The use of new technologies; digitalization, big data, and social networks with increasing intelligence and automation enterprises can capitalize on new opportunities on and optimize existing operations to achieve significant business improvement on circular economy. Managers inspired by driving a major data transition can begin with two straightforward strategies. To begin with, they can get in the propensity for asking "What do the data say?" when confronted with an essential choice and catching up with additional specific inquiries, for example, "Where did the data came from?," "What kinds of analyses were conducted?," and "How confident are we in the results?" Second, they can permit themselves to be overruled by the data when applying data discredits a hunch (McAfee; Brynjolfsson; Davenport; Patil; Barton, 2012). To get advantage from big data requires alterations and upgrades of technological infrastructure, organizational processes, business applications and in addition an incremental change in the business model of the firm. This includes also new techniques to derive knowledge from data. Firms going for a better utilization of accumulated data ought to see this additionally as a cultural challenge. To overcome this cultural challenge organization should concentrate on preparing employees to efficiently manage data appropriately and consolidate them into decision-making process. As opposed to considering data essentially as an input variable, its worth as an organization s "resource" should be understood and internalized. To amplify this resource, data governance should focus on ensuring high data quality as a premise for any big data activity (Buhl; Röglinger, Moser; Heidemann; Others, 2013). According to the experiences of conceptual development work, successful activity in circular economy is dependent on systematic long-term development on industry. An essential topic is preparing of up to date legislation, which enables and controls the operation and creates a business environment to apply new offering. European community is preparing new legislation and directives, which are speeding up the development of circular economy. Industry 4.0 as an industrial standard architecture has a remarkable role in preparing new functionalities on distributed value networks. The standard offers technical background and rules for implementation for digitalized circular economy. The co-operation between government, enterprise and universities is essential to succeed in co-evolution when building up cumulative competence while creating solutions for circular economy by benefiting digitalization in it. It is also essential to have a common vision to direct the local operation and funding. Otherwise, the activities can splinter into small pieces and do not form parts of the whole vision. The important role of universities is to support enterprises by applied research and creation of research and learning environments for continuous piloting of new technologies and preparation of new business models on circular economy. Digitalization changes everything and is a great opportunity to find out a competitive advantage in business. 8

9 Universities of applied science have a good opportunity and central role in supporting the growth of business in the area of circular economy. Smart services research unit at Häme University of Applied Sciences supports industry, commerce and the society in digitalization and service development needs. The task of the research unit is to create and execute, together with co-operation network, well-addressed R&D activities for the region and its enterprises. The focus is on developing knowledge that can be applied in diverse industries. Responsible business management and circular economy are key focus areas of the research strategy on Smart services research unit. The Smart Services research unit supports the utilization of digital technologies and service business development across sectors: similar solutions can be adapted in various lines of business. A specific geographic focus is on the growth path of Finland, Helsinki-Hämeenlinna-Tampere, which is a versatile area of industry. To be successful on new challenges of circular economy, enterprise-university partnership has to be tight and the main objective is common learning. Long-term co-operation creates a background for new co-innovation and business co-evolution. For research unit to be capable of collaborating with industrial companies, it is important to know the overall capability of research and development unit. The experts making applied research with customers have to have content and process knowledge of customer site, they have to be capable of working in teams on distributed way with other experts in value network and have to certain collaborative skills to work together. It is essential to categorize the competence and capability on three layers: content management capability, organization capability and human competence and capability (Salminen; Kantola; Vanharanta, 2015). Responsibility business leadership needs democratic innovation culture and coinnovation and co-evolution processes. This article introduces a concept of responsible service business. It gives a concept how to analyze co-evolution over the life cycle of business transition on circular economy. Digitalization is rapidly increasing and enterprises must find new ways to innovate for business advantage. Through digital transformation, the use of new technologies like cloud, mobile, big data, and social networks with increasing intelligence and automation enterprises can capitalize on new opportunities and optimize existing operations to achieve significant business improvement. Through digital transformation, the use of new technologies with increasing intelligence and automation enterprises can capitalize on new opportunities and optimize existing operations to achieve significant business improvement on circular economy. There is a great challenge on usability of digital systems and services and even data. The process of data (life cycle and big data) transferred on information and tacit knowledge and finally as life cycle care and services have to be managed to change it as a business opportunity or completely new entrepreneurship and business. It is tuff for a human being and his mindset, capability of organizations and team structures to manage scattered topics during business co-evolution. 9

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12 Smart services research unit P.O. Box Hämeenlinna, Finland Heikki Ruohomaa Häme University of Applied Sciences Smart services research unit P.O. Box Hämeenlinna, Finland 12