Social-Mobile-Analytics-Cloud: A digital ecosystem for innovation

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1 Social-Mobile-Analytics-Cloud: A digital ecosystem for innovation Dr. Manfred Langen Corporate Technology, Research in Digitalization & Automation Siemens AG Munich, Germany manfred.langen@siemens.com Abstract The four technology drivers Social Media, Mobile Computing, Data Analytics and Cloud Computing are of major importance for the digital transformation, and each incorporates disruptive potential for future businesses. Even more innovation potential lies at integrated solutions of these four technologies called the SMAC system. This combination amplifies the effects of each single technology, and forms a digital ecosystem for new products, services and business models. A microservice architecture is proposed to allow easy integration. This approach opens a wide range of possible combinations and constitutes an ecosystem of innovation which can systematically be exploited by the method of morphological modeling. Keywords digital ecosystem, social collaboration, mobile computing, cloud, disruptive innovation, API economy, morphological modeling I. INTRODUCTION How existing technologies are recombined into new innovations remains an important question not only for startups and venture capitalists. Today, the keywords Social, Mobile, Analytics, and Cloud can be found on every technology roadmap related to the digital transformation. They evolved from particular applications to broadly accepted technologies over the last 10 years. Starting in the consumer market, they disseminated very soon into industrial applications. Proponents of each technology field are convinced that their technology is a source for innovation and can change the rules of how business is done. The new challenge is the appropriate combination of the four technologies into a new class of IT-platform that can be used as a digital ecosystem for innovation. Some examples of successful ecosystems have already been placed on the market by Apple, Google, Amazon, or Salesforce. They are pioneering a deep transformation of many businesses in the coming years. This kind of transformation is not necessarily only driven by big players from the U.S. Every business owner can develop a strategy to amplify core competencies and leverage new opportunities in digital value networks by using a SMAC approach. SMAC technologies are introduced in more detail in section III. This paper describes a conceptual design for the vision of an innovation ecosystem with the potential to create new platform businesses in a systematic manner. II. RELATED WORK Several consultancy companies predict that the interplay of the four technology drivers Social-Mobile-Analytics-Cloud will dominate the next decade of the digital transformation [7]. The ability to design a combined solution that provides more value than the sum of the single pieces will turn into a big competitive advantage. IDC defines The third platform as the inter-dependencies between mobile computing, social media, cloud computing, as well as information/analytics (big data), and possibly the Internet of Things. It forms the basis for a continuous industry transformation [6]. Gartner claims these interdependent trends are transforming the way people and businesses relate to technology. Frank Diana created a very comprehensive overview in a visual chart in his blog posting on Technology, Social Change, and Future Scenarios [2]. As the main digital forces converge (Social, Mobil, Big Data, Analytics, and Cloud), he expects that right on the heels of such digital platform, a series of innovation accelerators will converge with the platform. These accelerators (Robotics, Artificial Intelligence, Blockchain, 3D Printing, Internet of Things, etc.) are game changers for future scenarios around Smart Cities, Connected Car, Sharing Economy or Maker Economy. Research on innovation management shows that innovation generally does not come out of the blue. An analysis of scientific papers found that the most creative ideas contained deeply conventional ideas, but also combined things in ways that they hadn t been combined before [10]. The role of atypical combinations of prior work becomes key for hit papers. The paper suggests an evolutionary aspect, i.e. novel pairings either are never used again (not adopted) or become conventional pairings (mainstream). Fey and Rivin use the TRIZ methodology [4] to overcome random innovation and supersede it with a method of systematic innovation. TRIZ is used to support systematic innovation with several methods for overcoming system conflicts and to provide a basis for technological forecasting.

2 III. CHARACTERISTICS OF SMAC COMPONENTS As a further introduction, the state of the art in each technology field is described in order to be sufficiently considered for the combined approach. Based on this understanding the roadmaps of these fields have to be aligned to drive these technologies towards convergence. In the following, a rough overview is given for the four technology drivers and their innovation trends. Fig. 1. The concept of SMAC (own illustration). A. Social Media Social media began their success story in the Internet (Facebook, twitter, LinkedIn, ) and are used by around 2 billion people. Added up, users spend 200 million hours on Facebook every year. That s ten times as many person-hours as were needed to build the entire Panama Canal [1]. The same principles of user interaction entered the area of workforce collaboration by means of Enterprise Social Networking (ESN) platforms. Such ESN are introduced in most companies and used with varying success. The untapped potential of social technologies was estimated in a McKinsey study with $1000 billion [9]. Today, the integration of social into business processes is a top priority. 61% of global CEOs state that socially-enabled business processes are strategically important to their business success [11]. The next step on the roadmap is the integration of social collaboration in vertical IT solutions [8], i.e. products and customer solutions are enhanced by features that support collaborative work. B. Mobile Computing One half of the world s population is using mobile phones. The importance of mobile computing rapidly increased with the advent of cheaper smart phones. Smartphone users carry more computational power in their pockets than a data processing center of the 1980s. Used as universal personal assistant everybody can add one of the million apps covering all kind of domains from smart home to healthcare. The industry sector uses mobile devices for the mobile workforce, e.g. service technicians. Wearables and augmented reality are on the roadmap for the future mobile work. In the near future, service technicians will be supported by annotations and projections appearing as an overlay on their screen or glasses that are related to their current context, e.g. an assembly group in focus. C. Data analytics Data analytics or big data combines the collection of large amounts of data with algorithms that calculate relations, help to find correlations, and visualize data sets. The data tracks can be either generated by humans ( social analytics ) or by machines ( Internet of Things ). In order to support decision making hypotheses can be tested and assigned a probability. As new technology in the field of analytics cognitive computing is on the rise. A combination of text analytics, natural language processing and semantic search algorithms becomes a novel type of artificial intelligence (AI). New forms of human-machine-collaboration will influence the future of AI in two ways: On the one hand, highquality information that has been generated collaboratively (e.g. Wikipedia) is used as a knowledge base for cognitive computing. On the other hand, AI can be used to support collaboration processes in complex man-machine use cases by generating context specific recommendations, e.g. in project management tasks. D. Cloud Computing With cloud computing a virtual computing center becomes available for every kind of application. Computational power and storage capacity can be scaled up and down on demand. For the future, hybrid solutions, combining public and private clouds, as well as the integrated play of local and cloud resources, will challenge current software architectures. Multicloud architectures with cross-cloud interoperability and cloud integration platforms are on the roadmaps. In addition, edge computing and fog computing are appearing at the horizon and claim to provide more decentralized cloud computing. IV. DIGITAL ECOSYSTEMS WITH SMAC Today we often find combinations of two or three technology drivers. After a steep rise during the last 3 years, now more than 90% of all Facebook users access their social application on mobile devices. Further examples are: mobile access to applications which run as cloud application social question and answering (Q&A) on mobile devices social analytics The full potential of SMAC can unfold when all drivers amplify each other. Success stories with high visibility are

3 applications of the so-called share economy: Uber, AirBnB, and BlaBlaCar are all based on SMAC systems. A. Full SMAC Fig. 2 shows how the four technology drivers can influence each other with a positive effect. Fig. 2. SMAC interdependencies For example, the analysis of a social graph can be used to recommend new contacts or for social media marketing. If the user has a mobile device, these recommendations can be adapted to the mobile data trace, e.g. location based information. The mentioned SMAC systems from the share economy are powerful platforms but they don t provide an ecosystem that can be used by third parties. In consequence, everybody who wants to benefit from the power of SMAC has to build such a system from scratch. B. Architecture requirements The software architecture of a SMAC system has to support the combination and easy integration of functionalities from the four technology fields. This can be difficult if socialmobile-analytics-cloud systems have been built separately on different technology stacks and legacy software causing errors and high integration efforts. Therefore, a business advantage can be achieved with a modular software architecture with full compatibility and approximately zero integration costs. The vision is an open SMAC ecosystem with a broad offering of functional SMAC modules where the design and integration into a new SMAC application can be handled without programming. Such a development environment allows quick adaptation to new requirements for the frontend (social, mobile) as well as for the backend (analytics, cloud) and this way supports the creation of new business models or the modification of existing ones. V. SOLUTION APPROACH Instead of developing separate software architectures for social, mobile, analytics, and cloud applications a common approach is suggested to facilitate the (re)combination of functional modules in a digital ecosystem. A. Microservices In this context the definition of powerful API s will become a success factor [5]. RESTful APIs and JSON as the primary format for exchanging data are currently the most widely used and promising candidates in this area. Another upcoming technology is GraphQL which aims to overcome challenges of REST-based architectures by rethinking the way clients communicate with remote systems. In addition, microservices can match the requirement for a modular system with the capability to combine lean functional modules. Although the implementation language for microservices should not play a major role, we suggest a full JavaScript stack such as MEAN (MongoDB, Express, AngularJS, Node.js) for all four technology drivers. Table 1 gives a summary of several aspects regarding microservice architectures. Microservices are easy to integrate with defined API-calls and can be used by multiple applications at the same time. Container virtualization technologies like Docker prepare microservices to run in a cloud environment for elastic load balancing and auto scaling. Characteristics Performance Agile development Software stack Integration Microservice Architectures Functionality is cut into several services, each of which is able to act independently. These services are combined into an application. Each service can be optimized separately and/or scaled independently. Changes are implemented within services without side effects. Services can be implemented in different languages and frameworks. Integration is done via defined APIs. These have to be stable or allow soft transitions by supporting multiple API versions. Tab 1: Properties of microservice architectures B. API management and API economy An effective API management is necessary to manage a large number of lean microservices. E.g. developers benefit from a common structure and semantic of API definitions to accelerate development and reduce errors. This is of course technically not mandatory, but it helps to increase adoption of such a software ecosystem. Based on the described concept different business models today known as API economy are built around the APIs for a revenue model. One approach is a pay per use model for certain API calls. Current business models often involve

4 charging for each API call or offer plans with a limit on the number of calls for a specific time period. Other business models offer APIs for free in order to increase the dissemination of an application and to generate return by an additional offering for the target group. For example, advertising based revenue models belong to this category. Depending on the business models, API management has to fulfill associated requirements. E.g. statistics on API usage have either to be linked to the own accounting system or have to be provided to a customer using such business model. C. SMAC Platform as a Service Many combinations of microservices are possible in a SMAC ecosystem so that a wide number of applications can be built upon such a system. Using such a system internally has a huge potential for large companies with their hundreds of internal enterprise applications. Nevertheless, the ultimate goal is an open microservices integration platform with Platform as a Service (PaaS) capability. Then, third parties can build their SMAC systems in which they can integrate public and private microservices to compose new SaaS applications and services. For instance, Salesforce s Platform as a Service Force.com enables (re)combination of CRM-related services into new applications and can be seen as a blueprint for the idea of a SMAC PaaS. VI. MORPHOLOGICAL MODEL FOR INNOVATION Creativity is fundamental for innovation and a summary of many inputs. Filmmaker Kirby Ferguson inspired by the filmmaking wisdom that all hits are flukes identified three key building blocks for innovation and creativity: copy, transform, and combine. In short: everything is a remix [3]. Copy: No one starts on plain field. You cannot create anything new without a solid foundation of knowledge and understanding in the line of work. Copying is how we learn. Transform: Taking an idea and creating variations. Major advances are usually not original ideas, but the breaking point in a long history of progress by many different individuals. Combine: The most dramatic results happen when various ideas are combined together. By connecting ideas, creative leaps can be made. Fig. 3. Copy-Transform-Combine visual (own illustration) The morphological model fits perfectly into this approach. First, we can copy and transfer the functional modules from each of the technology drivers into a common space. Then the architecture is transformed into a large number of separated microservices. And for the combination of microservices for new SMAC applications, the morphological model can be applied. Assusming microservices within each technology driver the resulting set would comprise microservices that can be combined into new applications. Not all combinations will make sense and some may be mutually exclusive. Therefore, process and tool support can facilitate such an approach. A model for a collaborative morphological analysis has been described in [12]. With a lot of combinations in the solution space, there will likely be some reasonable ones in there with never-beforeconnected features. VII. APPLICATION SCENARIO: 3D PRINTER HUB Additive manufacturing (AM), a 3D printing technology, has made incredible advancements over the past decade and is now transforming the way manufacturing is done. AM can be used to improve quality, reduce costs and increase flexibility. It also allows new ways of engineering: structures become possible that were not producible in traditional manufacturing. Fig. 4. 3D printer hub ecosystem The initial idea of the Siemens 3D Printer Hub is to get an overview of available 3D printers in a company and their features. They are owned by different business units and positioned at different locations. Some of them may have free capacities that can be used by other employees if printer capabilities fit to their requirements. The 3D printing community is the innovative force for new digital services around the 3D printer hub. Know-how sharing on the hub platform will shorten learning curves and reduce non conformance costs. In the long term, the hub will become a digital ecosystem including services like scanning, accounting, 2D to 3D conversion, 3D model library and social collaboration features for the users. According to SMAC this will comprise:

5 Social: improvement of models by feedback and discussions, sharing of 3D models and collaborative design, Q&A regarding 3D printing. Mobile: access from and presentation on mobile devices, instant feedback of experts in transition, virtual reality with head-mounted smartphone, 3D scanning, drone delivery. Analytics: model optimization, matching of print requirements to printer features and utilization including location and pricing data, utilization statistics identify gaps in geographical distribution or available features. Cloud: repository for 3D data, computational power for finite element analysis, optimization of 3D-printed lattice structures for structurally efficient material distribution, lattice performance under tension, compression, torsion et cetera. Such a SMAC system can then be used as part of a domain specific SMAC application. Thus the following preventive maintenance scenario can be implemented: the preventive maintenance program of a wind turbine recommends replacing a wearing part before failure. With the help of the digital twin of the wind mill, the appropriate type and serial number can be identified. The according 3D model is retrieved from the cloud repository. Using that data the turbine orders the specific spare part from the 3D printer hub. The printer hub calculates the best match of required printer features, utilization of printers and distance to the wind mill. As a result the selected printer location and time of completion is sent to the wind turbine. So the turbine can coordinate the mobile delivery by a drone with the appearance of an available service technician matching the required skills profile to install the part. Many other combinations of services and associated business models are possible with such an SMAC ecosystem. If designed as an open platform, third parties can bring in additional SMAC systems or services and again broaden the range of possible applications. VIII. CONCLUSION AND OUTLOOK SMAC systems implemented as digital ecosystems are a promising approach in the digital world. It opens up a new perspective on the design of a wide range of products and digital services. The combination of technology drivers facilitates cross-competency innovation. In some domains, the concept should be extended and also cover security as a technology driver resulting in SMACS as according acronym. For example, blockchain technology could lead to a paradigm shift in this area. Data protection and individual control of data privacy can become a unique value proposition in a competitive market. Then, SMACS represents the big five of digital transformation. REFERENCES [1] Brynjolfsson, E., McAfee, A. (2014). The Second Machine Age, W. W. Norton & Company 2014 [2] Diana, Frank (2016). Technology, Social Change, and Future Scenarios. Retrieved from Frank Diana s Blog February 18, 2016 [3] Ferguson, Kirby. (2010). Everything is a remix. Retrieved from [4] Fey, V. R., Rivin, E. I. (2005). Innovation on Demand: New Product Development Using TRIZ. Cambridge, UK: Cambridge University Press, [5] Hildebrand, C., Shankland, P., Baya, V. (2012). Consumerization of APIs: Scaling integrations, PWC, Retrieved from [6] IDC (2015). 3rd Platform Transformation. Retrieved from [7] KPMG (2013). The SMAC Code - Embracing new technologies for future business, KPMG report Retrieved from cuments/the-smac-code-embracing-new-technologies-for-futurebusiness.pdf [8] Langen, M. (2014) Disruptive innovation with social computing: What comes next? Proceedings of the International ICE Conference on Engineering, Technology and Innovation, Bergamo, June [9] McKinsey (2012). The social economy: Unlocking value and productivity through social technologies [10] Mukherjee, S., Uzzi, B., Jones, B., Stringer, M. (2016). A New Method for Identifying Recombinations of Existing Knowledge Associated with High-Impact Innovation. Journal of Product Innovation Management, Volume 33, Issue 2, pages , March [11] PWC (2015). The connected workforce is talking SMAC. PWC report March Retrieved from [12] Zec, M.; Schneider, A.W.; Matthes, F. (2015): Towards a Process Model for Computer-Supported Collaborative Morphological Analysis. In Proceedings of the 21st Americas Conference on Information Systems (AMCIS), Puerto Rico, 2015