Internet of Things (IoT): the business value, concerns, trends, technology and starting point

By Johnny Johansen & Stanislav Sinyagin

IoT is one of the fastest growing technology trends, and significant investment is seen globally across industries and sectors, as well as in the consumer segment. The interconnection of potentially widely distributed and numerous mechanical and digital sensors, computing power and real-time analytics capabilities provide powerful insights and improved decision-making. In this article we explain how IoT adds business value, some existing concerns, the technology, its features and how you may start exploring IoT in your own organization.

How does IoT add value to organizations?

A number of applications - where data sensing, collection and analysis for research, monitoring and response are core functionalities - benefit greatly from IoT. Such systems integrate communications, control, information processing and presentation in a highly decentralized and not least cost-efficient manner. The emergence of new digital technologies in combination with existing ones, have made IoT a favorite investment target for organizations globally.

IoT sensors (explained in more detail below) have become so accurate, small-sized, and cheap that they may sense and forward data at volumes and speeds unimaginable until recently. IoT Gateways (see below) are able to aggregate, reformat and align heterogeneous data streams at levels not seen before. Wireless and wired networks nowadays offer transfer capacity suitable to larger data volumes. In addition, data analytics capabilities have become mainstream and affordable to most organizations. In total, this allows for sensing of data from literarily anywhere, with near real-time analysis and powerful insights for improved decision-making, learning and response.

Literally any business discipline or domain in the professional and personal space are ripe for adopting IoT for increased value generation, reduced time and cost, improved insights, higher quality decision-making, higher efficiency, increased brand equity and reputation. Let’s look at some of these domains:

Automation of offices, manufacturing buildings and homes: Buildings are subject to sensing of a wide range of data in order to predict issues and needs for regular maintenance, optimize energy consumption, space utilization trough occupants’ behavior analysis, monitoring of the environment at large, optimizing HVAC and cleaning requirements, and so forth. All these options represent opportunities for considerable cost and time savings, in addition to other efficiency gains.

Transportation: IoT platforms may integrate control, communications, and data processing in most transportation systems. The vehicle, the infrastructure and the driver interact dynamically for optimized user experience, value, security, and time efficiency. Common aspects enabled are inter- and intra-vehicular communication, vehicle control, logistics and fleet management, safety, road assistance, smart parking, electronic toll collection systems, and smart traffic control.

Medical and health care: IoT systems are now adopted for tracing of patients and medical equipment in hospitals and similar institutions. Real-time information about occupancy is realized through “smart-beds” and monitoring of physical space. Health and safety for patients and employees is further safeguarded through predictive cleaning, indoor air quality and touch-free feedback systems based on sensory data and real-time analytics. In addition, any medical patient data may in principle be monitored, and alerts set off in case of anomalies. A network of intelligent sensors is able to collect, process, transfer, and analyze valuable information in real-time, including the interconnection of in-home devices to hospital IoT systems. During the present COVID-19 pandemic, these are all features which can prevent virus transmission, spread and optimize treatment.

Manufacturing: IoT integrates the various devices involved in the manufacturing process, enabling swift manufacturing of new products, real-time optimization of production and supply chains, and flexible responses to new demands. Industrial IoT (IIoT) is expected to be a main catalyzer for “Industry 4.0” – the fourth industrial revolution – through network control and management of the manufacturing process, equipment, assets, and situational awareness. Other advantages include optimization of safety and security, reliability, and predictive maintenance.

Climate change: Studies show that IoT have huge potential in the fight against climate change, in particular the curbing and reduction of CO2 emissions as they relate to global warming. In the mobility sector alone, logistics and traffic management, traffic optimization systems, smart buildings and power management technologies provide huge potential for CO2 savings. Numerous other applications may be deployed, with resulting real-time analytics, improved insights, and quality decision-making.

Elder care: Smart homes or institutions for disabled or elderly have IoT features deployed for improved security, instant alerts following incidents, voice control of various aids, medical dosage monitoring and control, physical condition monitoring, etc. These features provide the individuals with more freedom and a higher quality of life, and caretakers with better insights and assurance of individuals’ well-being.

Military: When applying IoT for military reconnaissance, surveillance, patrolling and combat maneuvers, it is designated The Internet of Military Things (IoMT). IoMT applies all known IoT technologies and is influenced by future prospects of warfare and includes – but is not limited to - sensors, vehicles, robots, munitions, wearable biometrics, and other smart devices relevant to combat situations.

Finance, marketing, sales: Sensors will analyze (e.g. at outlets/branches and ATMs in banking) consumer behavior and register abnormal service and customer issues for improved real-time insights. Additionally, brand-specific mobile apps (e.g. online banking) provide valuable data about customers’ interactions and reviews – generating supreme market insights. Such dynamic insights are fed back to marketing and sales departments which will tailor messages to the various customer segments, proposing proactive services based on data-driven product planning and management. Additionally, micro-sensors on products provide information about when, where and how the product was used – insights which are highly valuable in a marketing and sales process.

Retail: Automated check-outs are implemented through wireless tag registration of items for purchase, and subsequent deduction from customers’ mobile payment apps as they exit the store. Personalized discounts and loyalty points will be awarded to customers in-store based on mobile apps registering their interest for particular items. “Smart” store shelves will track items and volume based on wireless tag monitoring, automating shelf re-fill and potential theft alerts. Through Infra-Red (IR) sensors customers’ in-store movements may be registered and analyzed together with other consumer data for optimization of the store layout, space utilization and specific product placement.

Agriculture: Through real-time sensing data related to weather, humidity, air quality, soil conditions, crop quality, etc. farmers will respond quickly to undesired changes – potentially saving entire crops. Other registered deviations may require swift responses like sprinkling, covering, fertilizing, and so forth for optimizing the crop quantity and quality. These processes are assisted by sophisticated data analytics for predictive response, thus even timelier actions to improve productivity, optimize land utilization, reduce waste, and improve the environment.

Security: One main principle and best practice in the security industry is to obtain quality information about locations, situations, assets, and threats which enable rapid and quality decision-making. In combination with traditional measures and data, IoT sensory data (e.g. imagery, sound, vibrations, motion, IR and scent) and real-time analytics add considerable value to the overall situational awareness from a security point of view. When such data and analysis is implemented correctly and aligned with security doctrines, they represent tools which until recently were not in the toolbox of security officials and practitioners. The IoT platform in use allows for an accurate and real-time understanding of the circumstances, centralized and powerful management and control, early anomaly detection, and efficient determination of false alerts.

Smart Cities: IoT technologies are increasingly used to develop, deploy, and promote sustainable development practices to address growing urbanization challenges in many cities. The network of connected devices senses and transmits data (e.g. from vehicles, traffic lights, road surfaces, garbage cans, parking meters) through cellular or other low power wireless networks to data analytics platforms via IoT gateways. The resulting real-time analysis assists municipalities, enterprises, and citizens to make better decisions that improve quality of life. Examples may be improved energy distribution, waste collection and management, decreased traffic congestion, and improved air quality. Smart cities are a viable response to the growing global population and urbanization, in order to reach the Sustainable Development Goals (SDG).

PR & Communications: IoT brings additional data for analysis and improved market insights for PR & Communication actors. Many are already using tools for monitoring and analysis of traditional and online social media outlets for targeted messaging, whereas IoT sensory data and real-time analytics will significantly add value in terms of rapid response to market changes, deviating public perception of clients and other trends.

Infrastructure: A key application of IoT is the monitoring, controlling and incident response capabilities related to critical infrastructure like airports, highways, bridges, railway tracks, power grids, windfarms, water supply, and waste management. Sensory data from strategic touch points and the real-time IoT analytics will reveal potential anomalies and enable the appropriate response in terms of preventive maintenance, repair, or incidents. Such modalities provide significant savings in time and cost, improved safety and security, increased service quality, in addition to the avoidance of downtime of critical infrastructure and services.

Energy Management: Devices like appliances, motors, pumps, actuators, lamps, etc. will be included in IoT systems for automation, central management, remote controlling, efficiency gains, optimization of energy consumption and cost savings. As for the power grid actors, they will benefit from sensory data (e.g. user data, advanced metering infrastructure/AMI data) for balancing of power generation and distribution, as well as automated functions with transformers and the like.

Human Resources: Within the legal boundaries related to Privacy and Employment laws and regulations, sensory data from employees’ behavior will be used to analyze and respond to certain circumstances. These might be based on the sensing of location, voice, movements, and so forth. The data may be pseudonymized with resulting insights being centered on the effectiveness of cross-functional teamwork, productivity correlated to the physical working environment and the impact of team size. Many other parameters may be included, and future HR departments will work closely with technical departments to develop solutions and apps in the interest of improving employee satisfaction, individual and collective performance, and corporate productivity.

Environmental monitoring: IoT technologies have a clear potential to positively impact sustainability, of which environmental monitoring is a direct influence. Sensory data provides insights related to environmental research, conservation, policymaking and compliance with laws and regulations. Such data is collected from land, air or water – seeking to determine which factors are behind the results. The very nature of an IoT system makes data collection swift and cheap, and larger amounts of data can be collected and analyzed in real-time. Applications could be early detection and alerts of forest fires, extreme weather, flooding, avalanches, soil health, air pollution, water quality and animal habitats.

Supply chains: With Global Positioning System (GPS) apps and Radio Frequency Identification (RFID) of shipments, enclosures and items, an IoT platform will provide precise data (e.g. item storage temperature, time in transit) about the supply chain. Such data may be analyzed together with other relevant data and improve the quality of the transportation. The platform may also be used for real-time monitoring and rectification of suboptimal supply chain conditions, process optimization and ensure that the products reach customers in a timely manner.

By the way - what are the IoT trends?

IoT is increasingly combined with other new and emerging technologies for additional business value: Big Data analytics, Blockchain, AI, etc. Further technology convergence is expected to occur in the foreseeable future.

IoT is poised to have one of the most significant impacts on sustainability. McKinsey has forecasted that the technology, which consists of a vast network of internet-connected devices, could produce as much as $11.1 trillion in economic value annually by 2025. An analysis of 640 IoT projects by the World Economic Forum found that 84% of them could help achieve the United Nation’s Sustainable Development Goals (SDGs) - 17 goals adopted by all of the UN member states to promote prosperity and protect the environment.

Larger enterprises already invest significantly in IoT, with an impressive anticipated growth rate for the next few years. The International Data Corporation (IDC) forecasted global IoT spending to sustain a compound annual growth rate (CAGR) of 16.7% through the 2017-2021 period reaching $1.4 trillion by 2021.

According to a 2018 study from the World Economic Forum, 70–75% of IoT deployments were stuck in the pilot or prototype stage, unable to reach scale due in part to a lack of business planning. This is often a sign of missing strategic ownership, inadequate resources, and siloed initiatives. Contemporary studies indicate that proof-of-concepts, pilots, and prototyping are less likely to lead to real business value generation than bolder initiatives where “quick wins” are identified and rapidly rolled out – often at limited scale - to demonstrate early business value. Such a modality tends to engage organizations, gather strategic support and spark required scale-up and support for other similar initiatives.

SMEs are lagging in IoT adoption due to a number of reasons. They often lack the in-house resources to stay tech-savvy, have limited financial muscles, are often focused on their core business activities to stay afloat - with little or no time for strategic evaluation of new and emerging technology. Additionally, the up-front investment is not appealing, even if “quick-wins” and obvious business value are within reach. As an example, 51% of UK SMEs were either unsure or unaware of IoT, while 23% stated no interest at all. We know that SMEs are the backbone of every economy, e.g. offering 2/3rd of private sector employment in Europe and the US. Despite this, SMEs face several serious challenges: attracting investors, maintaining stable finances, scaling their operations, and hiring talent. Some of these challenges may in fact be countered by the very features of IoT: reducing cost and time consumption, improving security, enhancing scalability, proofing supply chains, and enhancing market knowledge. Furthermore - the brand of any SME which moves into the digital era will positively alter. Its attractiveness as a supplier, partner, employer, and investment object will increase significantly.

 IoT-as-a-Service are being offered by certain providers, where a complete IoT system is deployed against standardized service fees. These solutions come with all the hardware included, and the customer may only determine the purpose of the implementation, from which the scope, deliverables, schedule and cost will be defined. The embedded service analytics will provide the customer with the desired insights and tools, in accordance with a pre-determined Service Level Agreement. Such an offering is particularly appealing to organizations and companies which are seeking to reduce their hardware footprint, transform CAPEX into OPEX, reduce up-front technology investments and to avoid in-house swelling of technical departments.

 What are the present concerns related to IoT?

 Many organizations and companies lack strategic awareness of the real value proposition of IoT and its applications. The industry itself suffer from complex and technical jargon which is highly unappealing to board members, executives, and other influencers and decision-makers. This is a commonality in that technology with high value potential for many organizations is not considered due to its complexity and the lack of obvious business value. It is up to the industry and technology strategists and advocates to articulate value propositions, present use cases and educate beyond its inner circles for a wider adoption of IoT. Board members and executives play a crucial role in gaining awareness of business opportunities and value from emerging technologies.

Concerns have arisen about the rapid development and deployment of IoT systems, with potentially suboptimal considerations of the security challenges involved, including the lack of regulatory changes. Though several security considerations are common with other traditional technologies (e.g. servers, computers), many IoT devices have limited operational capabilities and are not conducive to supplementary security features. Certain other parts of the IoT dataflow chain may be secured with existing measures, including the wireless transmissions, but standardized and hardened end-to-end security has not been a default feature. International organizations, industry associations and governments are addressing these issues, whereas present IoT deployments require highly professional designs, implementations, and maintenance in order to operate securely.

Both hardware and software lack standardization and prevents full interoperability. This is also the situation for the wireless standards in use, even though modern gateways may operate with various standards and protocols. With such fragmentation, applications will not function consistently between different IoT platforms, and patches and security updates may suffer from inconsistent deployment. Industry initiatives are on way to rectify such incompatibilities, which will improve interoperability and security significantly.

National and international governing bodies have been slow in regulating IoT, which has led to a certain reluctance in investment. This is commonly observed with several other disruptive and emerging technologies, e.g. blockchain. Governments and inter-governing institutions are looking at aligning regulations and demands for interoperability, transparency and privacy which will address such concerns.

Like with certain other technologies, IoT represents a significant potential for social control and political manipulation in the hands of malicious actors. This goes beyond ordinary privacy concerns, in that IoT sensors in principle may be set up to sense and forward any kind of information without any compliance-based central management function. As recent data protection laws (e.g. GDPR in the EU) are technology agnostic, any collection and sharing of personal data is legally covered. I.e. it is not the location of the data sensors, the analytics or the holders of the data which determine the jurisdiction, but rather the geographical presence of the owners of the data. Other jurisdictions are expected to follow suit in regulating such data processing for their population.

Sensors in IoT systems forward potentially huge amounts of data for analysis, with public cloud systems commonly being used as storage and processing facilities. With the exponential growth in IoT and other data-driven technologies, data storage capabilities will equally expand. Internet-related activities already make up 5% of all energy consumption, leading to critical voices advocating for a slower implementation of new technologies and/or a halt until more energy-efficient devices are developed. Other generic concerns relate to the environmental impacts of manufacturing and disposing of semiconductor-rich devices, which exist across most technologies at present. Enterprises specialized in extracting metals and liquids from disposed electronics are presently offering solutions to such concerns.

So how does this all work?

Essence: IoT consists of a combination of hardware (mechanical and digital machines/sensors), software, algorithms and computation connected in a network. Objects in an IoT system commonly respond intelligently to particular situations and carry out specific tasks and are provided with unique identifiers (UIDs). Such a system senses and collects data as a primary activity, thus it is highly dynamic by nature. Common characteristics are scalability, modularity, extensibility, and interoperability. An IoT system has the ability to carry out tasks without human interaction. Due to the convergence of several technologies, data analytics, machine learning, commodity sensors and embedded systems, the capabilities of IoT and what its definition is has evolved significantly in recent years.

Brief History: Network-connected appliances did see daylight already in the 1980's - before Internet and IoT as concepts were realized. As an example, a soft drink vending machine at Carnegie Mellon University reported inventory and temperature to a centralized unit as one of the first "IoT" projects. More research, pilots, projects, and publishing went on through the 1990's, but IoT as a separate concept did not materialize until "things" or "objects" connected to internet reached a critical number. This number exceeded the number of people connected to internet sometime in 2008-2009 and is regarded by most academics and practitioners as the birth of IoT. In parallel, the evolution of microprocessors started to provide required capacity to sensing, collection, transfer, communication and analysis of data. Designers were able to standardize, simplify and optimize embedded systems, lowering prices considerably through mass production and subsequent economies of scale. These technology evolvements introduced small-sized, energy efficient and cheap semiconductors which gave IoT systems sufficient "brain power" to handle large amounts of data at high speed. In addition, multiple new wireless network capabilities were developed, providing the necessary last-mile connectivity for decentralized hardware (things). Other advances through the 2010's included Machine Learning (ML), real-time analytics, Cloud Services, Blockchain, etc. which started to converge - introducing IoT capabilities with real business value.

System: The basic architecture of an IoT system is commonly split in three tiers:

1. Devices, 2. Edge Gateway, 3. Data Storage/Processing

Tier 1 This tier includes the actual “things”, like sensors and actuators for data sensing/collection and mechanical or electronic responses to certain triggers, respectively. Examples of sensing data could be sound, temperature, vibration, pressure, smoke, electromagnetism, moisture, luminance, image, proximity, humidity, motion, weight, liquid levels, position, video, acceleration, gas, Infra-Red (IR), and so forth. The sensors will register events or changes in their environment and transform those into analog or digital (commonly) signals which subsequently are transmitted to other IoT components for further analysis or pre-programmed responses. The sensors vary in sophistication from Base, Smart to Intelligent – spanning from only forwarding the measured value all the way to integrated behavioral adaptations. Actuators are typically mechanical devices (electric, hydraulic, pneumatic, thermal) able to grip, carry, push, turn, and so forth, in order to execute a response to specific commands. One example could be a sensor detecting sound from an elevator system being analyzed by centralized cloud-based algorithms – giving alerts in case of deviations or anomalies for early detection of issues or predictive maintenance needs. Or even automatically slowing down the speed or completely shutting down the elevator if the anomality exceeds a predefined level. Being network-connected, the entire process may be monitored and controlled by different actors with varying degrees of information granularity. The accuracy of sensory data is crucial as highly critical decisions may be made upon the analysis of such data. The calibration of sensors is imperative, and the regular checks and potential re-calibration must be well defined and performed. The rapid evolvement of sensors has been one major reason for the growth of IoT as they have become advanced, accurate, small-sized, and low-cost. At a reasonable price, sensory data may be collected these days which was not even possible a few years back. Other “things” in an IoT system range widely from smart-TVs to train tracks and agriculture sprinkling and fertilizer devices.

Tier 2 The “things” - devices - in an IoT system will typically use different standards and protocols for various types of data and communication of this data. The IoT gateway handles the translation of these protocols, aggregates the data, pre-processes data for further analysis, and encrypts and sends the data to the analytics center. The devices are connected to the gateway through a wireless network like Bluetooth, Zigbee, Z-wave (short-range) or like LTE, LTE-M, WiFi, LoRa, 5G (long-range). The gateway itself is typically connected to internet via a wired Ethernet LAN or fiberoptic cable connection, but could also utilize a wireless connection. It is important to note that this is a two-way communication channel, i.e. the gateway may equally be used to remotely control, update, configure and secure the IoT devices. By pre-processing the data at the edge of the IoT system (edge computing) before transmitting to the analysis platform, unnecessary data, inaccurate data and incompatibilities are removed resulting in reduced latency and improved response rates. The edge gateway additionally acts as an extra layer of security defense, and additionally makes sensors and actuators more energy efficient by allowing short-range communication protocols to be used for local data transfer. Some scholars and practitioners have claimed the data aggregation and internet connection to be a separate component of the IoT system than the edge pre-processing function. For simplicity we have chosen not to elaborate on that distinction.

Tier 3 Storing and analyzing the sensory data may take place in a traditional centralized data warehouse or data lake, in a cloud set-up or as a blockchain solution. Commonly a cloud solution is chosen due to the huge volumes of data, ease of implementation, existing templates for various analytics requirements and cost-efficiency at the initial phase (no up-front hardware/software investment). The authors would like to add that blockchain should be investigated as a viable alternative due to its cost-efficiency, security and immutability nature – which increases trust in the data and reduces reliance on single points of failure. Data from IoT sensors represent both big (more common) and small data, complex and simple data. However, most often the data come in a wide variety, in large volumes, in several different formats and at high speed. I.e. significant demands are put on the sensor, gateway, and not least analytics capability. Sensors and gateways have evolved into high-speed and accurate IoT components, and new technologies have made it possible to analyze data in real-time, without the latency associated with batch-processing like in the past.

Evolvement: IoT as a technology is evolving by the day. Sensors and actuators are becoming more accurate, smaller, and cheaper. Gateways can translate, sort and forward data faster. Networks are becoming faster and more reliable at the edge of the system. Real-time analytics is constantly improving. At the time being, around 15 billion IoT devices are deployed, with an expected 25 billion by the end of 2021. A significant growth in IoT investment will continue, and companies will increasingly seek end-to-end solutions for rapid deployment, effective adoption, cost-efficiency, minimal CAPEX and “quick wins”. In other words, current vendors and service providers will need to adapt to larger IoT-as-a-Service actors in the market.

Yes, I would like to introduce IoT in my organization – but where do I start?

As with all new and emerging technologies, the first step is to acquire knowledge about them, the impact they have on your industry and business, what your competitors are doing with these technologies and subsequently create a benchmark for your own organization. If your strategic goals and objectives indicate business needs – opportunities or problems – where IoT would serve as a solution (it should!), you may want to test the business value through use cases. Then follows a strategy alignment, road map, investment analysis, requirements gathering, design, implementation and operationalization. One thing to keep in mind is that it is always a blend between new and existing technology that bring the forward leaps. Hence, do not rely on new and emerging technology entirely. Start with a limited initiative where one or more “quick wins” can be achieved. Expand as you and your organization gain further insights and identify other areas where real value may be generated. As for any such initiative, you need to make sure you have the available capabilities – from strategy analysis through design all the way to operationalization and continuous improvement and support. Only then will you be able to generate real and sustained business value from your investment in IoT technology.

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Please find below a list of literature on the topic of IoT, Digital Transformation and Change Management for further study - some of which informed this article with facts and figures:

Altimeter (2019) State of Digital Transformation. https://insights.prophet.com/the-state-of-digital-transformation-2018-2019

Bain & Company (2017) Orchestrating a Successful Digital Transformation. https://www.bain.com/insights/orchestrating-a-successful-digital-transformation

Davies, J. & Fortuna, C. (2020) The Internet of Things: From Data to Insight. John Wiley & Sons, NY, USA

 Furr, N., Gaarlandt, J. & Shipilov (2019) Don’t Put a Digital Expert in Charge of Your Digital Transformation Harvard Business Review, MA, USA. https://hbr.org/2019/08/dont-put-a-digital-expert-in-charge-of-your-digital-transformation

Habib ur Rehman M., Ibrar, Y., Salah Muhammad, K., Prem Prakash, I. & Charith Perera, J (2019) The role of big data analytics in industrial Internet of Things. Future Generation Computer Systems. Vol.99, pp.247-259.

Harvard Business School Publishing (2003) Managing Change and Transition. Harvard Business School Press, MA, USA.

Herbert, L (2017) Digital Transformation: Build Your Organization's Future for the Innovation. Bloomsbury Publishing PLC, UK.

Jick, T. D. (1989) The Challenge of Change. Harvard Business School Case Note 9-490-016, MA, USA.

Kotter, J. B. (1990) A Force For Change: How Leadership Differs From Management. The Free Press, NY, USA.

Kranz, M. (2017) Success with the Internet of Things Requires More Than Chasing the Cool Factor. Harvard Business Review, MA, USA

Mohamad Noor, M. binti & Haslina Hassan, W (2019) Current research on Internet of Things (IoT) security: A survey. Computer Networks, Vol.148, pp. 283-294.

 Saldanha, T. (2019) Why Digital Transformations Fail: The Surprising Disciplines of How to Take Off and Stay Ahead. Berrett-Koehler Publishers, CA, USA.

SAP 2017 global study on Digital Transformation. https://www.forbes.com/sites/adigaskell/2018/06/08/the-slow-pace-of-digital-transformation/#40f26e8d491b

Siebel, T. M (2019) Digital Transformation: Survive and Thrive in an Era of Mass Extinction. RosettaBooks LLC, NY, USA.

Statista (2020): Internet of Things (IoT) - Statistics & Facts. https://www.statista.com/topics/2637/internet-of-things/

 Tabrizi, B., Lam, E., Girard, K. & Irvin, V. (2019) Digital Transformation Is Not About Technology. Harvard Business Review, MA, USA. https://hbr.org/2019/03/digital-transformation-is-not-about-technology

Westerman, G., Bonnet, D. & McAfee, A. (2014) Leading Digital: Turning Technology into Business Transformation. Harvard Business Review Press, MA, USA.

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Johnny Johansen is an international executive who specializes in effective technology governance, enterprise risk management, compliance and strategic level information security and data protection practices.

He guides organizations, board members and C-suites on how to strategize innovation and other emerging technology change initiatives, and lectures at various forums in business analysis, privacy law and data protection, risk-based audit and BCM/DRM.

Johnny is a Partner in Superius, a management consulting group based in Geneva, Vaud, Aargau and Zurich, Switzerland.

As one of the founders of TILLIT Partner, he also advises and supports companies on various organizational aspects related to change initiatives, governance and process optimization, contemporary risk management, digital transformation, and Mergers & Acquisitions across different cultures and industries.

Stanislav Sinyagin is a senior systems engineer who has worked with most information technologies and offers a rare combination between a problem-solving mindset and deep technical insight. He has experience from global enterprises as well as SMEs, both as an internal and a consultant, including project and vendor management at a Fortune 500 global enterprise.

He is also a hands-on tech-developer, providing clients new ways of processing and securing their transactions and data through the use of new and emerging technology.

Stanislav is a Partner in Superius, a management consulting group based in Geneva, Vaud, Aargau and Zurich, Switzerland.

As founder and owner of K-Open, he also offers solutions like network design, custom software development, integration, automation, project-, SLA- and vendor management.