In my last post, I had detailed the key tips to do it right, pitfalls to avoid, typical Organizantion R&R in the quest for organizations to attempt digital transformation. In this post, I will focus primarily on the outlook, optimization, innovations that can be cornerstone of any digital transformation journey.
IDC estimates that 40% of all technology spending will be applied to “digital transformation,” with enterprises spending nearly $2 trillion by the year 2022. The trouble is, few businesses understand how to maximize their investment while also keeping the business at peak performance. Additionally, companies don’t always explore all the ways that services, processes and digital partnerships can support their digital strategy.
Quite often, executives spend considerable budget on digital programs, only to find they haven’t achieved the desired results. What’s more, digital investments have led to confusion among employees and partners alike, whereby teams are pulled in two very different directions: On the one side are technical and operational requirements, legacy technologies, tight timeframes and cost pressure; on the other are creativity, modernization, innovation and groundbreaking products or services.
Nowhere is the postmortem of troubled digital partnerships more evident than in Agile software development projects. Applied correctly, Agile can be an effective and game-changing collaborative tool to build applications quickly and deliver real business value. However, it’s not uncommon for partners to quickly assemble software that doesn’t fully align with business goals or fails to achieve a desired impact.
We need to address how companies and executives can better understand the full implications of digital pursuits and devise a digital strategy to get the most out of these endeavors.
Before embarking on a digital initiative, it’s important to develop specific and mutually agreed-upon business metrics and goals. Doing so helps align companies and their respective partners. Additionally, three strategies ensure companies maximize their digital efforts, investments and experience:
Develop the business skills of your digital team. Digital talent should support more than just doing “digital stuff;” they should also ensure their efforts support company performance. Too often, teams don’t have the insight or training to align technology with business issues and concerns. Spend time with the digital team to ensure they understand how the company works, identify the success metrics that are most meaningful to the health of the company, and choose the technology approaches to meet those goals.
Forge meaningful partnerships. Companies typically approach their digital challenges in one of three ways: build their own technology, buy technology and talent by acquiring a strong digital player, or find a partner that can synergistically help them grow and benefit from the combined strengths of both companies. Enlisting the help of a strategic partner is essential for companies that lack core digital skills to build modern, high-impact products and experiences.
Smart enterprises share risks and rewards with their partners while staying focused on a common vision. While selecting the right partner is often about operational and financial efficiencies, businesses today also expect partners to have “skin in the game” and be willing to share risks as well as reap rewards.
Build a culture of collaboration. Encouraging a culture of collaboration introduces new thinking and skill sets that enable both the company and its digital partner to work together to increase quality without compromising delivery. Internal and external teams are held to the same KPIs, measuring velocity, quality, product impact and autonomy, which allows for a seamless transition upon rollout.
One of the tangible outcomes of building a collaborative culture is the ability to put in place better processes and workflows, especially when it comes to testing automation. With our model, new product engineer sprints are implemented with a primary focus on building out an MVP (minimally viable product). In turn, this allows for the rapid build and evolution of upcoming platform features, and the potential to reduce testing time from months to a handful of weeks – saving millions of dollars.
Innovating While Running the Business
In today’s fast-moving digital marketplace, companies don’t have the luxury of time. Businesses must incorporate new products and technologies swiftly and in parallel with ongoing commercial activities. No company wants to hit the pause button on revenue-generating services or products.
This represents the real opportunity with digital: transform your business for tomorrow without stopping your business from performing today. I’m willing to bet $2 trillion that you like the sound of that.
Please feel free to review my other series of posts
In my last post, I had detailed the key approaches to Digital Transformation. In this post, I will focus primarily on useful tips, prominent roles, all the known pitfalls for any digital transformation journey.
The idea is to understand all the learnings from different customers experienced on their digital transformation journeys and ensure that one takes good care in not succumbing to known issues. The posts also lists some best practices that should be embraced for the entire journey, this will make the implementation more efficient and effective and less cumbersome for the people involved.
DIGITAL TRANSFORMATION TIPS
Let us briefly cover the six tips that govern a successful digital transformation journey
The question remains: when should you make preemptive changes? The observation of biological systems teaches us that it is optimal for companies to begin searching well before they exhaust their current sources of profit, and that firms should use a mix of ‘big steps’ to move to uncharted terrain and ‘small steps’ to uncover adjacent options at low cost. Regardless, having a strong bias toward change is critical.
Software engineers, cloud computing specialists and product managers remain key roles for companies seeking to roll out new products and services. DevOps leaders galvanize software development by merging development with operations, enabling companies to continuously iterate software to speed delivery.
Data scientists and data architects are also in high demand, as companies seek to glean insights out of vast troves of data, and transformations lean increasingly on machine learning and artificial intelligence.
Plus, IT departments supporting business-wide transformations also require UX designers, digital trainers, writers, conversational brand strategists, forensic analysts, ethics compliance managers and digital and workplace technology managers.
DIGITAL TRANSFORMATION PITFALLS
Digital transformations are lagging or even failing for several reasons, including poor leadership, disconnects between IT and the business, lagging employee engagement and substandard operations.
The primary obstacles include the ability to move fast and to innovate while stripping down legacy processes and technical debt investments that have served us well for a long time. The key culprits of a derailed digital transformation are obsession with big bang change, focus on cost cutting as a business driver, and failure to loop in the business.
Boardrooms and C-suites talk about digital and there is pressure to show something and show results, which creates wrong expectations about how quickly what can be done and when. When the investments don’t pay off, people blame the CIO, who finds himself or herself out of a job.
Moreover, approaching digital transformation as a technology journey independent of the business is a recipe for failure. If a clever CIO comes up with a clever idea to change something with new tech, that’s great. The next step is bringing it to the business and having the business own the process. When they own the process, you drive end-to-end transformation that includes processes, people, policies and tech. The siloed approach always fails.”
A typical role distribution for digital jobs within a company is depicted below for reference.
Adapting to change is nothing new in our industry. But the unprecedented pace of change and colliding trends like the internet of things, digital partner ecosystems, rapid cloud adoption, and machine learning are creating the perfect storm. A storm that is changing the business landscape. There is no one size fits all approach to digital transformation, each strategy will be unique to each organization. However, a focus of balancing activities across the right business model, right partners, right technology, right mindset provides the compass to guide a successful transformation.
Stay tuned…. Part 4 of this foray, we will look into some of the outlooks, optimizations and innovations that are key to any Digital transformation journey.
Please feel free to review my other series of posts
In my last post, I had quickly given a glance to my readers a brief on Digital Transformation – its definitions and elements. In this post, I will look through the Key approaches involved in the digital transformation journeys
Present and future shifts and changes, leading to the necessity of a faster deployment of a digital transformation strategy, can be induced by several causes. This is often at the same time, on the levels of customer behavior and expectations, new economic realities, societal shifts (e.g. aging populations), ecosystem/industry disruption and (the accelerating adoption and innovation regarding) emerging or existing digital technologies. In practice, end-to-end customer experience optimization, operational flexibility and innovation are key drivers and goals of digital transformation, along with the development of new revenue sources and information-powered ecosystems of value, leading to business model transformations and new forms of digital processes. However, before getting there it’s key to solve internal challenges as well, among others on the level of legacy systems and disconnects in processes, whereby internal goals are inevitable for the next steps. The human element is key in it on all levels: in the stages of transformation as such (collaboration, ecosystems, skills, culture, empowerment etc.) and obviously in the goals of digital transformation. Since people don’t want ‘digital’ for everything and do value human and face-to-face interactions there will always be an ‘offline’ element, depending on the context.
Hence A digital transformation strategy aims to create the capabilities of fully leveraging the possibilities and opportunities of new technologies and their impact faster, better and in more innovative way in the future. A digital transformation journey needs a staged approach with a clear roadmap, involving a variety of stakeholders, beyond silos and internal/external limitations. This roadmap takes into account that end goals will continue to move as digital transformation de facto is an ongoing journey, as is change and digital innovation.
The way we successfully strategize will be based on we ask the right questions and collect right/adequate responses. The illustration below depicts this in a detailed fashion.
Many executives feel like they are viewing a good jigsaw puzzle that they have to finish, and they have a bunch of pieces but they don’t know if they have all the pieces, and they don’t know what the finished picture looks like. As mentioned this doesn’t happen overnight and requires a series of incremental steps. And here the goal or ‘the what, why and how’ becomes a mix of intermediate goals and broader objectives within which they gain more significance.
5 Steps in Digital Transformation
Finally, the reason why we would prefer to speak about accelerated business transformation or, if needed, digital business transformation, is that it’s just a matter of time before no one makes a distinction between digital and physical or offline and online. Customers, for instance, don’t think in these terms at all, nor in the terms of channels.
How to lead a digital transformation
To meet shifting customer expectations, many CIOs are aligning with key executives, making sweeping organizational changes, reskilling employees, setting up innovation labs and experimenting with emerging technologies to meet strategic mandates issued by their CEOs and boards.
One of the first things companies should do in embarking on a digital transformation is answer the critical question: What business outcomes do you want to achieve for customers? It definitely starts with the business outcomes and the new business models you are going after and working backwards from there. Here, a keen understanding of your customer journey map and lifecycle is key. Consider the process of settling an insurance claim, which typically takes 7 to 14 business days and requires a lot of paper shuffling. Thanks to algorithms and mobile applications, consumers and claims officers can resolve claims in minutes.
Approach to Digital Transformation
Digital transformation hits each industry. But it can also affect all activities, divisions, functions and processes of the organization as it can impact the very business model as such.
CapGemini Consulting was one of the first to come up with the concept of digital transformation and a digital transformation framework as you can see below. The company did so in collaboration with the ‘MIT Center for Digital Business‘ during a three-year study which defined an effective digital transformation program as one that looked at the what and the how.
The McKinsey chart below shows just aspects where digital transformation can play:
The (digital) customer experience (as said, de facto a key element with many digital transformations being a mix of customer experience optimization and process improvement – and cost savings).
Product and service innovation where, for instance, co-creation models can be used.
Distribution, marketing and sales: another usual suspect and in practice an area (along with customer service) that is often one of the earliest areas undergoing digital transformations.
Digital fulfillment, risk optimization, enhanced corporate control, etc.
Others we can add include:
Intelligent information management (with information, data and the processes they feed being key and a focus on activation).
Work, human resources, new ways of collaborating, workforce engagement and enablement (agile working, social collaboration, enterprise collaboration, unified communications).
Learning and education.
Procurement, supply chain management (with the digital supply chain) and supplier relationships.
It’s important to remind that in a digital transformation (and, for that matter digital business) context, all these aspects, functions, processes, etc. are interconnected and silos have less (or no) place, not from a technological perspective but most of all also not from a process and people perspective.
Stay tuned…. Part 3 of this foray, we will look into the tips, key roles and pitfalls to any Digital transformation journey. Please feel free to review my earlier series of posts
Please feel free to review my earlier series of posts
In this series of posts, I will take a deep dive into Digital Transformation – the word/feeling/term that has taken the world by a storm. I have this word being referred to at lunches, coffee catch ups, and informal meets round the street corner and not to forget in almost all formal leadership summits. Hence I felt it will be very useful for me to indulge further upon this subject for the sake of all you netizens. In this series of posts, I will look through the evolution of the digital economy and then follow it up with its elements, approaches, areas, Strategies, industries specific implementations and last but not the least its importance beyond technology.
Digital transformation is the thoughtful transformation of business and organizational activities, processes, competencies and models to fully leverage the changes and opportunities of a mix of digital technologies and their accelerating impact across society in a strategic and prioritized way, with present and future shifts in mind. Just to keep it simple, an alternate definition would mention it as something that refers to converting processes, activities and models to meet digital economy requirements until the company is a fully networked digital organization.
Businesses have always been changing and innovating, technologies always came with challenges and opportunities, regulations and ecosystems have always evolved. That’s nothing new. It’s in the degree of interconnectedness and of various accelerations, which require profound enterprise-wide change, that digital (business) transformation is to be seen as more than a buzzword but as a challenge, force and most of all opportunity for organizations that will enable them to achieve the core business competencies they need to succeed in rapidly changing environments. So Why is it needed? Let us see below.
We need to make sure we speak the same language and it’s important to emphasize that digital transformation is not just about:
Digital marketing, even if that’s an important part of the business activities and if it’s the context in which digital transformation is often used.
Digital customer behavior, although it plays a role and customers are increasingly ‘digital and mobile’.
Technological disruptions because the disruptions are always about customers, workers, markets, competitors and stakeholders, even if related to technological evolution and knowing that ’emerging’ technologies indeed can have a ‘disruptive’ effect.
The transformation of paper into digital information as originally meant nor the digitization of information (flows) and business processes, which is simply a condition sine quod non.
Components of Digital Transformation: The basic seven elements of digital transformation that are required for you as an organization to lead a digital change is below.
Leadership and Vision: It’s required for you as an organization to inculcate the thought process and clear vision in leadership. This particularly means that the leaders and management must stimulate the right digital culture. They should focus on improving the organizations operations, revenue, customer experience and competitive position. They should have holistic view of the digital threats and opportunities. They should be able to utilize the collective intelligence to reshape the competitive landscape.
Formulating strategies: The organization should be able to define the outcome or result to help achieve the business goals. It should then work backwards to make a compelling digital transformation strategy. It should optimally harness technologies to deliver the value proposition. It could then utilize the niches like augmented reality, geo-location, and social media integration to extend the overall capabilities of the journey
Information Governance: The organization should have formulated a strong governance plan and apply a strategic approach and then move to cloud applications to expand the reach
Focus on Customer Journey: The organization should be able to identify customer needs with an accurate study of customer behavior and then should diversify customer experiences by utilizing the customer data, advanced analytics, online customer surveys and data mining tools.
Define Technology Road map: The organization should align the strategic priorities towards long term planning before the actual tool investment with a well-defined technology road map. This should be followed up to enhance the existing technology stack with the latest tools to match current and future business needs.. This will help leverage technology to increase RoI, improve product and service portfolio, boost productivity and enhance customer satisfaction
Business Disruptor: Businesses need disruptive elements like digital automation, collaboration tools, and enterprise analytics platforms. These help optimize, evolve or transform the entire value chain. Disruptive elements help organizations by modifying or replacing told methods with more faster and integrated ways of working across all the levels.
Utilizing Technology: Big data allow businesses to have an incredible amount of data to analyze and guide business decisions. AI carries out precise predictive or prescriptive analysis for active strategy development. Many businesses are also now using the ISO for information security controls to keep their clients’ data secured.
In overall essence the components help seek your way around the digital transformation to drive the digital way of change for your business.
Let us also quickly take a look at the general challenges that we face in the digital transformation journey so as to keep them in mind when we look at key approaches.
The right approach to digital transformation hence allows companies to adopt new technologies that meet the ever-increasing customer expectations. Additionally, cultural transformation is also critical as part of the digital transformation process. It must align with organizational norms along with their risk-taking capability to define and deliver compelling customer experiences. Based on these experiences, the new business models and operational processes are derived, which, in turn, drive the investments in technologies.
Stay tuned…. Part 2 of this foray, we will look key approaches to Digital transformation.
Please feel free to review my other series of posts
Just a recap, in my previous post, I had taken a deep dive into the growth and trends in the IoT space. This will be the concluding post for this series where we will discuss the Industries where IoTs have been successfully implemented.
According to Internet of Things spending data and forecasts, published early 2017 by IDC, the 3 main industries in terms of IoT spending in 2016 were, respectively, manufacturing, transportation and utilities. Consumer Internet of Things spending ranked fourth.
While globally in the period until 2020, manufacturing will remain the major industry (except in Western-Europe) there will be global changes in this top 3. Among the fastest growing industries in the period until 2020 are insurance, healthcare, retail, consumer and, as mentioned, cross-industry initiatives.
Obviously, there is a difference between Internet of Things spend and number of Internet of Things projects.
A report by IoT Analytics, really a list of 640 real-life Internet of Things projects, indicates that from the perspective of number of projects connected industry ranks first but is closely followed by smart city implementations (where we mentioned the report), which rank second.
Internet of Things in MANUFACTURING
The Manufacturing industry has always taken the lead in the implementation of IoT, given the origins of IoT i.e., RFID. Hence the most early typical use cases have kept this industry in the lead but not for long. In 2015, it was estimated that there were 307 million installed units in the manufacturing industry where systems with sensors have always been embedded into manufacturing and the automation processes. And that it would reach $98.8 billion by 2018 in manufacturing operations through efficiency optimization and connecting the automated areas. By and large the 3 top IoT use case in this industry are listed below.
A majority of manufacturers has deployed devices to collect, analyze/measure and act upon data. More than 34.6 percent of these companies had already implemented devices and sensors to gather this data and another 9.6 percent were about to implement IoT devices within a year. Only 24 percent from manufacturing industry had no plans to implement devices to collect, analyze and act upon data.
Retailers are working with the Internet of Things for several innovative and immersive approaches, ranging from virtual closets and self-checkouts to smart shelves (inventory accuracy) and connected vending machines.
The Internet of Things in the RETAIL business
Retail is moving up fast, both in operations and customer-facing circumstances. The emphasis is primarily on efforts to digitize the consumer experience. It is mainly in the optimization of processes and of logistics that the Internet of Things offers immediate benefits to retailers. However, obviously the customer-facing and inventory-related aspects matter a lot too. The use of the Internet of Things in retail, among others, changes customer experience, leads to better customer insights, enables new collaborations and business models and further blurs the line between digital and physical in an in-store context.
Retailers are working with the Internet of Things for several innovative and immersive approaches, ranging from virtual closets and self-checkouts to smart shelves (inventory accuracy) and connected vending machines.
The Internet of Things in GOVERNMENT AND CITIES
The Internet of Things is already used across several government activities and layers the sector is a very vast ecosystem and so are the many IoTs use cases in government. Probably the best-known usage of the Internet of Things in a government context concerns smart cities, in reality mainly smart city applications.
Smart city projects are what people hear about most and they get a lot of attention, among others because smart city applications are close to the daily lives of residents. Another reason why smart cities are often mentioned is that defacto smart city projects account for a big portion of Internet of Things deployments. Think about smart waste management (often a local matter), smart parking and environment monitoring.
Another area where we see the Internet of Things popping up is in citizen-facing public services. To a large extent smart city uses cases overlap with Internet of Things use cases in public services as one of the key tasks of a city is to serve the citizens. However, with public services we also go beyond the local/urban level but also includes smart energy. The degree of overlap depends on the way government services are organized in a particular country or region.
Improving citizen satisfaction is the main objective when considering or implementing the Internet of Things and other emerging technologies. Moreover, governments have a role in public health which can be enhanced by taking initiatives using the Internet of Things and in collaboration with private a state-sponsored partners. The same goes for public safety by the way. An example: collaborations between governments and insurance firms, leveraging telematics.
There are really hundreds of ways in which governments leverage and can leverage the Internet of Things to improve citizen experience, realize cost savings and, not to forget, generate new revenue streams.
The latter is quite important as many IoT projects have an impact on the funding of cities. A simple example: if you have a perfectly working smart parking solution in a city, you lose revenues for all the obvious reasons. So, it’s not just a matter of technologies but also of finding creative ways to turn enhanced citizen experience and citizen services in a global picture that is beneficial for everyone.
This takes time, planning and, as you can imagine, given the complexity of the government ecosystems, lots of alignment and coordination.
The Internet of Things in BUILDING AND FACILITIES
The Internet of Things plays an important role in facility management, among others including data centers and smart buildings. The integration of IT (Information Technology) and OT (Operational Technology) plays an important role in this regard. Smart buildings are among the fastest growing cross-industry Internet of Things use cases in the period until 2020. Moreover, research indicates that data collection from buildings and other structures such as HVAC is already high. Last but not least, the market and evolutions of the BMS (Building Management System) are strongly impacted by the Internet of Things.
As the graphic below indicates, building management systems are becoming the centers of connectivity in a world of ever more endpoints in buildings, data analytics and actionable data play a key role in the evolution of building design, the connected building and the building management. As data collection from end point increases and next generation technologies make analytics and insights key in building systems, the connected BMS becomes a center of visualization, insights and actions.
Leveraging data from IoT-enabled facility assets, along with new Internet of Things platforms and facility management, with embedded capabilities, are leading to possibilities and benefits in building management areas such as:
Smarter building security systems.
Smarter Heating, ventilation and air conditioning (HVAC).
Safer and more comfortable/healthy workplaces and buildings.
Facility service quality optimization.
Cost reductions, also in a green building context and in reduction of energy and water consumption.
Better planning, operational efficiencies and enhanced resource allocation.
Predictive maintenance and facility maintenance planning.
Facility equipment control, configuration and regulation.
Building management and building automation.
Light and room control, comfort.
This list is far from comprehensive. As there are various sorts of buildings, each with their own challenges, infrastructure, technologies and most of all goals the landscape of building automation and management is very broad. In light and room control alone there are several controls such as blind controls, AC unit controls and literally dozens more.
The overall building automation and management landscape exists since far before the Internet of Things existed and is composed of various specializations, each with their standards (e.g. KNX in room control or BACnet in building management systems), certification programs for green buildings (ecology and energy/ecology regulations are key drivers) and for OT channel partners, technologies, networks, solutions and of course goals (the goal of an IoT-enabled office space, building or even meeting room is not the same of a hospital, even if there are always overlaps) .
However, with the Internet of Things these worlds are converging (and the standards already evolved to IP). This is a challenge and opportunity for the various players who all have their skill sets but rarely are able to offer the full picture.
5. The Internet of Things in HEALTHCARE
The Internet of Things has been present in healthcare in many forms and shapes since several years.
With remote healthcare monitoring and medical/hospital asset tracking, monitoring and maintenance as typical examples of these initial applications, the face of the Internet of Things in healthcare is changing fast.
Among the evolutions and drivers of the Internet of Things in healthcare:
An increasing consciousness and engagement from the consumer/patient side leads to new models, leveraging personal healthcare devices.
In a more integrated perspective, data from biosensors, wearables and monitors are used in real-time health systems and to save time for caregivers, detect patterns, be more aware and increase quality of care.
A broad range of innovations in fields such as smart pills and ever better delivery robots help in making healthcare more efficient and in saving resources, while also increasing quality of care.
This glorifies the importance of remote monitoring as the main use case in healthcare from a spending perspective until 2020 and ongoing growth in the years after that with some vital sign monitor devices, followed by ways how healthcare providers and healthcare payers plan to leverage the Internet of Things and, finally smart healthcare market growth data.
Some evolutions and forecasts in healthcare IoT in numbers:
Research shows that by 2019, 89% of all healthcare organizations will have adopted IoT technology
Among the main perceived benefits of healthcare IoT in the future are increased workforce productivity (57%), cost saving (57%), the creation of new business models (36%) and better collaboration with colleagues and patients (27%). The key benefits as reported in March 2017, however, are increased innovation (80%), visibility across the organization (76%) and cost savings (73%).
Other research shows that wearables will play a key role in health care plans, clinical IoT device data will free up clinician’s time significantly by 2019 (up to 30%) and there will be an increasing role for IoT-enabled biosensors and robots for medication and supplies delivery in hospitals by 2019.
Internet of Things in UTILITIES AND ENERGY
Facing huge challenges and transformations for several reasons, utility firms have 299 million units installed according to Gartner. On top of utilities in the traditional sense there is also a lot happening in oil and gas and in energy.
Among the many typical use cases in utility firms: smart meters to improve efficiency in energy, from a household perspective (savings, better monitoring etc.) and a utility company perspective (billing, better processes and of course also dealing with natural resources in a more efficient way as they are not endless) and smart grids (which is about more than the Internet of Things).
The Internet of Things in AUTOMOTIVE
Connected cars and all the other evolutions in the automotive industry are driving the market as well. Again, connected vehicles is the hottest US market in the overall picture. The connected car is one of those typical examples where the Consumer Internet of Things and Industrial Internet of Things overlap.
The Internet of Things in OTHER SECTORS
Other industries include healthcare, transportation (where “smart devices” and sensors have existed for quite some time), logistics, agriculture and more. Add to that the consumer context and you know why it is such a hot topic.
In summary the biggest drivers for IoT projects are listed below
This is the last blog in the series on the World of IoT and the related space. Hope you all enjoyed reading through the posts as much as I enjoyed putting them together. Stay tuned while I come back with yet another series on a technology topic
Just a recap, in my previous post, I had emphasized primarily over the key definitions and approaches to the Internet of Things. In this post, we are going to take a deep dive into the growth and trends in the IoT space.
The exact predictions regarding the size and evolution of the Internet of Things landscape tend to focus on the number of devices, appliances and other ‘things’ that are connected and the staggering growth of this volume of IP-enabled IoT devices, as well as the data they generate, with mind-blowing numbers for many years to come.
It makes it look as if the Internet of Things is still nowhere. Make no mistake though: it is already bigger than many believe and used in far more applications than those which are typically mentioned in mainstream media.
At the same time it is true that the increase of connected devices is staggering and accelerating. As we wrote the first edition of this Internet of Things guide, approximately each single hour a million new connections were made and there were about 5 to 6 billion different items connected to the Internet. By 2020, Cisco expected there would be 20 billion devices in the Internet of Things. Estimations for 2030 went up to a whopping 50 billion devices and some predictions were even more bullish, stating that by 2025 there will be up to 100 billion devices. The truth is that we will have to wait and see and that by the time we have written about recent predictions, new ones are already published.
Regardless of the exact numbers, one thing is clear: there is a LOT that can still be connected and it’s safe to assume we’ll probably reach the lower numbers of connected devices (20-30 billion) by 2020. Moreover, it’s not that much the growth of connected devices which matters but how they are used in the broader context of the Internet of Things whereby the intersection of connected and IP-enabled devices, big data (analytics), people, processes and purposeful projects affect several industries.
Also the data aspect is critical (again with mind-blowing forecasts) and how all this (big) data is analyzed, leveraged and turned into actions or actionable intelligence that creates enhanced customer experience, increased productivity, better processes, societal improvements, innovative models and all possible other benefits and outcomes. The impact of the IoT from a sheer data volume and digital universe perspective is amazing. And the Internet of Things will surpass mobile phones as the largest category of connected devices with 16 billion connected devices being IoT devices
There are numerous reasons for the growing attention for the Internet of Things. While you will often will read about the decreasing costs of storage, processing and material or the third platform with the cloud, big data, smart (mobile) technologies/devices, etc. there certainly is also a societal/people dimension with a strong consumer element.
A factor that has also contributed a lot to the rise of the Internet of Things, certainly in a context of the industrial Internet of Things and smart buildings, to name a few, is the convergence of IT and OT (Operational Technology) whereby sensors, actuators and so forth remove the barriers between these traditionally disconnected worlds. Find the best rgb pc case and other gaming equipment on this website and have fun.
As companies increasingly started investing in Internet of Things technologies and scalable Internet of Things deployments instead of just pilot projects it quickly became clear that the Internet of Things as a term covered completely different realities which have little in common. The majority of the Internet of Things hype focused on consumer-oriented devices such as wearables or smart home gadgets. Yet, we can’t repeat it enough, there is a huge difference between a personal fitness tracker and the usage of IoT in industrial markets such as manufacturing where the IoT takes center stage in the vision of Industry 4.0 (you can for instance think about IoT-connected or IoT-enabled devices such as large industrial robots or IoT logistics systems). That’s why a distinction was made between the Industrial Internet of Things and the Consumer Internet of Things to begin with.
The Industrial Internet of Things (IIoT): is ‘machines, computers and people enabling intelligent industrial operations using advanced data analytics for transformational business outcomes”. The main value and applications are found in the so-called Industrial Internet of Things or IIoT. In all honesty one of the main reasons why we started talking about the Industrial Internet of Things is to distinguish it from the more popular view on the Internet of Things as it has becoming increasingly used in recent years: that of the consumer Internet of Things or consumer electronics applications such as wearables in a connected context or smart home applications.
Typical use cases of the Industrial Internet of Things include smart lightning and smart traffic solutions in smart cities, intelligent machine applications, industrial control applications, factory floor use cases, condition monitoring, use cases in agriculture, smart grid applications and oil refinery applications.
It’s important to know that the Industrial Internet of Things is not just about saving costs and optimizing efficiency though. Companies also have the possibility to realize important transformations and can find new opportunities thanks to IIoT.
Those who can overcome the challenges, understand the benefits beyond the obvious and are able to deal with the industrial data challenge have golden opportunities to be innovative, create competitive benefits and even entirely new business models
The Consumer Internet of Things (CIoT)
About 5 years ago, consumers rarely saw what the Internet of Things would mean to their private lives. Today, they increasingly do: not just because they are are interested in technology but mainly because a range of new applications and connected devices has hit the market.
These devices and their possibilities are getting major attention on virtually every news outlet and website that covers technology. Wearables and smart watches, connected and smart home applications (with Google’s Nest being a popular one but certainly not the first): there are ample of you know the examples.
Although it is said that there is some technology fatigue appearing, the combination of applications in a consumer context and of technology fascination undoubtedly plays a role in the growing attention for the Internet of Things. That consumer fascination aspect comes on top of all the real-life possibilities as they start getting implemented and the contextual and technological realities, making the Internet of Things one of those many pervasive technological umbrella terms. Obviously, the Consumer Internet of Things market is not just driven by new technology fascination: their manufacturers push the market heavily as adoption means news business possibilities with a key role for data.
Below are some consumer electronics challenges to tackle first:
Smarter devices. Consumers are waiting for smarter generations of wearables and Internet of Things products, which are able to fulfil more functions without being too dependent from smartphones, as is the case with many of such devices today (think the first generations of smartwatches, which need a smartphone).
Security. Consumers don’t trust the Internet of Things yet, further strengthened by breaches and the coverage of these breaches. Moreover, it’s not just about the security of the devices but also about, among others, the security of low data communication protocols (and Internet of Things operating systems). An example: home automation standard Zigbee was proven easy to crack in November 2016.
Data and privacy. On top of security concerns, there are also concerns regarding data usage and privacy. The lack of trust in regards with data, privacy and security was already an issue before these breaches as we cover in our overview of the consumer electronics market evolutions.
A “compelling reason to buy”. The current devices which are categorized as Consumer Internet of Things appliances are still relatively expensive, “dumb” and hard to use. They also often lack a unique benefit that makes consumers massively buy them.
Whereas the focus of the Industrial Internet of Things is more on the benefits of applications, the Consumer Internet of Things is more about new and immersive customer-centric experiences. As mentioned, the Consumer Internet of Things typically is about smart wearables and smart home appliances but also about smart televisions, drones for consumer applications and a broad range of gadgets with Internet of Things connectivity.
The Internet of Everything (IoE) : brings together people, process, data and things to make networked connections more relevant and valuable than ever before-turning information into actions that create new capabilities, richer experiences, and unprecedented economic opportunity for businesses, individuals, and countries.
It focuses too much on the things and, as mentioned, is also very broadly used. It’s why some started distinguishing between the just mentioned Consumer Internet of Things and the Industrial Internet of Things.
Cisco and other prefer to use the term Internet of Everything, partially because of that umbrella term issue, partially because of the focus on things and partially to provide context to their views and offerings. But it’s not just marketing. The Internet of Everything or IoE depicts crucial aspects of IoT, namely people, data, things and processes; in other words: what makes a business. It’s this mix that matters. Moreover, the classic illustration of the Internet of Everything also made clear what, for instance, machine to machine or M2M is all about.
We’ve based ourselves on that classic depiction and added the dimensions of value and data analysis.
The relevant four key drivers for IoE are listed below
The Internet of Robotic Things (IoRT): is a concept where intelligent devices can monitor events, fuse sensor data from a variety of sources, use local and distributed intelligence to determine a best course of action, and then act to control or manipulate objects the physical world, and in some cases while physically moving through that world
One of the major characteristics of the Internet of Things is that it enables to build far stronger bridges between physical and digital (cyber) worlds. You see it in all IoT use case and in the Industrial Internet of Things you see it in what’s called the Cyber Physical Systems.
Yet, in most case, the focus is predominantly on the ‘cyber’ part whereby data from sensors essentially are leveraged to achieve a particular outcome with human interference and with a focus on data analytics and ‘cyber’ platforms. The way it happens, as ABI Research, who came up with the IoRT concept (which is real today) puts it is that essentially many applications and business models are built upon passive interaction. The Internet of Robotic Things market is expected to be valued at USD 21.44 Billion by 2022
By adding robotics to the equation and turning devices (robots) in really intelligent devices with embedded monitoring capabilities, the ability to add sensor data from other sources, local and distributed intelligence and the fusion of data and intelligence in order to allow these devices determine actions to take and have them take these actions, within a pre-defined scope, you have a device that can control/manipulate objects in the physical world.
With collaborative industrial robots), warehouse automation (Amazon Robotics) and even personal robots for cleaning and so forth make it more tangible. It’s still early days for the IoRT but the projects and realizations in this next stage are real. IoRT is not tied to the consumer and industrial IoT distinction, it’s ever-present.
The Internet of Things is used in various industries for numerous use cases which are typical for these industries. On top of that, there is a long list of Internet of Things use cases that is de facto cross-industry. As the Internet of Things is embraced and deployed at different speeds throughout consumer and industrial sectors, we take a look at some of the main industries and use cases which drive the Internet of Things market and Internet of Things projects.
Patterns and shifts in the vertical industry and Internet of Things use case spend
Note that the biggest and/or fastest growing use cases are not always related to the biggest and/or fastest growing industries in terms of Internet of Things spending.
The costs and scope of the investments. A full-blown, enterprise-wide Internet of Things project in industrial settings such as manufacturing or logistics is far more expensive than a smart home implementation.
The shifts in the major Internet of Things use cases and industries. Remember that the Internet of Things mainly started as an industrial and business sector phenomenon. Industries with many existing physical assets can realize fast cost savings and efficiencies of scale. That’s why today they spend more in Internet of Things projects than consumer segments where we see more ‘new’ devices, rather than existing assets.
The Consumer Internet of Things catching up. As industries keep leading the current waves of Internet of Things spending until 2020, the fact that they started first and the advent of ever more consumer use cases and better (safer and more useful) solutions means that gradually consumer Internet of Things catches up with Industrial Internet of Things spending.
The rise of cross-industry Internet of Things applications and of scenarios whereby consumers and businesses meet each other in business-driven initiatives (for instance, the push for telematics in insurance, the push for smart meters in utilities) has a leveling effect on the adoption of the Internet of Things and on spending.
Stay tuned…. Part 4 of this foray, we will look into the 8 best example usages of the world of IoT.
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In this series of posts, I will emphasize primarily over the world of IoT (Internet of Things). We’ll start with looking at the origins of IoT, its common elements and approaches, look at the market growth and how it has changed the horizon for future tech devices, notably an sls printer. We will also touch base with the newer extensions of IoT like IIoT (Industrial IoT), CIoT (Consumer IoT), IoE (Internet of Everything) and IoRT (Internet of Robotic things).
IoT is an umbrella term for a broad range of underlying technologies and services depending upon the use cases and in turn are part of a broader technology ecosystem which includes related technologies such as AI, cloud computing, cyber security, analytics, big data, various connectivity/communication technologies, digital twin simulation, Augmented reality and virtual Reality, block chain and more.
The idea of the Internet of Things goes back quite some time. The RFID has been a key development towards the Internet of Things and the term Internet of Things has been coined in an RFID context (and NFC), whereby we used RFID to track items in various operations such as supply chain management and logistics.
The roots and origin of the Internet of Things go beyond just RFID. Think about machine-to-machine (M2M) networks. Or think about ATMs (automated teller machine or cash machines), which are connected to interbank networks, just as the point of sales terminals where you pay with your ATM cards. M2M solutions for ATMs have existed for a long time, just as RFID. These earlier forms of networks, connected devices and data are where the Internet of Things comes from. Yet, it’s not the Internet of Things.
The Role and Impact of RFID
In the nineties, technologies such as RFID, sensors and a few wireless innovations led to several applications in the connecting of devices and “things”. Most real-life implementations of RFID in those days happened in logistics like warehouses and the supply chain in general. However, there were many challenges and hurdles to overcome (mainly warehousing and industrial logistics as RFID was still expensive).
An example of an RFID application – electronic toll collection. The use of RFID became popular in areas beyond logistics and supply chain management: from public transport, identification (from pets to people), electronic toll collection (see image), access control and authentication, traffic monitoring, retail outdoor advertising. That growing usage was, among others, driven by the decreasing cost of RFID tags, increasing standardization and NFC(Near Field Communication).
Journey of RFID to IoT
The possibility of tagging, tracking, connecting and “reading” and analyzing data from objects would become known as the Internet of Things around the beginning of this Millennium.
It was obvious that the connection of the types of “things” and applications – as we saw them in RFID, NFCs – with the Internet would change a lot. It might surprise you but the concepts of connected refrigerators, telling you that you need to buy milk, the concept of what is now known as smart cities and the vision of an immersive shopping experience (without bar code scanning and leveraging smart real-time information obtained via connected devices and goods) go back since before the term Internet of Things even existed. Th attention for IoT in numerous other areas without a doubt has led to the grown attention for it as you’ll read further.
Coining of IoT Term
According to the large majority of sources, the term Internet of Things was coined in 1999 by Kevin Ashton at MIT.
RFID existed years before talked about the Internet of Things as a system, connecting the physical world and the Internet via omni-present sensors. Team there wanted to solve a challenge as wired reports: empty shelves for a specific product. When shelves are empty, obviously no one can buy what’s supposed to be there. It’s a typical problem of logistics and supply chain. The solution was found in RFID tags, which were still far too expensive to be able to put them on each product. Once the benefit was realized, there were many who invested in the expensive RFIDs to derive the benefits. The rest is a standard system, solving miniaturization challenges, lowering RFID tags prices and…history.
Definition of IoT
The internet of things, or IoT, is a system of interrelated computing devices, mechanical and digital machines, objects, animals or people that are provided with unique identifiers (UIDs) and the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction.
Physical devices are either designed for the Internet of Things or are assets, including living beings, which are equiped with data sensing and transmitting electronics. Beyond this endpoint dimension with devices, sensors, actuators and communication systems, the Internet of Things is also used to describe what is effectively done with the data acquired from connected things.
The Internet of Things describes a range of applications, protocols, standards, architectures and data acquisition and analysis technologies whereby devices and items (appliances, clothes, animals,….) which are equipped with sensors, specifically designed software and /or other digital and electronical systems, are connected to the Internet and/or other networks via a unique IP address or URI, with a societal, industrial, business and/or human purpose in mind. As you can read below, data and how they are acquired, analyzed and combined into information value chains and benefits are key in it. In fact, the true value of the IoT connectivity lies in the ways it enables to leverage entirely new sources and types of data for entirely new business models, insights, forms of engagement, and ways of living and societal improvements
The Internet of Things is not a thing. Data which is acquired, submitted, processed or sent to devices, in most cases travels across the Internet, fixed lines, across cloud ecosystems or via (tailored) wireless connectivity technologies which are developed for specific applications of IoT
Bridging digital, physical and human spheres through networks, connected processes and data, turned into knowledge and action, is an essential aspect in this equation. In recent years the focus in the Internet of Things has shifted from the pure aspect of connecting devices and gathering data to this interconnection of devices, data, business goals, people and processes, certainly in IIoT.
Elements of IoT
Most IoT definitions have several aspects in common. Here are the elements they have in common:
Internet of Things Connectivity
All IoT definitions include the connectivity and network aspect: a network of things, devices, sensors, objects and/or assets, depending on the source. It’s pretty clear that a dimension of networks and connectedness, we would even say hyper-connectedness, needs to be present in any decent IoT definition.
2. The Things in the Internet of Things
IoT-enabled assets, devices, physical objects, sensors, anything connected to the physical world, appliances, endpoints, the list goes on. They are all terms to describe what an essential part of a network of things. Some add words such as smart or intelligent to the devices. Let’s say that they contain technology that grants them an additional capability of ‘doing something’: measuring temperature or moisture levels, capturing location data, sensing movement or capturing any other form of action and context that can be captured and turned into data.
3. The Internet of Things and Data
This is part of that intelligent notion but it also brings us far closer to the essence. You can define the Internet of Things by simply describing all characteristics (“what it is”) but you also need to look at its purpose (“the why”).
4. Communication in the Internet of Things
Data as such is maybe not without value but it sure is without meaning unless it is used for a purpose and it is turned into meaning, insights, intelligence and actions. The data gathered and sensed by IoT devices needs to be communicated in order to even start turning it into actionable information, let alone knowledge, insights, wisdom or actions.
5. Internet of Things, Intelligence and action
We just touched upon this aspect. However, in most definitions we see that intelligence is attributed to just the network(s) and/or the devices. While we certainly need, for instance, ‘intelligent networking technologies’ in many cases and while connected devices have a capacity of action, the real intelligence and action sits in the analysis of the data and the smart usage of this data to solve a challenge, create a competitive benefit, automate a process, improve something, whatever possible action our IoT solution wants to tackle.
There is always a degree of automation, no matter the scope of the project or the type of Internet of Things application. This automation, irrespective of the system it is applied on, always comes concomitant with a smtp provider, considering the vulnerability of the system. Most IoT applications are essentially all about automation. And that often comes with costs and benefits. Industrial automation, business process automation or the automatic updating of software: it all plays a role, depending on the context.
Meaning and hyper-connectedness is what we miss in many answers on the questions regarding what the Internet of Things is. We stay too descriptive and focused on just the technologies and don’t look at purpose and intelligent action enough
While the above mentioned elements come back in all Internet of Things definitions there are a few we miss that are essential in the evolving views regarding the Internet of Things as it moves from devices and data to outcomes and actionable intelligence, and ultimately to a hyper-connected world of digital transformation (DX) and business.
The aspect of hyper-connectivity and integration often lacks. In a context of a reality whereby devices, people, processes and information are more interconnected than ever before; an Internet of Things definition and approach just needs to mention these aspects as the Internet of Things is part of something broader and is more about data, meaning and purpose than about objects. A key element of that hyper-connectivity in the Internet of Things sphere is that sometimes mentioned ongoing bridging of digital and physical environments, along with human environments, processes and data as the glue, enabler and condition to create value when properly used for connected purposes.
Then there is also the possibility to create new ecosystems where connected device usage by groups of people can lead to new applications and forms of community ecosystems. Last but not least and we’ve mentioned this often before: no Internet of Things without security.
Stay tuned…. Part 2 of this foray, we will look into key definitions and approaches for IoT.
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Just a recap, we learnt in my last update, the different ways to harness the new age machine to enhance market competitiveness of your products and services. In this excerpt we are going to dwell upon the different ways to harness the new age machine in by and large the innovation quotient that we need to invest upon.
As we have seen throughout this series of posts, the innovation related to the intelligent systems and digital economy is both a catalyst for and an outcome that will allow your organization to discover opportunities that were never before visible or addressable. Innovation being the center stone, it can’t be a side project which is nice-to-have but its central to remaining relevant in the great digital build-out that we are experiencing and of course lies ahead of us. While machines will do more and more of our work, the process of innovation will allow us to discover entirely new things to do that are impossible to imagine and hard to predict but they will be at the core of what we do in the future.
Today, https://www.themebounce.com reports that a new economy is emerging with a flurry of job categories that even a few years ago would have been hard to predict; social medial consultants, search engine optimizers, full stack engineers, content curators, and chief happiness officers. These all jobs that the tech economy’s equivalent to the Charles Babbages of the early starters would have imagined. AI is changing our world already, but in reality we have only begun to scratch the surface of where it will take us over the next 20, 50, 100 years. Your job is to imagine the new forms of value you can create with the new machines of the new revolution. Institutionalizing the role and importance of being open to the fruits of innovation is a hugely important role that you as a leader of the future need to play. The openness to innovation is not just a job of the company’s formal R&D department. It has to be a culture of innovation that each and every one of you should exhibit.
We have learned right through this series that the new machine will be your platform of innovation. Once you are instrumenting, automating, tracking and analyzing the core operations of your business an applying machine learning, innovation opportunities will be consistently unearthed. Innovation is thus a rich term with many different attributes and applications. It can be applied to many areas including some I have listed below.
With product innovation, team will gain continual insight as to how your products are being used, also what customer frustrations points exist, and where the obvious areas for improvement exist. These inputs definitely can’t be gauged without a thorough AI system in place. Once you have automated, instrumented and enhanced your company’s activities, the associated AI engines can be applied to innovation. The team will get greatly enhanced by the application of the new machine, primarily because it radically accelerates the scale and speed of the innovation process. As such, when the new machine is soon widely adopted, the rate of human progress in the 21st century (as defined by the cumulative growth of human knowledge and he pace of the innovation) will be at least 1000 times the average rate of the 20th century. Obviously the general factors affecting innovation in the organization (opinions, ideas, emotions, organization’s inertia etc) can bring down above prediction to may be by two orders of magnitude. Still the innovation quotient of 10 times is way higher than traditional R&D ways.
One of the core principle in these posts is that machines can do many things but that practical application should be focused on specific business processes and customer experiences. When you are making discovery investments, start at the process and experience level and imagine how the process can be restructured and reinvented with digital.
Discovery can be a risk. Invest too much in the wrong ideas and you go broke. Wait for somebody else to do it and you can miss the market opportunity of a lifetime. So what’s the best practice for bringing about this new form of innovation? We find too many managers looking for the new “the next great breakthrough” but that doesn’t work. The opposite approach is to ask how the new machine adds the most value – that is, by looking for continuous, incremental improvements or looking to hit singles on a consistent basis. This primarily caters to “change for better” but is implemented as small, continuous improvements that in time have a large impact. Your goal should be to become a Know-It-All business via instrumentation, sensors, big data and analytics. In the real world, organizations should establish a portfolio of initiatives focused on discovery, with a clear life cycle methodology that manages these initiates from inception through o ultimate success or failure. Central to their generative acts will be the belief that something better can be created. The true core of discovery is, after all, hope.
Obviously, please don’t forget that with the Gods come the devils as well. While most part of my posts are ushering in that AI is an age of miracles and wonder of technological marvels but in the hindsight we should also see a world of robots, more powerful human like machines taking over. Thus strike a balance.
In these posts, we have argued that the information technology innovations and investments of the past 4 decades are merely a precursor to the next waves of digitization, which will have truly revolutionary impacts on every aspect of work, society, and life.
As the last S-Curve’s growth rate continues its inexorable journey south, the new S-curve is gather momentum, and so are the companies poised to lead this new charge. These are the companies that have learned how to master the 3 Ms, how to align the new raw materials of the digital age (data), the new machines (intelligent systems), and the new models (business models that optimize the monetization of data-based personalization).These are the companies that understand how to build and operate a know-it-all-business, that understand that intelligent machines aren’t to be feared but embraced and harnessed, and that are energized by the unwritten future rather than just trying to hang onto the glories of the past.
Below are the few mandatory steps that any organization should embark upon and leaders from organizations should help them implement.
The companies that are getting ahead are the ones acting on these ideas. Some companies we work with emphasizes one ‘play’ over another, while others recognize the holistic connection between all of the plays, automation enables enhancement, discovery uncovers how to achieve excessiveness, and so on. All of them, however, understand the need to act now, to not wait for more certain times ahead, more clarity over exactly what AI is, and what it will become. All of them recognize that the rise of the machine intelligence is the ultimate game changer we face today. All of them know that inaction will result in irrelevance. All of them know that fortune favors the brave and punishes the timid.
This is the last blog in the series on AI/ML and the related space. Hope you all enjoyed reading through the posts. Stay tuned while I come back with yet another series on a technology topic.
Please feel free to review my other series of posts