Why the Internet of Things (IoT) is about Data Driven Ecosystems (& not really about the Devices)..

The Internet of Things (IoT) will have a great impact on the economy by transforming many enterprises into digital business and facilitating new business models, improving efficiency, and generating new forms of revenue.However, the ways in which enterprises can actualize any benefits will be diverse and, in some cases, painful” – Jim Tully, vice president and distinguished analyst at Gartner – 2015.

The IoT is one of the most hyped paradigms floating around at the moment. However the hype is not all unjustified. Analyst projections have about 25 billion devices connected to the internet by 2020 delivering cumulative business value of $2 trillion[1] across many industry verticals. Enterprise IT need to now begin developing capabilities to harness this information to serve their end customers. This blogpost discusses foundational IoT business elements that are common across industries.

                                                         Image Credit – ThinkStock

The Immense Market Opportunity around IoT 

The IoT has rapidly become one of the most familiar — and perhaps, most hyped — expressions across business and technology. That hype, however, is entirely justified and is backed up by the numbers as one can glean from the below graphic. The estimated business value of this still nascent market is expected to be around $10 trillion plus by 2022.

                                                         Credit – Tamara Franklin (Oracle Research)

Thinking around IoT has long been dominated by passive devices such as Industrial Sensors, RFID tags and Actuators. As pointed out in my “Gartner’s Trends for 2017” article, these devices are beginning to form a smart mesh. Field devices now have increased ‘smart’ capabilities to communicate with each other and with the internet – typically using an IP protocol -resulting in the combined intelligence of groups of such ‘things’.  The IoT now enables not just machine to machine communication but also the human to machine and human to IoT ecosystems. While the media plays up stories of IoT aware devices such as Google Nest or Amazon Echo etc – it is also shaking up vertical industries.

Virtually every industry out there has a significant amount of connected devices that have been deployed. This includes Retail, Energy & Utilities, Manufacturing, Healthcare, Transportation and Financial services etc.  Having said that, let us consider the five key industrial uses for the IoT space that will yield tremendous business value over the short to medium term – the next 2-5 years.

The Six Key Industry Applications of IoT 

Consider the above graphic (courtesy the BCG), the real business value in IoT lies in Analytics and Applications built on these analytics. In fact, BCG expects that by 2020 these higher order layers will have captured 60% of the growth from the [3]. In such a scenario, the rest of the technology elements – connected things, cloud platforms & data architectures merely enable the upper two layers in delivering business value.

Let us then consider the key industrial use cases for IoT –
  1. Retailers implementing IoT are working to ensure that their customers gain a seamless experience while browsing products in the store.For example the industry has begun adopting smart shelves that restock themselves, installed beacons in stores that communicate with shopping apps on consumers smartphones and NFC (Near Field Communications) that enable customers to make contact-less payments.  Internal operations such as Supply Chains are benefiting in a big way in their ability to gain realtime insight into the
  2. In the area of Commercial real estate, facilities management is an area where companies spend massive amounts of money on energy consumption. According to Deon Newman, at IBM Watson[3], global conglomerates like Siemens own hundreds of thousands of building which produce tens of thousands of millions of emissions. In this case, IoT analytics is being leveraged to reduce such huge carbon footprint.
  3. In the Utilities Industry – as Smart Meters have proliferated in the industry, IoT is driving use-cases ranging from Predictive Maintenance of equipment to optimizing Grid usage. For instance, in water utilities, smart sensors track everything from quality to pressure to usage patterns. Utilities are creating software platforms that provide analytics on usage patterns and forecast demand spikes in the grid .
  4. The Manufacturing industry is moving to an entirely virtual world across its lifecycle, ranging from product development, customer demand monitoring to production to inventory management. This trend is being termed as Industry 4.0 or Connected Manufacturing. As devices & systems become more interactive and intelligent, the data they send out can be used to optimize the lifecycle across the value chain thus driving higher utilization of plant capacity and improved operational efficiencies.
  5. The biggest trend in the Transportation industry is undoubtedly self driving connected cars & buses. The Connected Vehicle concept enables a car or a truck to behave as a giant smart app – sending out data and receiving inputs to optimize it’s functions. With the passing of every year, car makers are adding more and more smart features. Thus, vehicles have more automatic features builtin – ranging from navigation, requesting roadside assistance, self parking etc etc. Applications are being built which will enable these devices to be tracked on the digital mesh thus enabling easy inter vehicle communication to enable traffic management, pollution reduction and public safety.
  6. With Smart Cities governments across the globe are increasingly focused on traffic management, pollution management, public services etc – all with a view to improving quality of life for their citizens.  All of these ecosystems will be adopting IoT technology in the days and years to come.

Conclusion..

It can be seen from the above that the applications are myriad. Thus, while one cannot recommend a generic IT approach to IoT thats applicable to every industry – familiar themes do emerge that apply from a core IT capability standpoint.

The next post will consider the five key & common technology capabilities that Enterprise CIOs need to ensure that their organizations begin to develop to win in the IoT era.

References

[1] Gartner July 2015 – “The Internet of Things is a Revolution waiting to happen” – http://www.gartner.com/smarterwithgartner/the-internet-of-things-is-a-revolution-waiting-to-happen/

[2] BCG Analysis – “Winning in the IoT is about business processes” – https://www.bcgperspectives.com/content/articles/hardware-software-energy-environment-winning-in-iot-all-about-winning-processes/

[3] “Cognitive Computing and the future of smart buildings” – Deon Newman, IBM Watson IoT

https://www.ibm.com/blogs/internet-of-things/cognitive-computing-future-smart-buildings/

Across Industries, Big Data Is Now the Engine of Digital Innovation..

The data fabric is the next middleware.” –Todd Papaioannou, CTO at Splunk

Enterprises across the globe are confronting the need to create a Digital Strategy. While the term itself may seen intimidating to some, it essentially represents  an agile culture built on customer centricity & responsiveness. The only way to attain Digital success is to understand your customers at a micro level while making strategic decisions on your offerings to the market. Big Data has become the catalyst in this massive disruption as it can help business in any vertical solve their need to understand their customers better. It aids this by providing foundational  platform for amazing products.

We have seen how how exploding data generation across the global has become a clear & present business & IT phenomenon. Data volumes are rapidly expanding across industries. However, while the production of data itself that has increased but it is also driving the need for organizations to derive business value from it. This calls for the collection & curation of data from dynamic,  and highly distributed sources such as consumer transactions, B2B interactions, machines such as ATM’s & geo location devices, click streams, social media feeds, server & application log files and multimedia content such as videos etc. It needs to be noted that data volumes here consist of multi-varied formats, differing schemas, transport protocols and velocities.

Internet of Things (IoT) has become an entire phenomenon to itself. It is truly a horizontal vertical (no pun intended) as the proliferation of applications of sensors is causing rapid change in system & application architectures. The system of IoT is burgeoning from the initial sensors, digital devices, mechanical automatons to cars, process monitoring systems, browsers, television, traffic cameras etc etc.

Big Data is thus crossing the innovation chasm. A vast majority of early adopter projects are finding business success with a strong gain in ROI (Return On Investment). The skills gap is beginning to slowly decrease with Hadoop ecosystem becoming a skill that every modern application developer needs to have. Increasingly customers are leading the way by deploying Big Data in new and previously uncharted areas like cybersecurity leading to massive cross vertical interest.

DT_Vectors

The five elements in Digital Transformation, irrespective of the business vertical you operate in, are –

  1. Customer Centricity
  2. Realtime multichannel analytics
  3. Operational improvements – Risk, Fraud & Compliance
  4. Ability of the business to visualize data
  5. Marketing & Campaign optimization

The first element in Digital is the Customer centricity.

Big Data drives this in myriad ways  –  

  1. Obtaining a realtime Single View of an entity (typically a customer across multiple channels, product silos & geographies)
  2. Customer Segmentation by helping businesses understand their customers down to the individual level as well as at a segment level
  3. Customer sentiment analysis by combining internal organizational data, clickstream data, sentiment analysis with structured sales history to provide a clear view into consumer behavior.
  4. Product Recommendation engines which provide compelling personal product recommendations by mining realtime consumer sentiment, product affinity information with historical data.
  5. Market Basket Analysis, observing consumer purchase history and enriching this data with social media, web activity, and community sentiment regarding past purchase and future buying trends.

Realtime Multichannel Analytics is the second piece of a Digital Strategy.

Mobile applications first begun forcing the need for enterprise to begin supporting multiple channels of interaction with their consumers. For example Banking now requires an ability to engage consumers in a seamless experience across an average of four to five channels – Mobile, eBanking, Call Center, Kiosk etc. The healthcare industry stores patient data across multiple silos – ADT (Admit Discharge Transfer) systems, medication systems, CRM systems etc but all of this must be exposed across different mediums of access. Data Lakes provide an ability to visualize all of the patients data in one place thus improving outcomes. Every customer facing application needs to be both multi-channel as well as one that supports  a unified 360 degree customer view across all these engagement points. Applications developed in 2016 and beyond must take a 360 degree based approach to ensuring a continuous client experience across the spectrum of endpoints and the platforms that span them from a Data Visualization standpoint. Every serious business needs to provide a unified view of a customer across tens of product lines and geographies. Big Data not only provides the core foundational elements for a realtime view of the moving parts of the business but also enables businesses to listen to their customers.

A strategic approach to improving Risk, Fraud & Compliance analytics  can add massive value and competitive differentiation in three distinct categories as shown below.

  1. Exponentially improve existing business processes. e.. Risk data aggregation and measurement, HIPAA/SOX/Manufacturing compliance, fraud detection
  2. Help create new business models and go to market strategies – by monetizing multiple data sources – both internal and external
  3. Vastly improve regulatory compliance by generating fresher and more accurate insights across silos of proprietary data

The onset of Digital Architectures in enterprise businesses implies the ability to drive continuous online interactions with global consumers/customers/clients or patients. The goal is not just provide engaging Visualization but also to personalize services clients care about across multiple modes of interaction. Mobile applications first begun forcing the need for enterprise to begin supporting multiple channels of interaction with their consumers. For example Banking now requires an ability to engage consumers in a seamless experience across an average of four to five channels – Mobile, eBanking, Call Center, Kiosk etc. Healthcare is a close second where caregivers expect patient, medication & disease data at their fingertips with a few finger swipes on an iPad app.

The ability of outbound Marketing campaigns to reach engaged customers in a proactive manner using the right channel has been a big gap in their effectiveness. The old school strategy of blasting out direct mailers and emails does not work anymore both from a cost as well as a customer engagement standpoint. Nowadays, campaigns for exciting new products & promotions need to be built on the rich customer intelligence assets that Big Data enables you to build. Examples of these capabilities are replete in sectors like Retail where offering a positive purchase experience in terms of personalized offers, price comparisons, social network based sharing of experiences et al drive higher customer engagement & loyalty.

The Final Word

My goal for this post was to communicate a business revelation that I have had in past year. While the semantics of business processes, the usecases & the data sources, elements, formats may vary from industry to industry ( e.g. Banking to Healthcare to Manufacturing to Telecom) – the approaches as well as the benefits from leveraging a data & analytics driven business model essentially remain the same. These capabilities are beginning to separate the winners from the rest of the pack.