IoT Decision Framework: Factors & Challenges

IoT Decision Framework: Factors & Challenges

Internet of Things(IoT) – A new revolution that is going to be the core backbone of business in the years to come. Industry is getting ready to adopt this massive change that is likely to hit it sooner than later. As per a recent survey[1]  96% of the senior business leaders have plan to use IoT in next 3 years. Among the ones who have adopted – 94% already have started to realize their return on investment. IoT has potential to create additional 10-15 trillion$ economy. Virtually every vertical will have an impact due to this massive change in technology.

Important factors to consider IoT Decision Framework

Inflection point in this technology adoption can be attributed to a few important IoT Decision Framework factors. These are:

Revolution in Sensor technology

Availability of new sensors virtually able to sense every possible core attribute that is significant,  miniaturization of sensors, and continuous dropping cost of sensors

Revolution in Connectivity

Wireless connectivity has gone through five generations of revolution in about two and a half decades. 4G networks offer very high data bandwidth and fully deployed in most of the geographies. 5G trials are already in advanced stage. Installation of  production ready network may happen anytime in next 2-3 years. 5G network will offer multiple advantages – 10x higher bandwidth compared to 4G, Ultra low latency, better connection and network availability etc are some of the advantages that are likely to give significant boost to IoT adoption[2]

Massive deployment of Cloud enabled services

Cloud enabled services have picked up massively in last decade or so. Cloud offers multiple advantages over the in-house, standalone data centers.  Higher availability, Rapid scalability, Faster Service deployments, Multi-tenancy etc are some of them.  Now, cloud platform and services are coming up in many flavors based on the specific need of the business. Massive services are being offered by the cloud platform players. All Key players – Amazon(AWS), Micorsoft( Azure), Google( Google Cloud) and a lot of others have started offering full stack services for rapid development on their cloud.

Advancement in Machine Learning, Deep Learning and Artificial Intelligence

The real benefit of IoT is realized when things become smarter and smarter. They are able to learn by themselves, they are able to talk to each other, they are able to negotiate with each other, and able to run the applications best suited for maximized outcomes with minimal human interaction and minimal disruption. New advancement in technologies like Machine Learning, Deep Learning, Natural Language Processing and Artificial Intelligence open the path exactly in that direction. With these technologies, new usecases are getting created everyday and a lot of businesses are taking advantage of the intelligence being created.

IoTfying Your Business – What exactly it means

There are lot of manual intervention in day-to-day business processes.  Each of these manual intervention has its own incremental cost involved with it. Labor cost of executing these processes, process waiting time loss cost – cost involved related to wait time for other dependent process for every manual process. Quality control cost – there are chances of error in manual execution and with every error caused, the cost for rectification of such error could be huge. Sometimes beyond monetary, resulting into business reputation or loss of business.

IoTfying is actually about identifying all potential possibilities of extreme automation, applying state of the art Industry best practices for automation which will result in significant improvements in revenue generation, cost efficiencies and predictable & improved quality.  IoTfying will improve business to evolve new innovative business models, new ways to engage and serve customers and collaborating with suppliers and partners.

How to approach IoTfying your business

Locate relevant examples already implemented

Every industry sector is going through business and technology innovation cycle. Example case studies are already available in almost all verticals which have applied IoT technology in their business and have benefits to showcase. Be it Manufacturing, Services Industry, Travel Industry, Retail, Energy & Utilities, Infrastructure services management, Automotive industry or any other sector. We can find a lot of case studies which would be relevant to your business.

Identify your primary business drivers for the change

Business has to identify and articulate core objectives for implementing the change. For some it may be tapping additional market opportunity for revenue generation, for some it may be achieving cost efficiencies/productivity and eliminate waste, for some it could be better customer engagements, customer insights, for others identifying opportunity to up-sell/cross sell to the existing customers.

Articulate/Re-articulate long term vision

IoT is here to stay. The technology will offer potential to reap the benefits on continuous basis. New innovations will continue to hit the market. It is important to spend senior management time and articulate long term vision for the business. This long term vision will help in further steps like data collection, IT architecture, product development & evolution and selecting the basic tools and elements of the solution.

Conceptualizing the solution

Now it is time to get into solution element. The solution may be an evolving solution with few phases of implementation based on specific need. Solution would include things/objects/machineries to be monitored and controlled, essential data elements,  hardware product concept identification, new user interfaces, new industry interfaces, platform architecture, cloud services specification, mobile application specification etc. Even though there are quick & ready made industry solutions already available in tons, it is important that the solution is designed & customized to your specific needs. A sample decision framework that could help conceptualizing the solution is depicted below: [3]

Develop Pilot

Before you go for full scale implementation, it is important run a few iteration of pilot to touch critical touch-points of your business and assess the impact of IIoT. Is user experience of your solution as per articulated vision ? What are the challenges in collecting data, Is hardware product meeting the requirements and fitting well with your business processes ? Any challenges in data acquisition, data processing, data storing or analyzing ?  What is the feedback of end users and other stakeholders ?  So many such questions needs to be answered during pilot development stage.

Implement the solution

Now it is time to implement the solution. The integrated solution would typically involve multiple discrete and distributed technology solutions. e.g. the product hardware, product embedded software solution,  edge computing & device gateway, data acquisition and ingesting components are the back-end, cloud computing services, data storage services, security and authentication services, Mobile application etc.  There are several industry grade platforms that are providing standard and customized solutions. It is wise to choose among one of these platform based solution which is best suited for your business.  Agile/DevOps based approach would help in quick roll-out of solution and reducing deployment nightmares.

Maintain & Support the solution

As mentioned above, IoT solutions are constantly evolving. New upgrades, new features have to be rolled out on regular basis to customize the solution as per market needs.

Challenges in IoTfying

IoTfying is not an easy task. The implementation journey for your businesses goes through  multiple challenges. It is important to be educated about these challenges well in advance and identifying the right mitigation steps to overcome these challenges. These are

Security and Data Governance related

Wireless connections, open apis, security vulnerabilities around connection and configuration, less-educated and limited aware end users,  massive liability & legal implications makes companies concerned about security and data governance issues.

In order to face this challenge, it is important to review the security of end-to-end solution at multiple levels and strengthen current IT infrastructures. Also carefully select new hardware and software partners by analyzing their security profiles etc.

IT & Business partnership related

IoT solutions is all about collaborating and partnerships. A solution may involve multiple disjoint partners which could lead to partnerships that are not natural relationships. Haziness about the partnership terms, partnership rights and constraints could be another challenge to discuss and sort out.

Data and Analytics complexity

Data and Analytics solutions have to be designed very carefully. It is experienced a lot of implementations are collecting vast amount of data and sensors are just sending the data directly to cloud. Collecting   vast amount of unnecessary data and transferring every bit to cloud is likely to impose massive challenges like bandwidth requirements, optimized usage of battery power, latency issues for critical applications, data storage, and legal issues around data ownership.  Designing the solution should be based on the principles of collecting minimum needed set of data, and should also make use of available edge computing/fog computing capabilities so that lot of analysis can be done locally.

Lack of Standards

Absence of available standards/ presence of multiple standards at every level is likely to pose huge challenges going forward. IoT is not able standalone devices or standalone organization. The devices will be required to talk to other devices & things.  These devices may follow completely different standard. This will pose integration challenges for inter-working of devices.

Highly fragmented market of niche solution

IoT devices have widely varying requirements of power, data processing, form factor, and other factors. Some of these devices are expected to run on battery power for months or years together without any need to replace battery. Some solutions may be ok with low bandwidth requirements whereas others may need very high bandwidth. IoT solution for industry devices may require direct connection to power supply and may have very high bandwidth requirements. On the software side, there are plethora of software solutions offering niche services. Integrating all these solutions sometimes becomes very challenging

Realizing the value (RoI)

As the technology and its business implementation is still evolving, a lot of times it becomes challenging to articulate clear use cases and quantitative analysis of return on investments. Vague value statements and unrealistic expectation of RoI may lead to management frustration and abandoning half baked solution. It is important to build proof of concepts to test the waters with well thought of business cases that are customer centric and not technology centric.

In summary, IoT is leading industry towards a amazing, highly productive state of the art business solutions – Solutions with potential to offer path breaking benefits and flip the business model upside down. The need is to rightly approach the solution across whole cycle from strategies, conceptualizing, implementing and maintaining.

[1]     http://www.em-visual.com/2015/06/servicemax-internet-of-things-infographic/

[2]     https://5g.co.uk/guides/5g-and-the-connected-car/

[3]     http://techproductmanagement.com/iot-decision-framework/

This article was written by Anil Gupta, the Founder of Magnos Technologies.