The Journey to Managed Enterprise IoT – Part 3 – Beyond the use case

<This blog was previously published at the Atos Thought Leadership website – it was written by Philip Griffiths>

In the 1st blog in the series, an overview was shared of the journey to managed enterprise IoT, which we divide into three levels of maturity. In my second post you will learn more about the first level: Enabling the use case.

Once you have determined the IoT use case you need to ensure that the solution is secure, accurate and predictable – i.e. it delivers sustainable value – in the face of increasing quality of devices, edges, continuous data flows, and technologies. This is enabled through ‘non-functional requirements’ (NFRs) and spans both execution qualities and evolution qualities. This is going ‘beyond the use case’.

By focusing on ‘how’ the use case is delivered, instead of ‘what’, you can realize the following benefits:

  • Quality: If your products and services cannot extract value, the data, and opportunities, it is lost.
  • Risk: Complex IoT use cases can put business continuity at risk; reduce it through strong NFRs.
  • Productivity: A use case has little value if it stops working after 6 months or in peak load periods.
  • Future-proofing: Your system should be built for low cost and simple improvements / evolution.

Realizing this require you to define, discuss, document, and design your NFRs as you enable the use case and beyond it. Extending the timeline from the previous post, the following activities take around 12-24 months:

  1. Project: Design solution, install and implement IoT solution from core to edge, integrate into your existing business systems as well as ensure system security – including building ecosystem of partners.
  2. Business Platform: Scale-up and industrialize the use case to a full platform, do further roll-outs, integrate into your existing business and enhance parts of the system to delivery sustainable value.

Below is a non-exhaustive list of topics and example questions to be considered for NFRs:

NFR Topic Example Questions
Execution Availability Does your E2E use case need an operational uptime of 99.99% or 95%?
Continuity What are you E2E RTO/RPO? What are the business impact / cost of your use cases being down for 1 or 60 minutes? How does this impact backup or disaster recovery? How do you enable HA, backup or disaster recovery in a distributed architecture?
Manageability How will you update millions of devices? When and how to push new functionality? How to handle a million+ devices all calling home sick? Will you have 24×7 operations?
Interoperability  How will data be handled across different silos? Do your platforms work together?
Performance How quickly do you need to access the data? Does it need to be processed at edge?
Resilience How will the system do backups and ensure service continuity? How will you ensure high uptime of distributed architecture? How will errors be handled ‘gracefully’?
Security How will data from connected objects be trusted? How will you ensure security in new and high risk environments? How will you reduce attack surface? How will you ensure internal and external compliance, auditability as well as alignment to standards?
Usability How will you reduce the head count of managing such E2E complexity? How will you optimize latency issues to improve real-time outcomes and / or use experience?
Evolution Maintainability How will defects be corrected? Will the system and components have self-healing? How will uptime be ensured without sending people / parts onsite?
Modularity Will your system be built on principles of separate independent functionality?
Scalability Will it scale up/down to meet peak demands?

 By focusing on ‘how’ you enable value from and not just ‘what’ the use case is you will derive much greater long term value for your business. To do this, you need to define, discuss, document and design them into the use case from the start. If you are not already doing this I suggest you look at facilitating it as soon as possible.

I have spoken to many clients who have rolled out IoT solutions which are ‘the future of the businesses’. It is therefore unfortunate when they stop working effectively or if the operations team only know of problems when they are informed by the customer. It is normally at this point that they ask for expertise on going ‘beyond the use case’.  A few common outcomes are re-building the app, creating a new platform, facilitating rapid scalability or enabling an operations team with E2E monitoring; either way, it costs time and money that were not predicted in the business case.

The journey to managed enterprise IoT – Part 2 – Enabling the use case

<This blog was previously published at the Atos Thought Leadership website – it was written by Philip Griffiths>

In my previous blog, I shared our overview of the journey to managed enterprise IoT, which we divide into three levels of maturity. Here I’ll explain the first level: Enabling the use case. For each company to transform data – the world’s most valuable resource – into business outcomes, they first need to work out how data and IoT will improve the business. This could be by enhancing customer experience and improving your internal organization. Once the strategy is picked, a use case can be developed and tested with speed and agility to measure the outcome and validate its value. This is ‘enabling the use case’.

By taking advantage of data, companies can deliver a multitude of benefits by delivering IoT projects. Examples include:

  • Customer Experience: Using data to understand market demands, behavior and buying trends and develop new products and services your customer’s will love to use
  • Business Reinvention: Market agility with new business models, products, services and revenue streams
  • Operational excellence: Gain efficiency and agility with data-driven business processes
  • Trust & Compliance: Unleash the power of analytics to protect your assets

To realize these benefits, 3 key activities need to be developed:

  1. Strategy & Ideation(S&I): Explore market changes, customer needs, business problems, opportunities and available data to select IoT use cases that enable data insights and sustainable business value. This includes identifying the business processes, any applicable standards and users.
  2. Proof of Value (PoV): Execute rapid prototyping to test and prove that the use case delivers value – the best approach is a limited scope and time frame. If it holds value, you should also develop a high level architecture for the future.
  3. Business Case (BC): Define the BC for the next steps – including investment costs and a genuine ROI – and business model that will be used while actively looking ‘beyond the use case’ – see next blog piece.

Across each of these topics, agility and an exploratory nature are critical. We expect the use case enablement to take anywhere between 2-4 months from the initial workshop, detailed study and developing PoV with BC – if it is then rolled out as a project this could take another 6-12 months. There should be a few deliverables (non-exhaustive list):

  • Strategy & Ideation: Data strategy, process scoping, value assessment, connectivity definition, high level plan for PoV and BC, management presentation.
  • Proof of Value: Requirements, built and tested PoV with results, use case feasibility report, project solution architecture, management presentation.
  • Business Case: Strategy map, benefits profile (with KPIs), project costing, business case, investment performance analysis, project plan, management presentation.

The first step in getting more value from your business data is to brainstorm and assess the IoT opportunities that could enable real business benefits. In starting the journey you take one step closer to delivering internal and external changes within your organization based upon the data you already have. I recommend holding a discovery workshop to identify the benefits you will enable and your next steps. Sounds pretty simple and straightforward, doesn’t it?

My customers often find that some data is more valuable than others. Out of the hundreds or thousands of data points that could be gathered, only a small handful will give the highest likelihood of accurately determining a business outcome (following an 80/20 rule). Clustering, co-occurrence and classification analysis techniques can help you to determine which data points produce the greatest value and therefore what you should focus on.

Check out my next blog where I’ll address the 2nd maturity level: ‘Beyond the use case’.

I would like to add a special thanks to Philip Griffiths (@ThePGriffiths). Philip was until recently, the strategic partner manager for the IoT practice and took the initiative to write this blog-series that you are reading now.

The journey to managed enterprise IoT

<This blog was previously published at the Atos Thought Leadership website>

A lot has been said about the data-driven economy we live in and its effects on the people, processes, places and products of all businesses, but how many companies actually use their data efficiently? Every organisation should not only be driven by data or the Internet of Things (IoT – a term we will use to cover gathering, processing and extracting value from data), but also ensure that it delivers measureable outcomes into their core business processes. Few can claim to be at this level of maturity and, if you are not one of them, our overview of the journey to managed enterprise IoT can help put you on the right path.

A true data-driven strategy can deliver benefits that range from tightly integrating customer care into product usage and performance to being able to remotely monitor and improve product (or service) performance to enabling new revenue streams.

We can divide the journey towards Managed enterprise IoT into three levels of maturity (that will be further explained with their own separate blogs) including the six sequential activities shown in the picture below:

  • Enabling the use case: exploring and solving business operational problems in minimum time to value with easily understandable business impact on people, process, places and products.
     >> Benefits: Project – Business operations managing each use case
  • Beyond the use case: ensuring predictability for delivering value – i.e. high quality (from fewer errors), resiliency (higher availability and stability) and security.
     >> Benefits: Program / Portfolio – Business operations across all use cases
  • Managed Enterprise IoT: simplifying the complexity of IoT, which is now business critical, to be both agile and predictable as well as being proactive, prescriptive and automated to deliver positive and measurable benefits for your whole enterprise.
     >> Benefits: Enterprise – IoT underpins whole business

Businesses are made up of people, processes, places, and products which need to create value – the fundamentals of business that have not changed with a data-driven economy. As businesses derive more and more of their revenue from data (and IoT), they are required to resolve its inherent challenges – enabling business value, managing the quantity of things and data, dealing with the complexity of the ecosystem and reducing security and privacy risks.

This is critical to enabling benefits for companies, to their customers, shareholders and the wider data-driven economy – the outcome of Managed enterprise IoT. Rather than taking big leaps from one maturity level to another, put in place a road-map at the start of your journey to Managed enterprise IoT (particularly as forward planning will save lots of time and effort later).

The companies I work with often ask, “Should we manufacture a solution in-house or purchase it from an external supplier?” These are my high level recommendations:

  • Nothing exists in a bubble; consider your long term strategy and competencies (taking into account value and performance). Approximately, core ones should be made, marginal bought, supporting could be either – core is defined as high value and high performance, marginal as low and low respectively.
  • Do not think that you can only make or buy; you can customize a solution that fits your needs. Build a level of extraction (i.e. non-native) above the layer at which you buy; this will enable you to commoditize everything below it, to future proof and ensure cost reductions and quality improvements.
  • Open source gives you access to a larger pool of innovation and can be a low cost way to experiment (enterprise versions offer greater predictability).

In the next post, I will explain the 1st level of maturity of this journey towards Managed enterprise IoT: ‘Enabling the use case’.


I would like to add a special thanks to Philip Griffiths (@ThePGriffiths). Philip was until recently, the strategic partner manager for the ATOS IoT practice and took the initiative to write this blog-series you are reading now.

 

The challenging future of the data center in an IoT landscape

Disclosure: This post was previously published on Atos Ascent Blog Post and was co-authored by Mr. Andrea Sorrentino (LinkedIn) – minor format and content edits have been applied to fit it to this website.

“Whosoever desires constant success must change his conduct with the times.” This phrase of Machiavelli Wikipedia perfectly aligns with how we should consider the Internet of Things (IoT) – the need to change our mindset regarding the IT industry and how we use data. Better analytics are now creating an amount of information which has never been obtained before; providing important insights into markets and consumers. The IoT can further enhance the business value extrapolated from data, and we find ourselves in the early phase of development of this new technology that will shape our vision of the world.

Now, imagine a company that distributes millions of sensors along its production chain in several factories, all sending data about machinery to a central location. On one hand, managers will have access to a large amount of data which can effectively contribute to help correct inefficiencies, and to create business value. McKinsey estimate that if policy makers and businesses get it right, linking the physical and digital worlds could generate up to $11.1 trillion a year in economic value by 2025. On the other hand, the data center involved would probably very quickly reach its processing capacity, as it would be overloaded with data and connections that are being pushed from the sensors. According to Gartner, it would not be technically and economically feasible to maintain every computing activity in a central location with the IoT.

The impact of the IoT

The IoT will have a huge influence on companies’ data center strategies, and the best option is likely to be creating a distributed data center infrastructure, installing smaller facilities close to the devices for local processing, with further aggregation in a central location. This creates a more flexible management system which can be adapted to changing requirements. The old logic of using a centralized data center to reduce costs and increase security is simply not compatible in the IoT era. However, any strategy is dependent on the smartness of the devices being used to filter data and avoid overloading the entire system to prevent inefficiencies.

The adoption of the IoT will likely lead to a profound reassessment of data management strategies within businesses, and aspects such as costs and the integration of new technology are hot topics for managers today. The IoT represents a great opportunity for creating smarter companies that are more responsive to market needs. It enhances capabilities that, decades ago, managers could barely imagine: real time analytics that allow for preemptive intervention to avoid potential errors.

Therefore, implementing IoT solutions is important to be able to create a tailored data management strategy, re-considering the role of the data center for a business. The IoT will likely speed up the transitional process to cloud-oriented infrastructure; companies in different sectors are already gradually running a larger part of their processes on hybrid cloud solutions. The cloud is an enabler of digital transformation which can enhance the potential of the entire infrastructure, and support in delivering better services.

A future for the traditional data center?

The advancement of IoT and cloud computing may lead to the reduction in the use of data centers by businesses, simply due to the potential level of scalability and flexibility that companies may need to attain. Clearly, security cannot be underestimated and companies need to maintain a robust infrastructure around their data. It is likely that data centers will gradually lose strategic importance for most businesses, however physical locations will still be needed as safe stations of reference in case of system failures.

IT managers need to begin thinking about the best approach to optimize and innovate their infrastructure, ensuring it doesn’t become quickly outdated in a fast moving environment, enabled by the IoT.