IoT project requirements can be complex. Starting from the biggest challenge which is understanding the scale and scope of the initiative, IoT projects often get stuck due to multiple reasons - ranging from domain complexity to availability of technical resources to long implementation cycles. It sometimes takes multiple engagements with several vendors for an IoT adopter to realize value.
According to a recent IoT industry survey by Beecham Research - Though IoT has grown rapidly over the last 5-10 years, it's not all been smooth sailing, with up to 74% of companies considering their IoT projects to be unsuccessful.
More than 30% of IoT Projects Fail in Proof of Concept (PoC) Phase: Microsoft Research
Often an IoT adopter might require more than one solution to drive the expected outcomes. They might develop different IoT solutions for multiple business processes. That often means a continuous production line of Proofs of Concept (PoC) and Proofs of Value (PoV).
Microsoft’s IoT Signals Report highlights some interesting findings:
- Among those who have had IoT projects stall in the trial stage, 32% of businesses cited the ‘high cost of scaling’ as the main issue with getting their projects off the board.
- In other cases when the business benefits are not well enough defined, it’s difficult to justify moving forward on a project.
- 28% of organizations reported that their projects failed when their pilots demonstrated unclear business value or ROI (Return on Investment).
- 26% of companies found it difficult to justify a business case without demonstrating short-term impact.
- Lack of leadership buy-in can also contribute to lowering IoT success.
PoC and PoV can be interlinked but distinct processes. Some enterprises focus on a PoC when, in fact, the actual need is a PoV. As you evaluate IoT solutions for your operational technology (OT) needs, it's worth looking at both - PoC and the PoV built on it - to understand how business benefits are delivered in a real-world scenario.
Extracting Proof-of-Value: Value / Cost Curve
A PoC basically validates that a technology solution can work, with rapid, limited-scale implementation. Subsequently, a PoV demonstrates that there is business value to the solution. How? By justifying a business case to scale the solution to production.
For example: - A PoC-alone approach would be relevant when a domain-specific emerging technology is being tried out. A PoV approach would make sense when Operational Transformation initiatives are being undertaken viewed from a business lens. A hybrid iterative approach is most desirable. For eg:- Device metrics and data come from the devices, but maintenance, warranty and service provider info is often captured in an enterprise system (Ex:- SAP/ Oracle). Unlocking contextual insights by leveraging multiple sources of data is where true value exists.
Sometimes more data does not mean more incremental value. However, other times it does. And this is where the ‘PoV-driven optimal PoC discovery’ approach kicks in. Knowing the ‘what’ and ‘when’.
‘Is-it-feasible?’ kind of PoCs sometimes kill engagement momentum, because the focus moves towards getting an accuracy of 99%, whereas the PoV could've been discovered at an accuracy of 90%. The question is what it costs and what value it generates. The value/cost curve is not a linear relation (i.e more-is-more), but it is essentially - a curve. And a successful IoT program is all about finding the top of that curve.
Traditional approach | Modern approach |
1) PoC: Can it be done? 2) PoV: Why do it? Does it generate value? |
1) PoV: Why do it? Does it generate value? 2) Optimal PoC: How can it be done? |
Pivoting Agility Matters: Pivoting from PoV to Optimal PoC
Building any analytics dashboard isn’t rocket science. But building a dashboard - that can impact profitability, by unlocking key insights for process optimization/cost savings - needs a lot of agility. True value is creating dashboards that can be quickly adapted and modified based on user feedback.
An IoT program framework that allows for quick discovery of that optimal value/cost curve, is what makes all the difference. At Xoriant, we are enabling industrial enterprises to capture data smartly, analyze it, act on it sooner, and most importantly, unlock value sooner. Xoriant leverages Azure services (like IoT Hub, IoT Edge, Azure Machine Learning) in a low-code environment so that the PoV can be achieved in a very short time. The goal is to de-risk the project continually and create demonstrable views of business value with a customer’s actual devices and data. Xoriant’s approach allows for quick ‘Optimal PoCs’ and once PoV is generated, quick scaling to production.
To learn more on how Xoriant helped customers rapidly scale their IoT velocity - From ‘PoV / Optimal PoC Pivoting’ to Production - Connect With Us.