The old ways have failed us
With IoT projects we face new risks and have a hard time to manage them. This is why we need to refresh our risk mitigation methods.
Much like gravitation, the relationship of risk and reward could be formalized as a natural law.
Development projects are a company’s investment in the future. And as every investment carries a risk, it’s not surprising that many projects fail.
This is why many companies have adopted a best practice of using risk management in development projects inspired by ISO 31000.
Especially IoT projects have a high failure quote (fail to collaborate, fail to deliver product, product fails to impact market). One source even lists a failure rate of up to 75%.
Risk management in IoT projects
So, to save valuable time and resources in IoT projects, strong risk risk management should be in place.
According to “four ways to discover risks in your next project” (Source), typical ways to discover and mitigate risk are:
Schedule Based: where we plot the expected risk along the project schedule.
Development Process Based: where we plot the risks along the company’s product development process.
Success-Thwarting Based: where we plot “the possibility that an undesired outcome disrupts your project”.
Prompt-List Based: where we use lessons learned from other, comparable projects.
Problem A: We don’t know anything for sure
All these methods work fine in conventional projects. But when it comes to IoT projects you are lost, because you don’t know much about
The expected schedule as the project might be very dynamic.The process to develop the IoT solution, which may differ from the typical process a lot.What you define as “success” in your project.Comparable projects, matter of fact there might not be any in your industry.
Problem B: New risks join the old ones
“The old risk did not go away just because IoT showed up” (Longtailrisk.com)
With IoT projects you add new risks to the ones you were already facing in traditional product development projects.
“So, which new risks do we face with IoT projects and how do we manage them?” (Every IoT product manager, ever)
The old ways of risk management are ready for a make-over
1 - Risk Discovery
In IoT projects you will need to start with a few basic questions first to answer as a project team:
How do we define success? Is this monetary or measured in “validated learning”? What happens to our definition if we need to pivot our scope?On which fundamental assumptions do we hinge our success? How many are there?
After that you’ll need to consider different sources of possible risks to your project:
a) Organizational risk
As in traditional projects the people in your organization may impact your success. But in IoT projects this becomes a major point.
Because IoT projects are typically cross functional they go against the known and beloved (?) silo structure. So as you introduce change to the organization you need to be prepared to step on a few toes.
One method to keep the overview is to draw up a stakeholder map with a few trustees in your team. This map can include:
The stakeholders across all hierarchies.
Their relationship towards one another.
Their stance towards your project.
Their hidden motives.
b) Technological risk
In the area of IoT, the technological risk grows when you work on the forefront of technology. You might consider new hardware and software which is not yet proven in the field.
If you are working in an established company to open up new “digital” products you might face an rather large, already installed base. This means you might need to upgrade the existing, “dumb” products. Think about what might compromise your success in this retrofit case.
c) Market risk
The typical risk revolves around not knowing what customers want. And if you’ll be successful with the use cases and features you came up with.
But with IoT solutions you also add the risk of catering to completely new customers. They might have totally different needs that what you’re used to.
Also, in IoT the security and privacy concerns of your customers are potential show stoppers for the product. Be sure you know the implications and challenges around IoT security.
2 - Risk Assessment
The typical risk assessment matrix looks good on paper but in IoT projects we have little to no “lessons learned” to work with. Thus, we tend to estimate the impact and probability inaccurately.
But how can we assess the risk anyway? We try that by adding details about the events and compensate for being to optimistic.
List the core project components which contribute to your success. Then, below each, list the risk events.
On the other axis you list:
Impact
Probability
Time to discover
And rate them subjectively from 1–10
The multiplication of these factors gives you the risk score.
As we tend to estimate conservatively the likelihood and impact of events, you may want to use the square risk score.
3 - Mitigation
To avoid that any of these risks mess up your IoT project, you’ll think of actions. They are started immediately, at a certain project phase, or as soon as an indicator lights up:
What can we do now to mitigate?
Who is responsible to monitor and mitigate?
What is the counteraction if the risk happens?
What is our “Plan B” for the project?
4 - Wash, rinse, repeat
The IoT risk matrix is not a “fire and forget” document to pull out for stakeholders.
It is rather a living document that belongs on your PM wall and deserves your attention at least once every other week for review. (30min every other week could save you valuable time and resources)
Be sure to track and refresh the findings on your IoT risk matrix. Share the findings as well as the responsibility in your team to maximize your IoT project’s success.
By the nature of their work, people at The University of California, where I serve as Chief Risk Officer, are risk…hbr.org
TL;DR
IoT projects fail quite often because they work with new technology and outside of typical processes. To enhance their rate of success we need to mitigate the risk in a smart way. This can be done with a few techniques outlined above which are adapted to a high uncertainty environment of IoT projects.
Daniel Sontag connects the bots:
As Industry 4.0 lead and manager for connected products, he does what he loves — tying business to tech, and theory to practice.
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