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What are the key points to look out for when evaluating IoT business cases—especially outside of ones industry expertise?
I think we need to look at each IoT business case individually - even within the same industry. Begin by establishing the data strategy for the project since different projects have different objectives, collect different data, and has different stakeholders that will want access to the data and the insights therein.
- Identify the data you want to collect and understand the meaning, the structure, the origin, and the location.
- Determine how the data will be packaged and made available to stakeholders while respecting rules and access guidelines.
- Determine how you will store data, structure and location, that supports access and procesing across the enterprise.
- Identify how you will move and integrate data residing in multiple locations and provide a unified view of the data.
- Establish, communicate, and enforce information policies and mechanisms to ensure effective use.
Key thing to address is "what are you looking to gain from IOT?" - the answer should usually be reducing cost or increasing revenue. Implementing IOT because it is technically feasable is an interesting project, but unsure what value will come from it. This question is best addressed by someone familiar with healthcare industry and/or the product manager. However, if this person is an IOT novice, they may be thinking with blinders on and not fully understand what they might do. If this is the case, a healthcare industry expert should consult with an IOT expert to get familiar with what others in their and related markets are doing. Once the IOT use case is determined, it can be implemented by an IOT expert not neccessarily familiar with healthcare market.
For example, "Our service techs are being called at odd hours which is costing us money by having to staff up large service organization for peaks and valleys of service". If we know machine usage or sense when the machine is on the verge of a failure through predictive maintenance data collected, we can reduce service staff and do preventative maintenance at our convenience verus repairs at unplanned outages. Or the revenue producing product-as-a service use case of "smaller clinics can not afford our expensive machine; let's offer 'product-as-services and not machines', so can we charge our clients for every use, and maintain on our schedule, perhaps with refurbished equipment. We can now address a previously untapped market and increase revenues."
Once the IOT use case and goal is determined, then you can attack it from a technical point of view - what is the environment it is used, what data are you trying to capture/analyze, how will you transmit/store/analyse the data, budget/schedule constraints.
Here's my experience-based advice:
- Understand the forces at work in the healthcare industry;
- Understand the needs and buying behaviour of the potential customers;
- Why have some already engaged with IoT healthcare devices - Why have most of them not yet implemented IoT healthcare devices?;
- Apply the understanding of your core value proposition to the IoT healthcare industry.
o The effect regulation plays into the different IoT business cases. For example in healthcare HIPAA Compliance needs to be accounted when designing new operational models (business processing, data processing,), and ownership of the data being processed needs to be identified. Also, as technology based applications increase and penetrate health care, ongoing security & privacy vulnerabilities factors should not be forgiven. We should not just assume that after demonstrating the IoT applications works well or even excellent, deployment and implementation will just follow; regulatory factors have slowed down adoption of solutions even when some will benefit healthcare.
o The data flow processes used ( and sometimes established in certain industries like in finance, healthcare) may be different than those used in the industry of our expertise.
o The infrastructure to support the technology we have been using in our industry may not be there and/or it may not be adequate.
o The methods or tools used to enable the capabilities may not align or bridge well with those used in our known area of expertise.