As it has been awhile since we've discussed the IoT on the forum, how big of an impact do you see the Internet of Things having on BPM?
Big impact - We already have IoT impacting in that external devices frequently source data to run-time Case environments hosting BPM process template instances.
These instances can have in-line compliance control steps that consult imported IoT-sourced data and block/unblock processing at the individual instance level.
By way of a simple example I'd like to show an answer...
Imagine a vending machine. Currently these devices are being checked and maintained by a vending machine technician. Refilling is done by yet another role. Products that are sold out, are being refilled on regular basis. But not pro-activily. Same goes for break-downs; only when something is broken and after calling a (repair) phone number, a technician will be scheduled on site...
Enter IoT... What if the machine is able to:
The drill: Small example but definitely impact the process. Big time. So... IoT does impact process. Combine this with current blockchain, AI, IAM developments and we have a whole bunch of BPM related stuff to work on.
How many times I have seen the phrase "impact on process"... More importantly still and in context of process: I strongly believe we need to get rid of traditional company thinking and move to community and network thinking. Currently we face a growing gap between old thinking (and derivated regulation to name just one) and these exciting new developments.
IoT programmes may drive more demand for BPM technology and BPM management methodologies.
Because BPM is the best solution to the most challenging IoT problems, specifically complexity and business semantics.
There is no IoT business value chain if you drown your end-users in data (e.g. via "alarm fatigue") or if you fail to focus on the fundamental purpose of IoT ("driving decisions").
Both example anti-patterns are really about understanding your business and engineering domain, and encoding that understanding in process and rules. Thus BPM (and business rules and analytics) as the technology where business ideas are first class citizens of that technology and can be directly deployed and evolved, without the expensive mediation of code.
Why not BPM?
Because demand for a BPM solution is not assured. The challenges of IoT business semantics are revealed in IoT programme governance and economics -- paying for the intangibles of business analysis and engineering are hard sales problems. BPM can enable IoT programme success -- if you are willing to step up and budget for the hard work of analysis.
From our previous discussions:
The IoT is incorrectly viewed in terms of smart devices, such as thermostats, refrigerators, or wearables. However, the real power of the IoT is in the data captured by smart devices, and the services and processes that can be triggered from this information. Data has always been the blood in the veins of BPM solutions, used to trigger processes, recommend next-best actions and guide employees. So it would seem then that BPM applications are perfectly suited to orchestrate the flow of information and actions between the smart devices, the consumer and businesses.
However many of the BPM applications we have today are not nimble enough to capitalize on this opportunity. I expect IoT opportunities and services to be delivered by low code platforms and point process solutions? For the most part IoT services will not be characterised by large scale professional services contracts. Instead IoT services will be provisioned rapidly and on demand by the end users.
What impact will the IoT have on BPM? It’ll transform the process automation market completely with many more new market entrants and lead us to reconsider what we think are the core components of a BPMs.
I believe IoT amplifies the use cases to use BPM solutions. Simply put it can connect insight to action. Either because the device/agent requires an action to be fulfilled manually or automatically, there is no better way to delegate these needs to a process. Alternatively, the devices can be less intelligent and send periodic signals with information (or lack of signals as well) so that a central entity analyzes these stream of information and decides to kick off a process. These are things that technically speaking were complex to implement in the past.
As mentioned before, it broadens the applicability of use cases to a new level!
Hate to poo-poo some of the Kool-Aid here (no, not really), but it's another source of data that will aid the onslaught of too much data, not enough insight for anything substantively actionable. Will have about as much overall oomph as blockchain.
I'm good sitting back, waiting and watching on this one.
Big on 2 counts. First the fact that machines as IoT create data which contribute to whatever the required business outcome. The BPM discipline will therefore include this to join up the end to end process with all required attributes such as audit trail real time feedback etc from the supporting software.
The second is when the "gadget" is created there must also be the understanding, control and reporting on the build process ensuring testing accuracy and "compliance" etc. Such an example going wrong was the Volkswagen emission measurements. All this is going to be a bit of culture shock for many but get it right all creators of information contribute to an empowered organisation.....needing fewer managers...!
Some thoughts that struck me in this area (at the end, with some pre-amble at the beginning):
In the future - if you want to integrate sensor/IoT data on top of people’s activity data, that’s not difficult to do. It will probably be part of large initiatives like digital transformation (cited)
We are firmly of the opinion that IoT/sensor data cannot possibly be useful without the human activity information that has to be superimposed on top of it for root cause analysis and intervention.
The simple answer is yes, and in some domains the imapct will be of a high order. The problem lies in the handling of the vast amounts of data that is generated and received. Real-time predictive analytics uses techniques for processing the data as it is received, and chunking it down to useful information. This is from IBM, "...Internet of Things, sensors can collect and analyze volumes of weather data collected at the edge for faster forecasts",http://phys.org/news/2016-08-ibm-scientists-imitate-functionality-neurons.html#jCp. We have some way to go yet before we fully integrate Internet of Things into BPM.
The only immediate impact of IoT on BPM is that systems will start playing out as more competent / present actors in wokflows.
It's not like solutions that couple data events with actions never existed until IoT... it's just that they will happen faster and closer to the point where event is triggered due to sensors.
Also, I don't equate 100x more data to a technological revolution. As always, cognitive impairment is still the limiting factor.
I can the several viewpoints expressed:
If we want Things to cooperate dynamically then we need to add a business viewpoint as well. See ref1.