Here, There... Intelligent Buildings Everywhere!
Like most intelligent buildings and supply chains, there are challenges with disjoints between existing systems, Internet of Things (IoT)-related smart assets and other human-collected data. Often asset data may not be acted upon in a uniform manner, and visualization of data is often misjudged as interpretation.
Visualize, Interpret, Anticipate…then ACT
Like most intelligent buildings and supply chains, there are challenges with disjoints between existing systems, Internet of Things (IoT)-related smart assets and other human-collected data. Often asset data may not be acted upon in a uniform manner, and visualization of data is often misjudged as interpretation. Sometimes viewing statistical asset information in a graphical format may seem to present a solid solution but data is lost on how companies/techs/people respond.
Stop…and Automate IIoT Actions!
With a flurry of the manufacturing supply chain trying to do more with less and coping with the varying degrees of a remote workforce, it’s critical to turn more to automation to lessen the load on individuals. The question is “…but at what cost?”
With a flurry of the manufacturing supply chain trying to do more with less and coping with the varying degrees of a remote workforce, it’s critical to turn more to automation to lessen the load on individuals. The question is “…but at what cost?”
IIoT Purgatory
Many manufacturers and distributors that have embarked on their Industrial IoT (IIoT) journey recognize common hurdles often forcing them into IoT purgatory. With an end goal of monetizing on the initiative, these organizations may have:
started to manage sensor-related data but need to harness and act on it,
produced graphical, data visualizations with ideas of what needs to be done but haven’t done it,
created too much “white noise” with sensor-related data making it difficult to wade through which alarms or aggregate of alarms are most important, or
acted on the visualized data by generating a work order in their own system or a system down the supply chain, but realize they have no supply chain aggregation about:
what happened,
why it happened,
how it was resolved, and
what they need to do in the future to increase efficiency.
In essence, the actionable data is siloed into linear business systems either within the organization or outside of the organization. It could also be a combination of both; worst case is the data is simply lost.
Break Free and Monetize
Sensor-related “white noise” can be one of the largest later-stage issues when capitalizing on IoT data. But what is often just as important in addressing white noise, is not simply pinpointing what needs to be done, but the timing of when to pause and when to act. Plus, a “data-over-the-fence” mentality without tracking what happens once action does occur (whether one provides direct service or not), doesn’t poise an organization to outpace its competition in the supply chain race for data.
The good news is that many organizations break through IIoT purgatory hurdles with additional automation that doesn’t take years of building on an IoT platform but can be plugged in and managed in months.
The Intersection: IIoT and Service Parts Planning
Many conversations revolve around combining IoT data with data already available via various business systems. Service parts planning is often integral to this. Key to properly planning parts heavily depends on better planning inputs. Where do service parts planning and IIoT intersect?
Better managed Alarm Response Automation (ARA) of IoT-enabled assets contributes to:
predicting maintenance events,
initiating pre-emptive service (which minimizes asset downtime),
managing asset utilization (for more accurate failure rate forecasts), and
securing as-configured data (which enhances views into replaceable parts).
On the data side, service parts planning gains a new vantage point. Not only does the reflection of ARA contributions improve the accuracy of demand events, provide more granular failure rates, and increase insight into replaceable part data, but it enables better forecasting and optimization of service inventory. This results in:
increased machine uptime, and
more productive supply chains.
The combination of the resulting data from both IIoT ARA and service parts planning, sets the stage for an organization to capitalize and monetize on their IIoT investments.
Time to Act
While each member throughout the supply chain may be at different phases of IIoT-enablement, every member has an opportunity to position themselves as a winner in the race for data. Definite opportunities await an organization whether it be a manufacturer, OEM, distributor or dealer.
There are ways to monetize. By setting the stage to monetize on IIoT efforts, supply chain members have a unique opportunity, especially when automation is so integral to success.
In the end, the cost of remaining in IIoT purgatory far outweighs the price of taking action.
Previously published by Baxter Planning as a guest blog
The OEM Blind Spot
It’s obvious there is a race for data among the supply chain. What many OEMs miss is that the data an OEM can capture in their equipment supersedes any other data captured in the supply chain. There is power in IIoT, but will OEMs resist the opportunity to monetize?
THE ADVANTAGES OEMS OFTEN MISS
It’s obvious there is a race for data among the supply chain. What many OEMs miss is that the data an OEM can capture in their equipment supersedes any other data captured in the supply chain. The OEM is either at the very beginning of the chain or at the central point in a supply chain ecosystem when it comes to Industrial IoT (IIoT). There is power in IIoT, but will OEMs resist the opportunity to monetize?
Find out here about the power OEMs have to generate new revenue streams and strengthen ties to its customers.
The Winner in the Race for IIoT Data
Whereas a primary pain point exists between the integration of IIoT data and various business systems, the true value becomes apparent when a more holistic approach is taken that views the manufacturer’s enterprise system as one component within the supply chain ecosystem.
Even though it’s a race among members of the supply chain, winning takes on different angles and hues depending on the participant.
Whereas a primary pain point exists between the integration of IIoT data and various business systems, the true value becomes apparent when a more holistic approach is taken that views the manufacturer’s enterprise system as one component within the supply chain ecosystem.
The individual enterprise data integration isn’t the primary goal – it’s using and capturing enough data to be useful in generating a win-win.
Focus!...and Take IIoT Action
Your focus may be within your four walls – but the real value is shifting the Industrial IoT attention to your supply chain. Create Actionable IoT in the face of Industrial IoT pilot purgatory.
Your focus may be within your four walls – but the real value is shifting the Industrial IoT attention to your supply chain.
While the latest edge computing consolidates, contextualizes and filters end-point sensor data near the point of creation, it also provides a pathway for this data to be packaged and delivered. Where it’s delivered and how it’s used once delivered is key – sometimes obvious, but not necessarily easy to execute.
Read more on how to avoid IIoT purgatory.