What is an intelligent enterprise :Most of us must have heard of terms like –
1)Data, 2)New business models, 3)new revenue streams,4)empower employees, 5)Automation, 6)Customer at the center, 7)predict customer needs,8)Reduce risk, 9)faster outcomes,10) respond to changes,11)responsiveness ,12)digital thread,13)digital transformation etc.
If one has to define an intelligent enterprise with terms mentioned above , it is like ..
- Data being the new oil, use data assets to predict outcomes to reduce the risk and disruption.
- Insights into data will unlock opportunities,which open doors for new business models and revenue streams
- Predict and respond to customer needs
- Connecting the entire company, from engineering ,manufacturing, sales, service groups in one thread
- Empower employee with Robotics process automation ( Human + robot= Cohbot)
Traditionally, companies collect data like transactions and documents produced during the standard business process(IT) . Equipment/Machines were never used to come with sensors embedded, even if there are any external sensors attached to serve a specific purpose , the communication between multiple hardware and software partners were complex to handle. It never made a business sense to have a sensor embedded into every equipment due to heavy cost of sensors those days .( Dumb assets)
Now that sensors are getting cheaper and the computational capability at edge is getting better day by day , more and more equipment and machinery comes with advanced sensors that are capable of capturing data at 100th of every second as well,.( Smart Asset)
Sensor:Transforms a variable to measures into the type necessary for measurement.
How Product become a Asset: If you look at Design to operate process from start to end , In the world of engineering where the product is designed and handed over to manufacturing for building it . Once the product is built and delivered to customer for operations ,from OEM perspective it is an asset . Partners involved in the entire process of design to operate are OEM (design and Build), service provider and asset operator.
When the product travel from OEM to Asset operator ( Product-> Asset) surpassing series of milestones like design,plan,manufacture,deliver,operate,maintain,decommission. There never used to be a common asset taxonomy between stake holders( OEM,operator etc), due to which there was poor asset data integrity and siloed asset data.
Due to lack of collaboration between stake holders , there was no way for an OEM to pass an update of specification/service bulletin on an asset . There was no collaboration/network between stake holders ( Partners) which could have enable them to share information in real-time starting from engineering till product maintenance in which everyone share one standard model with common taxonomy.
Digital thread is a communication framework that allows connected data flow in integrated view of asset data through the life cycle , traditionally siloed .
SAP intelligent asset management (IAM) is an integral part of SAP intelligent enterprise . SAP intelligent asset management supports full digital representation of connected assets along the life cycle delivering an embedded, collaborative and real-time set of next generation processes and systems.
SAP IAM consists of,
- Asset intelligent network–>provides single version of truth enabling collaboration of cloud based network b/n OEM,Operator, service provider.
- Asset strategy and performance-> Measure and improve the performance of asset (likely chance of failure and its consequence ), if i have a factory of assets, they all are not the same ,a batch of assets have less frequent failures, even if they fail , there would not be any noticeable impact on my production, but second batch of assets are prone to less frequent failures but will have major impact on the production, highly critical .
- Predictive maintenance and service-> Predicting the anomalies and fixing them to avoid unplanned breakdowns. Pro-active service will make sure you are wasting the services, reactive service is loss of production , due to break down, striking a balance of both, where providing service by predicting failure for the right asset at right time, so that we are not over doing service or reacting to failure with delays .
- Predictive Asset insights -> Combine big data with physical based analytics. Closed loop process between design and operation.
What next .. As assets gets more and more intelligent capturing ,ingesting, storing, analyzing data along the life cycle . It may un-locks many revenue streams and business models in future. The very model of product sold as product vs product sold as value added service / product as service would be a new guaranteed revenue stream for future .