Creating a Unified Asset Profile
Creating a Unified Asset Profile.
Before we review the topic of creating a Unified Asset Profile, lets review the Salesforce Data Cloud model as the metadata framework that manages the data and all the supportive processes is key in the next phase of the asset model. Salesforce Data Cloud is a usage based offering which combines a range of data points from various data sources to build a unified individual or account by creating unique and individual profiles.
By unifying data across multiple systems Data Cloud uses rulesets and reconciliation rules to create targeted audience segments. An important design element is that these data points are not merged as the source records still exist after data points are combined. This data can be demographic or behavioral like e-commerce purchases, order history or customer support cases.
What goal does this solve? Simply put, Identity Resolution to better track and honor your customers preferences throughout all of your company’s channel marketing practice. A key value is also finding hidden insights in data that humans are not able to see easily to position Services (revenue) in a competitive and valuable way to our customers in ways that they also do not see for success.
Now lets take the concept of Data Cloud and unify the asset profile.
As is the case for individual and accounts, data is coming from multiple source systems in fragmented formats and insights. You might have notes from the field techs, IoT data logs, historical data from Cases, reports, 3rd party or the asset manufacturing data, surveys and SM from customers. The list goes on and on.
As an undertone to this asset data is the Services positioned to support the assets that are manufactured or implemented so even though we have moved from an individual and account model to an asset (Installed Product) model, we are still marketing to the company based on the Site insights.
*Note: The Site or Location is a hierarchy with 1:M Assets via Lookup that reside in that location. The Site contains key metrics/KPIs gathered from all Assets and Analytics/AI and predictive models are applied to the data gathered.>
Each of these sources of data will provide data sets that will most likely contain different data structure (metadata), data set organization, record fields (dates, time, region, part name, etc) and the list goes on and on. What can we do to streamline the data from multiple sources and make it actionable. Apparently, quite a lot. Lets list a few below.
Case Consolidation: Cases can be created from IoT, Customer calls, FS Techs and other channels with automated Work Order record creation and Work Types from Predictive Modeling practices. From Services comes revenue so before working on the Asset model, get the Cases in your org managed correctly.
Dynamic Checklists: Streamline the data input from your field techs via Dynamic Checklists like Salesforce, Youreka or custom designs on mobile apps. This will ensure the data is applied in the correct format, at the right time (at the source of the issue vs end of the day/week) in consistent and completed formats with automated actions and flows. I’ve seen the value in the utilities space and its impressive.
R&D: Bring R&D teams into the data discussion. Build Asset components to provide relevant and direct data input from the Asset in the field. If there is a product that has a few blind spots, the time to fix the issue is in the next iteration of the product or to apply add on components that can provide key data points. My customers are having these discussions to better understand the asset and build a closer more direct relationship with the assets in the field.
IoT: Build a comprehensive IoT Strategy for inputting key data points via data sets to measure the state of the asset. A ‘strategy fuels the platforms’ needed to support the model and not the other way around. What are we missing in our relationship? What is the data we are getting telling us? How do we get this data that is missing (R&D,etc)? How can we combine this data with other data sets from different systems to have a better understanding (ie. metadata framework)?
Customer Input via SM, surveys, sites, etc.
Etc, Etc, Etc – this is a short article so I can only cover so much.
It helps to put a Data Strategy together so that when all this disparate (but now organized and streamlined) data is captured from multiple source systems to one target system, you can combine different data to complete a Unified Profile of your individual asset and produce better actions from the asset and improved analytics from the Site location. After building your Unified Asset Profiles you can utilize AI to find the hidden insights that humans don’t see. There is tremendous value in your data and as I mention in most of my posts, your “data is an asset”, just like your services and products you sell. Services follow Installed Products but to drive revenue in Services you have to show optimal value in customer Sites.