This Industry Viewpoint was authored by Arco Versluis and Sathya Narayanan of Prodapt
Digital Service Provider’s (DSP’s) inventory data consisting of their assets and services is very critical to their operations. These assets grow every day making it more difficult to manage. Almost all the DSPs manually register their inventories once their capacity management team forecasts and decides to expand the network. It doesn’t matter how much the technology evolves from now, the registration would remain a manual procedure. Hence, an efficient inventory management system with an intelligent User Interface should be built to guide the users in the manual registration process. Lack of such intelligent registration tools will hinder the ability to plan optimized networks resulting in delayed service, poor customer satisfaction and loss of revenue.
Factors leading to inventory data integrity issues:
- Assets and services are manually registered in the OSS inventory
- Duplication of records due to lack of efficient validation tools
- Multiple siloed inventories
Existing approaches to improve inventory data integrity
- Creating a single central integrated inventory
Siloed inventory systems lead to data pollution- Duplicate data, Outdated data, multiple manual registrations. A central integrated inventory will provide DSPs with a unified view and a single source of truth. Also, It is recommended to set up a data migration factory as it will accelerate the implementation of a central integrated inventory transformation program. The team needs to Initiate migration from the inventory with the least data to the central inventory. On completion, they need to compare the data with Network Management System (NMS) and other old inventories. Once the quality of data is good, users are familiar with the system and all the processes work without any problem, migrate the remaining systems one by one.
- Automated inventory reconciliation
DSPs must Use domain experts to choose the right network discovery and reconciliation tools and to Implement automated workflow. Stringent business rules needs to be framed, revised and set inside the reconciliation tool. The Reconciliation application needs to give two reports once the synchronization process is over 1) Summary report (reconciled data) 2) Fallout report (configurable items that were not reconciled along with the reason)
Regardless of the tools or technologies used by DSPs to tackle data integrity issues discrepancies still happen, as data is registered manually. This issue must be fixed during the manual registration process to have a high-quality inventory data. We are proposing a data driven approach to arrest these errors at the source.
Proposed Data-driven approach using data-driven inventory wizard:
Data-driven wizard aids in improving the registration quality and arrests the errors at source thereby maintaining a high quality of data in OSS inventory.
How does this data-driven wizard work?
- Capacity management team forecasts the demand and plans network expansion
- Based on the forecast, capacity management team creates a work order
- The desk engineers pick up the work order from data-driven inventory wizard and starts registration process
- The wizard contains a data intelligence engine that comprises a custom-built business rule set, configuration tables and data from external sources. It aids in manual registration and guides the users in end to end registration process.
- Registration data is submitted to the OSS inventory.
- Execution of network rollout and activation based on OSS inventory data.
Key Capabilities to be Built on Data-driven Inventory Wizard
- Auto-populate: The data-driven inventory wizard should be able to auto-populate specific data based on logical combinations, business rules, and external sources.
- Dropdown menu: It should provide drop-down options when there are two or more logical possible combinations and filter illogical ones.
- Manual data validation: The data-driven wizard should have a validation check (logical and syntax check) for manual data entries, that ensures wrong manual entries don’t go into the inventory.
Let us now deep dive into all these three capabilities of data-driven inventory wizard:
- Based on the logical combinations, business rules and data from external sources, inventory wizard should auto-fill in all the possible data in the User interface.
- For example: While adding network equipment (Ex: DSLAM), when users select a site name and select corresponding chassis template, corresponding network equipment model and production code should auto-populate. Also, other related parameters should also be auto-filled subsequently.
- Whenever there are 2 or more possible logical combinations available for a selection, the wizard should provide a drop-down menu in which the user can select the correct entry. It should also filter all the illogical combinations based on business rules and give only minimal logical options for the user.
- For example: Once the user selects the uplink slot, the wizard should provide the list of logically (filtering out illogical ones) possible uplink templates through a drop-down menu rather than providing the entire list of templates. When a user selects an uplink slot that can logically go with five uplink card templates, the wizard must provide the user only with just those five options to select from.
Manual data validation:
- The above two capabilities reduce the total errors drastically. But there will be entries where the user needs to manually enter specific values/data.
- The manual entries need to be subjected to validation checks on both syntaxes as well as logical combinations to ensure no duplicate registration happens.
- The wizard needs to protect the data from unacceptable values and wrong format by throwing an error whenever the users deviate from acceptable formats and values. For example, If the user is entering a rack or cage number in terms of an alphabet, the wizard throws error as unacceptable format.
Benefits of using the proposed strategy
With data-driven inventory wizard in place, DSPs can realize major benefits in data integrity of inventory such as:
- Timesaving: Improves manual registration time by 87.5%.
- Accuracy in data: Registration accuracy on an average improves from 70.5% to 98%.
- Reduced Efforts: Reduces manual data entry by by 65% and the rework to be done due to errors during manual registration
About the authors
- Arco Versluis – Solution Architect Medior, Prodapt Consulting
- Sathya Narayanan – Assistant Manager, Strategic Insights, Prodapt
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