Mature Service Management means tracking the cost, value, risk, quality, and demand for services. Service Costing is often the first step on this journey, but many companies stumble , falter ,or just fail to launch.
Here are the top things that prevent companies
from having a successful Service Costing implementation:
Not understanding the Use Cases for the implementation.
A Service Costing implementation involves building a model of the service composition. Like any model, it can be designed and structured in multiple ways. Even the existing frameworks like the TBM framework have flexibility in how the data linkages are implemented. Choose the wrong data model and suddenly your design creates a model that is not capable of producing the types of reports and dashboards that bring real strategic insights.
Not Treating this project like an Enterprise System Deployment
IT and Technology departments have become very skilled at enterprise system deployments. Most companies have an understanding of data architecture, change management, system integration, report and dashboard design and management that allows them to deploy Enterprise Systems like ERP, Manufacturing Execution Systems and Warehouse Management Systems. The implementation of a detailed Service Costing model that is designed for show back or charge back of costs based on consumption will need data from your Enterprise Financial, Asset, CMDB, Labor, Project and Timekeeping systems ( at a minimum). It requires data architecture design, integration, and may cause one of the biggest changes in how IT and the business interact that you have seen in a long time. Too many times companies attempt to implement a solution with 1 or 2 people from IT Finance, a part time project manager, and a software vendor team. Is it really any surprise that these initiatives go sideways? Leverage the experts in your company to ensure this implementation is a success.
Not Sizing for a Big Data Initiative
If your organization is large enough, bringing together the data you need to model your services and calculate costs across many dimensions is a Big Data project. You will be bringing together data from 5–20 different systems. You may have millions of rows of financial data to combine with 100s of thousands of rows of CMDB and Asset data to combine with tens of thousands of rows of project data to combine with 100s of thousands of rows of labor data to combine with….. You get the picture. Understand the size and scope of your initiative and make sure that the tool you choose is able to handle the load. This is one of the reasons that Service Costing in Excel fails. Even before you start to build, make sure that the analytics you use to assess data readiness are up to the job. Without the right algorithm design, discovering circular logic in your CMDB before it blows up your Service Costing model can take months or longer. We cannot emphasize the importance of algorithms here. We routinely do this analysis in minutes or less, with less than 8 gigs of memory- but only because our algorithms are tuned for the efforts by experts on staff. Complex data problems like Service Costing do not require Big Iron or ever increasing server instances, they require smarter algorithms.
Not drafting a design before starting to execute
Even if you are leveraging an existing framework, your organization will not be uniformly mature. Some categories of services will be very mature already and ready to leap into consumption based models and demand management. Other service categories in your enterprise may just be starting to think in services and will only have data that will support presumptive business rules for cost allocations. Trying to treat them all the same with an out of the box framework from a software provider will lead to frustration from both your advanced and nascent services.