Measuring efficiency gains of Quote-to-Cash (QTC) projects
Quote-to-cash (QTC or Q2C) is an IT approach to integration and automation of end-to-end business processes.
It covers the entire lifespan of a product: from planning, quoting, delivery, billing & invoicing to payment processing and financial analysis.
Organizations undertake various IT projects such as CPQ deployments, CRM customizations, integration & automation and others to make their quote-to-cash more efficient.
QTC is an excellent planning and implementation framework for business transformation & optimization from both IT and non-IT perspectives. It has a proven track record of finding performance bottlenecks, defining business architectures and project prioritization (see this blog post on establishing QTC priorities).
| Businesses often tend to focus on the implementation side of QTC while loosely (or incorrectly) defining the success criteria (“increase efficiency”, “reduce cost”), which in turn leads to projects falling short of expectations, or even focusing on wrong projects in the first place. |
This post outlines a framework to help businesses measure efficiency gains and establish measurable goals for QTC projects.
Defining goals
The list below provides a few real-life QTC goals/objectives:
- 10% cost reduction of order delivery
- Reduction of SGNA per $ of generated revenue
- Process 10% more orders with the current headcount
- Shorten order delivery time by 25%
- Error rate reduction to reduce cost of fixing errors and improved user experience
- Increased sales velocity/reduction of sales cycle time
- Improve data quality to allow accurate reporting
- Increase operational efficiency
It is easy to notice that some of these goals are better than others.
In general, a good set of goals:
|
Refining goals
While “what” is driven by the business (e.g., “20% cost reduction per transaction”), the “how” part of the problem is a process and IT systems question.
As far as IT systems are concerned, optimization can be narrowed down to only three categories of measures:
It does not matter what is measured: quotes prepared, orders delivered, customer issues resolved, MTTR etc. — goals and efficiency gains can be generally defined in terms of these categories. |
Very often, one of these is a countermeasure to the other two: speed can be increased and the expense of efficiency and accuracy; accuracy will suffer with increased speed while keeping the same efficiency levels, etc. The exceptions are usually related to automation which can address all three at the same time.
Increased processing capacity
Capacity is best expressed using unit economics (direct revenues and/or costs on a per unit basis).
Examples (“what”):
- Operational cost per $ of new revenue
- Quotes generated per sales department head
- New order revenue $ delivered per head in operations department
Means of improvement (“how”):
- Integration across systems in process flows (e.g., from sales to delivery)
- Automating manual processes (e.g., eliminating manual entry)
- Optimizing parts of the process: faster quoting with CPQ, implementation of uniform process flows for order delivery, etc.
- Task driven delivery with automated hand-offs, task queues, workload balancing, etc.
Decreased processing time
Processing time is based on average interval measurements both end-to-end (e.g., quote to bill) as well as partial, i.e., order to order confirmation. Interval variability (divergence from average values) is also an important (and often overlooked) measure, as it gives insight into process consistency and repeatability.
Examples (“what”):
- Sales: time to close a qualified opportunity, quote to bill, lead-to-quote
- Order processing: order placed to delivery; order received to firm order confirmation (FOC)
- Customer support: MTTR (mean time to repair)
Means of improvement (“how”):
- Shortening a critical path in the delivery process
- Replacing data swivel-chairing with integrations
- Improving information flow in the organization (e.g., with tasks, queues, cases, etc.) to minimize disruptions
- Making information more accessible (reduce staff time spent on searching for information)
Reduced error rate
The error rate is best measured per unit of revenue or unit of processing (i.e., transaction count). Weighted values can be applied, as some errors are easier to correct (i.e., have a lower correction cost) or have a lower customer impact.
Examples (“what”):
- Number of orders with problems/jeopardies
- Wrong data entry count
- Service desk cases per product
Means of improvement (“how”):
- Reduce amount of repeated manual data entry — copy prior data automatically instead
- Replace data swivel-chairing between systems with automated integration (e.g., quote to order, order to billing)
- Automate processing with workflows to ensure sequence of steps, required data entry, etc.
- Employ data validation rules
- Run data quality checks & reports and improve data quality as a continuous process
Conclusions
Defining goals is one of the most important steps in quote-to-cash optimization planning. A good set of goals contains a limited number of goals, with each goal that:
- Are specific and measurable
- Define what needs to be accomplished and how
- Have impact on one of the following: Increased Processing Capacity (efficiency), Decreased Transaction Time (speed) or Reduced Error Rate (accuracy)
Nextian is a vendor of quote-to-cash (QTC) software for cloud and communications helping providers accelerate growth and increase customer lifetime value.
Contact us today to find out how we can help you!
