Analytics Portfolio

Benchmarking systems

The use of benchmarking systems to monitor and improve performance metrics is often hampered by a lack of real comparability due to external factors. This can be remedied by creating models for the benchmark that take into account these external factors.

Analysis of the raw metric

Typical performance metrics

  • Realised prices for a product
  • Time or resources per client used for providing a service
  • Revenue generated per sales area
tend to vary hugely, but possible performance issues are clouded by the influence of external factors:
  • Prices may vary due to sold product type and added services
  • Complexity of delivered services may vary due to client size
  • Sales area have varying customer structure
  • etc. etc.

Determine influencing factors and model baseline

For the pricing levels of products and services, this could be a list of the main product features and differentiating attributes, e.g. in a B2B context

  • Service level agreements
  • Delivery and payment terms
  • Volume and rebate agreements
A model is then built to determine the influence of each factor on the price and to calculate a baseline price for each situation.

Establish fixed benchmark

A fixed baseline and acceptability-corridor, based on the agreed influencing factors, is then established.Performance levels are tracked against this new benchmark.

Individual performance sheets

Responsible managers are provided with regular reports about the performance of their area against the benchmarks.

About me

I am a consultant and project manager in marketing and business analytics. Having worked in the area for more than 15 years and having led the Data Science and Analytics teams at IRI Germany from 2009 to 2016, I am now again working as an independent consultant focusing on applications of Big Data and AI in marketing.

Quantitative Consulting

Boris Vaillant - Quantitative Consulting 17

QC 17