There is no doubt that data analytics is one of the most important developments in recent years and promises to dramatically improve how shippers can manage and control their transportation spend. But with all the promise comes much hype, and it can be difficult to distinguish between visualizations, dashboards and the real analytic capabilities required to deliver maximum benefit for managing your spend. There are two critical questions which any solution must be able to answer. First, you must be able to continuously monitor your spending with visibility into key components of that spend—you must be able to answer the question of “what happened?” Understanding spend dynamics at all times allows for rapid identification of both problems and opportunities. The more critical question is “why did it happen?” Answering this question is extremely difficult and highlights the true promise of robust data analytics. We’ll explore both questions in this session and discuss the necessary elements required to answer them through spend analytics. Specifically, we’ll discuss sources of data, the importance of data cleansing and enhancement, data transformation, key components and influencers of variance in transportation spending and techniques for measuring these impacts.
- Role of data analytics in overall management of transportation spend
- Importance of identifying spend components and determining what key influencers are
- How data analytics can be leveraged to produce meaningful variance and trend analysis across time, key performance indicators and spend components
- How data analytics can be used to perform root cause analysis and help identify appropriate courses of action
- Role of visualization in variance analysis
- Importance of data normalization and enrichment