We have all seen it. We have all heard it. Perhaps many, or most of us, have even participated in the ongoing debate over which is more critical; transportation planning or transportation execution? Some trivialize planning as something generic and focus on the hard realities of execution. Others advocate the basic principle that a better plan leads to improved execution. In typical Canadian fashion, I would argue that the answer is somewhere in the middle.
Where the Money is
The first premise I want to establish is that planning is where the money is. While auditing freight bills more efficiently or having more effective ways to communicate with carriers both absolutely add value, the bulk of the value proposition for any transportation initiative lies in the ability to plan better. Whether through improved consolidation, increased asset utilization or just better carrier and equipment selection; the math clearly establishes the importance of effective planning. And the more sophisticated the planning strategies that can be implemented, the more potential value that can be achieved.
Point and Counter-Point
The counter argument for focusing on effective transportation planning is that the best plan can fall apart when faced with the realities of execution (unavailable capacity, limited dock space, order variability, etc.). The flaw in this contention is that it assumes that effective transportation planning doesn’t consider execution constraints. Unfortunately, this is an issue with many transportation solutions.
The ideal solution will consider active execution-level constraints (dock capacity, throughput, available carrier and fleet capacity, etc.) concurrently during the planning process. While not everything can be anticipated upstream, the more that can be will enable more complex strategies, incremental value, and less user intervention.
Iteration and Postponement
In addition to the need to consider multiple active constraints during the planning process, additional challenges include the degree to which those constraints change during the time lag between the planning and execution processes and the missed opportunities due to a lack of visibility into new orders and order changes. To effectively deal with these challenges, a transportation solution has to move beyond the traditional “point in time” optimization approach, to a more dynamic planning approach in which plans and execution are continuously adjusted as needed based upon new orders, order changes, and dynamic constraints within the network. This, of course, requires the creation of true interoperability between planning and execution.
The benefits of this approach are multifold. First, it reduces the latency between the planning and execution domains which subsequently reduces the variability between the two and creates real value. Second, it creates a notion of resiliency through the ability to sense and respond to inevitable order variability and disruption. Lastly, it provides the opportunity to create consolidation and utilization opportunities that were previously not possible.
Do it Right
In the end, it’s not about planning or execution. In the world of transportation, the two are intertwined. To achieve maximum value, solutions must bridge the gap. They must allow multiple constraints to be considered during the planning process. Planning should be dynamic, rather than static. And planning and execution must interoperate to deal with order and constraint variability over time.
As Vice President of Global Logistics at JDA Software, Fabrizio Brasca (@FabBrasca) is responsible for developing transportation and logistics strategies across all industry verticals, strengthening executive-level relationships with JDA’s key customers and prospects, and advising companies on best practices. He holds an Honors Bachelor of Mathematics co-op degree with a specialization in business and information systems from the University of Waterloo, Waterloo, Ontario. The author invites comments or questions from readers. He can be reached via email at fab.brasca@jda.com.
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