At first glance, the answer to this may seem obvious -- we are optimizing for OUR benefit, to improve OUR profits and OUR market share, etc. And this is certainly true, whether directly or indirectly. But in the LML, the strategies and tactics for achieving these goals vary depending on the role your company plays. For example, a shipper/importer may be focused on reducing transportation cost per unit of product, while his intermediate service provider (forwarder/broker) is trying to increase revenue and yields, and the carrier is concerned with return on assets. At face value these objectives are in direct conflict with one another, making optimization less straightforward than it first appeared.

There is no single answer to the question, "for whom are we optimizing?" In fact, the real answer is that we want to optimize for all parties simultaneously -- but those who seek long term competitive advantage will focus on the shipper/importer's needs first. Why? Because theirs is the first procurement dollar spent in the LML model. That dollar is then spent by the intermediary to procure vessel space and then by the asset based carrier to procure vessel capacity -- a classic demand chain. And as we learned last issue, the procurement function is the strategic componenent of the LML.

A simple case

In the above example, the shipper/importer seeks to reduce transit time and increase load factor. If that optimization strategy is successful, the short term savings will come directly out of the pocket of the intermediary as volumes from that customer drop. Many service providers choose to focus short term on this built-in disincentive, cooperating in shipper optimization solutions reluctantly or not at all. But the more savvy players take a longer view -- always keeping in mind that the LML is a cycle that will enable them to leverage their performance on behalf of their customer to competitive advantage in the next round, and the next, etc.

For example, the intermediary might enter a gain-sharing arrangement with the shipper to enjoy some of the optimization benefits. While this will not be dollar for dollar, the impact will be significant on the net revenue line because there is no off-setting cost of transportation. The greater benefit over time for the intermediary will be in customer retention and increased market share as more shippers procure their services in order to reap similar benefits.

Keeping the perspective issue in mind, we will examine this question primarily from the shipper/importer's point of view. As with the previous question, there is no single answer on what to optimize. But all optimization efforts will focus on any combination of these three general components:

• Time
• Money
• Quality

The supply chain requirements of the shipper/importer's particular industry will determine which of these three areas to emphasize, but all must be considered. At the most general level, optimization means finding the best possible balance between the three elements in order to achieve business objectives, be they profitability, market share, return on assets, shorter cash to cash cycle, etc.

In the LML construct, this means we could be optimizing one or several of these key performance areas:

• Inventory levels
• Average transit time duration
• Transit time variability
• Transportation cost per unit
• Warehousing/postponement cost per unit
• Outsourcing strategies
• Facility locations
• Sourcing decisions
• Capacity
• Order fulfillment
• Claims
• Returns
• Billing timeliness and accuracy

A deeper look into optimizing each of the above is outside the scope of this artical and whole libraries have been written on the subject. For now, it is important to understand that a sound optimization initiative requires a clearly defined scope that is in line with business objectives.

Caution: One must bear in mind the inherent trade offs between many of the performance areas. Otherwise, it is easy to sub-optimize that which is IN SCOPE at the expense of that which is OUT OF SCOPE. For instance, 100% order fulfillment rates are easily attained if no consideration is given to inventory levels. Early recognition of these trade-offs will help ensure that the proper controls and measures are in place to prevent such "collateral damage." While looking at these trade-offs it is important to look at employee incentive compensation models to ensure that they are not rewarding sub-optimal agendas.

If time were no issue, optimizing almost anything would be a trivial matter. But in the ever accelerating business world, it has become our most valuable commodity (even in the face of soaring fuel prices). Goods move faster, the same dollar is spent and respent dozens of times on three continents in the time it used to take to spend it once, and customers have come to expect high goods availability in short delivery times.

Accelerated supply chain processes and transaction cycles force business leaders to make decisions more quickly and with less information than would be the case if they had more time. Paradoxically, this time crunch puts a higher premium on optimization while at the same time making it more difficult to achieve.

In our last issue on Procurement, we mentioned that the ideal time to optimize is at the point where procurement decisions are made. But limited time and information make this virtually impossible. However, the principle still stands -- the earlier in the LML optimization takes place, the more benefits to be derived in the remainder of the cycle. This principle should be a key driver in optimization strategies.

All optimization starts with timely and accurate information from which analyses can be developed. An axiom of 6 Sigma quality teaching says, "If you can't measure it, you can't improve it." Much of the required information is related to the key performance areas listed in the Scope section above. Notice that some of the information is related to cost, while the balance deals with performance and execution. This is an important distinction because both types of information are required for optimization, but they are gathered in very different ways.

As just shown, time limitations make it increasingly difficult to collect quality information to be properly anaylzed in support of sound decisions. Since time is perfectly limited, we must turn to our methods of gathering and analyzing information in order to fundamentally improve optimization benefits.

Fortunately, much of this information is generated through day to day planning and transactional activities -- especially the cost related information. The performance and execution information is not created naturally through the accounting process, so other systems must be employed to close the gap.

The challenge is to harness the information in a way that enables analysis and decision making virtually on-demand. This may sound "pie in the sky," but many companies have invested aggregate billions of dollars into ERP and data-warehousing solutions in search of such capability within the four walls of their enterprises. The problem is that these systems have a large "blind spot" when it comes to transportation and logistics activities beyond those four walls.

However, there are IT solutions available that make LML optimization with real time information and on-demand analysis & decision support viable.

The short answer is by overcoming the four key challenge areas covered above. More specifically, the first two relatively simple once we are aware of them:

• Keep proper perspective by focusing on the shipper/importer's supply chain requirements.
• Clearly define the scope and guard against "collateral damage."

But the last two -- Time and Information -- are not so easy. These require IT strategies and tools that complement and overcome the LML blind spots of ERP systems, while at the same time interfacing with these systems to share information.

There are now internet native solutions available that enable on-demand optimization from real-time information. Ideally, such a system will:

• integrate Optimization into the strategic Procurement process
• have execution and service performance measurement capabilities to ensure real time availability of information related to these activities
• be web-services enabled to maximize ERP and other system interfacing opportunities
• be scalable and configurable to your specific requirements, rather than requiring wholesale business process changes

While optimization seems an elusive goal given all of the challenges, the fact is that the tools are now available to make it a reality. Those who employ such tools -- especially to optimize procurement decisions -- will enjoy a competitive advantage throughout the entire Logistics Management Lifecycle.