Our fundamental goal is to identify, quantify and prioritize cost takedown opportunities in hospital supply chains. This requires a determination of both current supply chain costs and supply chain costs under each action proposal. You will probably also want to know the "best achievable" supply chain costs unless your action proposals target these.
Here are a few of the considerations we typically address in our analyses:
Cost takedown opportunities must first of all be feasible. Physician preference items, for example, can generate very large supply chain costs but are extremely hard to tackle in practice. Doctors often regard their own list as vital to the quality of care they can provide. Moving them toward a standard list is a long-term and slow process at best. Big dollars are involved but this is not usually an opportunity in any short-to-medium time frame.
The largest cost takedown opportunities should be obvious but often they are not. They rarely stand out because of clear over-staffing or excessive inventory. In fact, they may be quite difficult to discover because they are deeply buried within the overall hospital administrative expense.
When you look carefully at the supply chain related activities in a hospital, you find these activities in a surprisingly number of jobs. Nurses, for example, can spend 10% or more of their time chasing supplies. This is typically a very large but virtually invisible cost item. Helping nurses reduce the time they spend on supplies can lead to substantial savings.
We normally look for a way to focus our efforts where we can get the highest return for that effort. It is common to see huge laundry lists of "issues" to address without any clear and data-grounded means of prioritization.
Spreading limited resources across too broad a range of initiatives typically produces weak results. You need to have your opportunities (or "issues", if you prefer) stacked in order of probable return. This stack order must reflect initiative costs and time required relative to the net cost savings expected. Sometimes an ROI metric is unavoidable.
You may well find that a number of quite simple actions appear at the top of your stack — not those with the largest savings but those that are virtually costless and easy to implement. Those with the largest savings potential may be well down in your stack — costly and time-consuming to implement. Chief among these latter opportunities are those requiring system (IT) changes.
Focusing your actions in this manner can also have a valuable motivational outcome. Nothing energizes people more than some early successes. These can help make the more difficult efforts to come seem at least a little easier.
Our simulation methodology is designed pinpoint the largest opportunities. Sometimes the main opportunities are locations with supply chain process weaknesses. Other big opportunities may be found within the overall supply chain process itself — in unnecessarily complex or unnecessary duplication of steps.
We have found situations with too-frequent ordering, a result of insufficient storage space at point-of-use locations.
We have found storage locations dominated by slow and non-moving items, leaving inadequate space for high-volume items.
We have found many instances of unnecessarily duplicated inventory, such as the same item being stocked at several locations on the same floor.
The simulation modeling approach also provides a means of tracking progress and results of action initiatives. As each such initiative is implemented, the related system variables used in the model should begin to show improvement.
Action produces results — some good, some not so good. Among the good outcomes will be a few that are truly big wins. Even better, they may be generally applicable. This brings up the question of ... Sharing Best Practices ...
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A common approach to finding opportunities for cost takedown is activity-based costing (ABC), a process-oriented version of traditional cost accounting. This works but can be very costly to do in any large organization.
The ABC approach is not only quite costly but difficult to use for what-if analyses. ABC spreadsheets are rarely designed for simulation purposes.
Our models are high-level activity-based but are designed specifically for simulation of possible action initiatives and optimization analyses. They tend to be less detailed and precise than many ABC analyses but this makes our models work better in simulation runs.
In the end, you want to know how best to address a cost opportunity. Sometimes the right approach is obvious but in many cases it is not. This is particularly true for storage space optimizations.