Download PDF
Enabling Strategic Vision Through Network Design
Technology Category
- Analytics & Modeling - Predictive Analytics
- Functional Applications - Transportation Management Systems (TMS)
- Functional Applications - Warehouse Management Systems (WMS)
Applicable Industries
- Healthcare & Hospitals
Applicable Functions
- Logistics & Transportation
- Warehouse & Inventory Management
Use Cases
- Fleet Management
- Supply Chain Visibility
- Warehouse Automation
Services
- Software Design & Engineering Services
- System Integration
The Challenge
Over the past decade, the specialty healthcare distributor had undergone substantial growth by expanding existing product lines and acquiring complementary businesses. The current single point manufacturing and distribution footprint had become stretched as the organization was supporting over two-thousand end customer locations across North America. This further manifested in their primary East Coast distribution center which suffered from significant capacity constraints. Also, on the West Coast, the organization felt pressures of both increased distribution cost and expedited customer delivery expectations. In addition, two factors added complexity to the distribution network. First, many products had inherently different manufacturing and distribution requirements (i.e. lead-time, manufacturing processes, etc.). Second, different customer types had unique demand profiles for specific items (i.e. order sizes, shipping times, etc.).
About The Customer
Houlihan Lokey is a global investment bank with expertise in capital markets, financial restructuring, and strategic consulting. They were commissioned by one of North America’s leading healthcare distributors to help revitalize their distribution operations. The healthcare distributor had undergone substantial growth over the past decade by expanding existing product lines and acquiring complementary businesses. They were supporting over two-thousand end customer locations across North America, which led to significant capacity constraints in their primary East Coast distribution center and increased distribution costs and expedited delivery expectations on the West Coast. The distributor's network was complex due to the varying manufacturing and distribution requirements of different products and the unique demand profiles of different customer types.
The Solution
Given these changing variables, a new fit-for-purpose distribution network needed to be developed. The anyLogistixTM platform was chosen by Houlihan Lokey Strategic Consulting to be the primary engine for designing a new distribution network due to the software’s robust modeling capabilities and its ability to account for the project’s various complex supply chain requirements. Furthermore, the combination of a straightforward user interface, extensive documentation, and a dedicated customer service team gave Houlihan Lokey confidence that the anyLogistixTM platform would be the best fit solution. To renovate the distribution network, the following objectives were established: reduce variable operating costs (i.e. transportation, handling), improve service levels with a focus on shipping times, and limit the amount of capital investment (i.e. new facilities). The model designed by Houlihan Lokey utilized the distributor’s transactional records over the prior year to represent demand in the model. This included data from all the organization’s current distribution facilities located in the US and Canada. To plan for future distribution requirements, various growth scenarios and supply acquisition volumes were modeled within the anyLogistixTM platform to target specific geographic regions and product lines. Leveraging the anyLogistixTM “Greenfield Analysis” network design experiment, Houlihan Lokey was able to determine the optimal distribution footprint considering multiple network configurations including point-to-point and hub & spoke distribution. The anyLogistixTM platform was able to incorporate the organization’s requirement to allow certain customers and products to be serviced by specific distribution facilities. This was vital as it allowed the company’s complex customer and product requirements to be fully considered throughout the network design process. In the end, the anyLogistixTM platform enabled the creation of several distinct design scenarios which were then ranked according to the objectives laid out for the distribution network design project.
Operational Impact
Quantitative Benefit
Related Case Studies.
Case Study
Hospital Inventory Management
The hospital supply chain team is responsible for ensuring that the right medical supplies are readily available to clinicians when and where needed, and to do so in the most efficient manner possible. However, many of the systems and processes in use at the cancer center for supply chain management were not best suited to support these goals. Barcoding technology, a commonly used method for inventory management of medical supplies, is labor intensive, time consuming, does not provide real-time visibility into inventory levels and can be prone to error. Consequently, the lack of accurate and real-time visibility into inventory levels across multiple supply rooms in multiple hospital facilities creates additional inefficiency in the system causing over-ordering, hoarding, and wasted supplies. Other sources of waste and cost were also identified as candidates for improvement. Existing systems and processes did not provide adequate security for high-cost inventory within the hospital, which was another driver of cost. A lack of visibility into expiration dates for supplies resulted in supplies being wasted due to past expiry dates. Storage of supplies was also a key consideration given the location of the cancer center’s facilities in a dense urban setting, where space is always at a premium. In order to address the challenges outlined above, the hospital sought a solution that would provide real-time inventory information with high levels of accuracy, reduce the level of manual effort required and enable data driven decision making to ensure that the right supplies were readily available to clinicians in the right location at the right time.
Case Study
Gas Pipeline Monitoring System for Hospitals
This system integrator focuses on providing centralized gas pipeline monitoring systems for hospitals. The service they provide makes it possible for hospitals to reduce both maintenance and labor costs. Since hospitals may not have an existing network suitable for this type of system, GPRS communication provides an easy and ready-to-use solution for remote, distributed monitoring systems System Requirements - GPRS communication - Seamless connection with SCADA software - Simple, front-end control capability - Expandable I/O channels - Combine AI, DI, and DO channels
Case Study
Driving Digital Transformations for Vitro Diagnostic Medical Devices
Diagnostic devices play a vital role in helping to improve healthcare delivery. In fact, an estimated 60 percent of the world’s medical decisions are made with support from in vitrodiagnostics (IVD) solutions, such as those provided by Roche Diagnostics, an industry leader. As the demand for medical diagnostic services grows rapidly in hospitals and clinics across China, so does the market for IVD solutions. In addition, the typically high cost of these diagnostic devices means that comprehensive post-sales services are needed. Wanteed to improve three portions of thr IVD:1. Remotely monitor and manage IVD devices as fixed assets.2. Optimizing device availability with predictive maintenance.3. Recommending the best IVD solution for a customer’s needs.
Case Study
HaemoCloud Global Blood Management System
1) Deliver a connected digital product system to protect and increase the differentiated value of Haemonetics blood and plasma solutions. 2) Improve patient outcomes by increasing the efficiency of blood supply flows. 3) Navigate and satisfy a complex web of global regulatory compliance requirements. 4) Reduce costly and labor-intensive maintenance procedures.
Case Study
Harnessing real-time data to give a holistic picture of patient health
Every day, vast quantities of data are collected about patients as they pass through health service organizations—from operational data such as treatment history and medications to physiological data captured by medical devices. The insights hidden within this treasure trove of data can be used to support more personalized treatments, more accurate diagnosis and more advanced preparative care. But since the information is generated faster than most organizations can consume it, unlocking the power of this big data can be a struggle. This type of predictive approach not only improves patient care—it also helps to reduce costs, because in the healthcare industry, prevention is almost always more cost-effective than treatment. However, collecting, analyzing and presenting these data-streams in a way that clinicians can easily understand can pose a significant technical challenge.