Watch this presentation from the 2017 E Source Forum Conference given by Huntsville Utilities on how they rebuilt customer relationships and prioritized customer experience (CX). ProModel played a role in this turnaround as mentioned starting at the 6:40 mark.
Speaking of Huntsville Alabama – We will be at the annual AUSA Global Force Symposium and Expo at the Von Braun Center in Huntsville, AL Mar 26-28. Stop by ProModel booth #200 and check out our latest products and releases.
CHALLENGES
The mission of the Office of Probation for any state in the US is to provide seamless services to the victims, communities, offenders, and courts of that state. The administration of probation is a complex and ever-changing process. Recently a state probation organization’s Sr. IT representative contacted ProModel looking for help understanding, analyzing, and improving its probation office processes. Its systems and infrastructure needed to be updated, but before that could begin they needed to understand the “As Is”condition of its processes and all that was involved.
During the project, the US Justice Department planned to release about 6,000 inmates early from prison—the largest one-time release of federal prisoners — in an effort to reduce overcrowding and provide relief to non-violent drug offenders who received harsh sentences over the past three decades. The inmates from federal prisons nationwide were set free between Oct. 30 and Nov. 2 of the same year. This followed action by the U.S. Sentencing Commission—that reduced the potential punishment for future drug offenders from the previous year and then made that change retroactive. The panel estimated that its change in sentencing guidelines eventually could result in 46,000 of the nation’s approximately 100,000 drug offenders in federal prison qualifying for early release.
It became important to also determine the impact of this action on this state’s probation services and local jail systems.
OBJECTIVES
The Probation Office was interested in using Predictive Analytics to analyze the as-is condition of its processes:
• Where might there be any bottlenecks or constraints?
• Assess the impact of the new law on the probation office workload and the local county jail occupancy rate.
• Where could other improvements be made?
SOLUTION
In order to model and simulate the current processes, they needed to be fully understood and documented. ProModel’s resident lean expert was brought in to work with Office of Probation personnel to create a quick high-level Process Simulator Model of the voucher process. Together in a room with four or five probation team employees, ProModel documented in Microsoft Visio, the ins and outs of the voucher system. When this model was built and simulated, the results so closely resembled the realities of the current process and resource utilization of certain team members, that the go-ahead was given to proceed to a complete model of the voucher process.
The entire probation process was modeled and simulated by several experienced members of the ProModel consulting team, along with Office of Probation personnel. The following processes models were completed:
1. Voucher process
2. Juvenile probation process
3. Adult probation process
4. Problem-solving court process
One Part of the Overall Model
VALUE PROVIDED
As part of the law change, convicts who are guilty of certain felonies will spend part of their sentence in probation instead of spending all of it in prison. These felons are at a higher risk level than the current average probationer, and will likely cause a disproportionate workload increase on the probation officers as well as take up county jail space should custodial sanctions need to be implemented.
This simulation model clearly communicated that the current processes and resources available were not adequate to handle the predicted increases in probation candidates. Several areas of the process were evaluated for improvements and the model was used to validate several proposed IT enablers and Lean modifications.
Situation
Hospitals face increasing pressure to reduce costs while continuing to provide quality care to patients. The operating room, one of the most difficult and expensive wings to manage, must run efficiently in order to avoid unnecessary costs. Hospital managers often implement case cart systems which create a centralized materials management system. Case carts carry medical supplies within an operating room. The case cart system ensures that the staff obtain the necessary materials and instruments in time for their upcoming procedures (1. Making a Case for a Case Cart System).
This study was undertaken to test the impact of implementing a case cart system on the OR process in a client’s newly configured OR Suite. The impact was determined by patient delays in any stage of the OR process that was attributable to case carts.
Objectives
The client wanted a predictive analytic model which would help answer the following key questions:
Results
The model outputs suggest that maximum patient throughput could increase by 38% in 6 months with the implementation of a case cart system. The following additional insights were also gained from the study.
Maximum System Volume
At these higher volumes both POCU and PACU spaces become limiting factors.
![SS-HC-Case-Carts-Improve-Patient-Throughput[1]](https://promodel.files.wordpress.com/2017/08/ss-hc-case-carts-improve-patient-throughput1.jpg?w=652)
Solutions
Defining the Process
A spreadsheet defines the “patient flow” process as it relates to patient type, location sequence, staffing utilized and task times. The spreadsheet “Staff” columns work together to schedule the first staff member required for each procedure step. Some procedure steps have the staffing flexibility of allowing an alternate position to “back up” the primary position. Times for each process step are defined in the Process spreadsheet using triangular distributions which account for work time as well as wait time.
Cases Defined by Historical Data
The medical center provided historical data such as original date of surgery, the service which performed the procedure, the surgeon assigned to the case, and the OR assignment.
Block Schedule
Operating room schedules are entered onto a spreadsheet. The model solution places the previously entered cases into schedule blocks and continues through the process until the patient completes the surgical experience.
Staffing
The simulation model uses the data on a worksheet to perform scheduling tasks by staff person, primary or secondary resource group, and times that shifts begin and end.
Sterile Processing Department Input Worksheet
Data entered into the Sterile Processing Department (SPD) worksheet is matched with the procedure from the “Cases” worksheet. The model solution will produce results indicating the turn around time on the carts, and will predict the performance of SPD.
Location Assignments
A worksheet defines the primary and secondary uses of each location in the model.
Procedure Requirements
Three triangular time distributions are used on this model (Min / Mode/ Max) to represent procedure times for all clinic procedures. The first triangular is used for the procedure itself. The second triangular is used for room turnover. The third and last triangular distribution is the set-up time occurring before the next procedure is performed.
Room Restrictions
“Special Restrictions” may apply for up to five ORs. These restrictions define the rooms that may be used
by each service. An entry of “999” indicates that “any” OR may be used.
Services Using Case Carts Chart
Services using carts receive a “1” in corresponding column while services not using case carts remain blank.
References: ![SS-HC-Case-Carts-Improve-Patient-Throughput[2]](https://promodel.files.wordpress.com/2017/08/ss-hc-case-carts-improve-patient-throughput2.jpg?w=652)
“1. Making a Case for a Case Cart System.” Making a Case for a Case Cart System – Research – Herman Miller. Herman Miller Inc., n.d. Web. 14 June 2017.
Keith Knudsen ProModel Project Manager
Over the past 29 years, ProModel users across a spectrum of industries have demonstrated the value that modeling can bring to an organization. Just a few examples include:
Increasingly, however, ProModel customers are looking to extend these benefits by integrating their models with other IT systems to develop web-based decision support tools. These model-based tools utilize a ProModel engine on a server, read in live data and utilize ProModel simulation and optimization capabilities to provide forecasting, automated scenario exploration and prescriptive suggestions.
Whether created by ProModel consultants or in-house analysts, a good model (traditional or integrated) is composed of several key elements as shown below.
Custom integrated model(s) take all of the above, integrate it with live data and makes its power available in a live, web-based format so that tactical decision-makers at all levels of the organization can utilize it. In a live integrated environment, prescriptive analytics can be provided daily or even hourly in support of near real-time decision-making.
ProModel has now developed about half a dozen custom predictive prescriptive platforms with direct integration of the ProModel server into the customer’s operational IT environment. Examples include:
AREAS capacity planning capability was featured in the Signal Magazine on page 2. The article states that Ingalls Shipbuilding estimated a potential annual cost savings of just under $1M from the use of this tool.
Benefits of a custom integration of ProModel include:
Contact saleshelp@promodel.com if you are interested in learning more about custom model integration.
Steve Courtney, ProModel Sr. Consultant
I have several years of experience in supply chain and logistics modeling helping clients who have large warehouses and distribution centers. These models are often very large (thousands or tens of thousands of locations), which can be very time consuming to model. I’ve found the old adage to be very true: “Necessity is the Mother of Invention”, so I developed a ProModel App that is used from within AutoCAD which enables us to quickly build the graphical portions of the model using OLE automation. This capability is also very useful when experimenting with several different layouts.
The types of Warehouse / DC modeling questions that can be answered include:
I recently gave a webinar on this topic which you can view here
The requirements for using the app include:
If you would like to discuss this further, or have other ideas that can help us all improve warehouse and distribution center modeling, please comment below. Thanks and Happy Modeling!
Thanks, Steve Courtney
The automotive industry is likely to change more in the next 10 years than it has in the previous 50. It seems like in so many industries today including technology, entertainment, and consumer products, change at a very rapid pace. The auto industry is by far no exception. There are many new entrants into car making, add to that self-driving vehicles, electric cars, and car sharing just to name a few. All these factors are providing increased competition. Not to mention the rapidly fluctuating price of gasoline. With instability in the Middle-East and increased oil production in the US and other parts of the world, who knows how that may change in the next 6 months. There is no doubt that reacting quickly and strategically to these rapid demand shifts will be an absolute priority for auto leaders in 2016.
Simulation is a tool that can help automakers accommodate these rapid changes and develop scenarios for planning for the uncertainties that may occur.
Consider that a US plant reduced its work force by 20% in 2010 during the recession. Not only that, but floor space has been re-arranged to accommodate those reductions. Now in this post-recession period the demand for vehicles from this plant is increasing rapidly. How do you meet that demand with the existing workforce? Can you build the number of vehicles necessary without moving lines or cells around again and hiring more workers? If you do hire, which positions, how many, and on what shifts do you need more FTEs? Simulation can help you make these decisions more confidently. Here are some ways in which it has already been done.
A large automotive component manufacturer experienced difficulties reaching a desired line speed. The operation involved mating a set of tires with rims for multiple manufacturers. The line was consistently under producing and management wanted the problem solved now! Given the interactions between the various parts of the line, it was difficult to assess which component was the actual bottleneck. Only a limited number of things could be changed, so the objective was to find what modification to the line was possible to achieve improved speed in a short period of time with as little capital investment as possible. The following modifications were tested:
The largest gain in line rate required three changes: the time between rim arrivals was reduced from 23 seconds to 16 seconds, the elimination of switch-outs and the lengthening of tire feed spur lengths.
These modifications allowed the client to get to the desired line rate and the model was developed and results were submitted within 5 days. View the video for a quick sample of the model.
Check out one of our success stories about another auto manufacturer: Tofus-FIAT Realizes 48% Reduction in WIP with ProModel Simulation. This solution story is available among many from our online library. Many solution and model videos are also available on our YouTube Channel. If you would like to learn more about ProModel solutions contact us.
Charles Harrell, Founder ProModel Corporation
Last month we lost a long-time member of the ProModel family and, for many of us, a beloved friend. Following a sudden incident of heart failure while working out in the gym, Rob Bateman passed away on October 11th 2015. We at ProModel will remember him as a warm, energetic, impassioned leader and friend whose life was devoted to the pursuit of excellence and selfless service. His absence will continue to be profoundly felt in the months and years to come.
I first met Rob just over 25 years ago when he was doing graduate studies at BYU. He took a simulation class from me and I could tell he was excited about the potential benefits of simulation. So after completing a stint with the US state department as a foreign-service officer in 1990, Rob began working as a ProModel distributor. With his international background and grasp of simulation, Rob eventually become the Vice President of International Operations and later established an independent company (Dynamisis A.G.) for directing all international operations for ProModel.
Robert Bateman
(April 4, 1958 – October 11, 2015)
Rob was an extraordinary individual with remarkable talents. He was one of those individuals who was always on-the-go and seemed to cram more into one day than most of us manage to accomplish in several days. At the same time, he maintained a zest for life and could frequently be seen buzzing around in his sports car with his signature driving cap or biking into work in his cycling shorts and helmet.
Here are a few of the many talents Rob displayed:
Here are a few memories related by some of the distributers who worked with him.
A Distributor in Germany and Austria relates, “On my first trip to Utah to visit with Rob as a new ProModel rep, I had the feeling I was meeting with an old friend. I was impressed by his hospitality and the time that he gave me.”
A Brazilian distributor recalled meeting Rob the first time 21 years ago and thinking to himself, “Who is this guy who can conduct a meeting with high level business leaders, comfortably use legal and business terms in both German and English and then turn around the following day and teach a simulation course in Spanish to a group of engineers. How can one person have so many skills?”
As another of his co-workers commented, “I’ve been in rooms with him teaching and negotiating with Nigerians, Germans, Japanese, Brazilians, Mexicans, and more. No matter the nationality, Rob could relate and connect. He was confident, knowledgeable, and personable.”
On a personal note, one co-worker related: “This past year Rob joined the cycling team that I belong to called Team C4C (“Cycle for Cure”). The team was formed to raise money for health-related charities such as the Huntsman Cancer Center and the National MS Society. Rob immediately identified with the purpose of the group and quickly became one of the strongest riders on the team.”
This same co-worker related how Rob was instrumental in helping him complete a grueling ‘Ultimate Challenge’ cycling event saying, “I will always cherish a picture I have of Rob and me crossing the finish line together at Snowbird after riding 100 miles and climbing 10,000 feet in one day. I could not have made it without his encouragement along the way.”
For all those who have been influenced by his exemplary life, Rob will always be remembered as a leader, mentor and friend. Perhaps it is fitting that he pursued a career in simulation modeling since he seems to have understood the impact that models can have, not only on organizations, but on the people around him. Those who knew Rob, know that he was a model of the best that a human being can be, and for that he will always be remembered.
Jennifer Cowden – Sr. Consultant
It was recently announced that the U.S. Justice Department is planning to release 6000 inmates near the end of the month due to new sentencing policies for non-violent drug-offenders. Most of the prisoners will be placed in half-way houses and drug rehab centers as part of the “largest one-time release of federal prisoners” in U. S History, which begs the question: are these rehabilitation centers going to be ready for this sudden influx?
One state has had a similar law change recently and is rightly concerned about the impact that the new sentencing structure will have on the probation system and ancillary support services. ProModel consultants have been working with this state’s Administrative Office of Probation to build a series of models around different aspects of the probation system. The previous phase model studied the movement of youths through the juvenile probation system, while the model discussed in the video below addresses the adult probationer population.
In addition to gaining insight into bottlenecks in the process, the Probation Office was interested in using Predictive Analytics to assess the impact that the new law will have on the probation office workload and the local county jail occupancy rate. As part of the law change, convicts who are guilty of certain felonies will spend part of their sentence in probation instead of spending all of it in prison. These felons are at a higher risk level than the current average probationer, and will likely cause a disproportionate workload increase on the probation officers as well as take up county jail space should custodial sanctions need to be implemented. The model will be used to help quantify the increased demand so that the appropriate adjustments can be made ahead of time.
The next steps for this model is to combine it with the juvenile model in order to predict more accurately the demand on shared services and resources.
Dale Schroyer – Sr. Consultant & Project Manager
I generally find that in healthcare, WHEN something needs to happen is more important than WHAT needs to happen. It’s a field that is rife with variation, but with simulation, I firmly believe that it can be properly managed. Patient flow and staffing are always a top concern for hospitals, but it’s important to remember that utilization levels that are too high are just as bad as levels that are too low, and one of the benefits of simulation in healthcare is the ability to staff to demand.
Check out Dale’s work with Robert Wood Johnson University Hospital where they successfully used simulation to manage increased OR patient volume:
About Dale
Since joining ProModel in 2000, Dale has been developing simulation models used by businesses to perform operational improvement and strategic planning. Prior to joining ProModel Dale spent seven years as a Sr. Corporate Management Engineering Consultant for Baystate Health System in Springfield, MA where he facilitated quality improvement efforts system wide including setting standards and facilitating business re-engineering teams. Earlier he worked as a Project Engineer at the Hamilton Standard Division of United Technologies.
Dale has a BS in Mechanical Engineering from the University of Michigan and a Masters of Management Science from Lesley University. He is a certified Six Sigma Green Belt and is Lean Bronze certified.
NEW! ProModel’s Patient Flow Solution:
ProModel Healthcare Solutions:
Hospitals are currently under intense pressure to simultaneously improve the effectiveness and efficiency of healthcare delivery in an environment where operating costs are being reduced, downsizing and consolidation is the norm, and cost for care is increasing while revenue is decreasing. At the same time the systemic effects of peak census and varying demand on patient LOS are creating capacity issues and unacceptable patient wait times…leading to a major decline in patient satisfaction.
The amount of proposals to enhance a hospitals quality care are as numerous as the healthcare professionals dedicated to the cause. What hospitals need however is the ability to quickly and accurately evaluate the impact of those various operational proposals and to experiment with system behavior without disrupting the actual system – and ProModel’s simulation technology is allowing them to do just that.
The predictive analytic capability of ProModel simulation will allow healthcare professionals to test assumptions and answer those patient flow “what if” questions in a matter of minutes and days, not weeks and months. Simply put, it’s providing a decision support system to assist healthcare leaders in making critical decisions quickly with a higher degree of accuracy and confidence.
Simulation will also help healthcare staff quickly identify room availability and recognize high risk patient flow bottlenecks before extreme problems occur. This invaluable knowledge will then lead to reductions in patient wait times and LOS, avoid unnecessary re-admissions and costly expansions, and most importantly – increase the overall quality of service and patient satisfaction.
ProModel 