East Coast pool company dives into outsourcing with process simulation

Imagine running an engineering shop where 85% of the work lands in just six months of the year. That was the reality for one East Coast pool company, and the seasonality was only part of the pressure. To stay competitive, the company also committed to turning around every design within 24 hours of receiving an order. The result was a steep set of challenges:

• Sales varied every day, yet the 24-hour turnaround stayed fixed.
• Engineering work came in three levels of complexity, and each higher level required greater skill.
• During peak season, the existing engineers were exhausted, with some working more than 70 hours a week.
• The industry is cost conscious, so lower costs mean a better chance of survival.
• Finding engineering talent willing to work odd shifts is difficult.
• Finding engineers willing to work only half the year is difficult.

The company weighed several ideas, and one of the strongest was outsourcing part of the work to India. They identified five major advantages to using Indian engineers to solve the resource shortage.

First, cost savings. Indian engineers generally earn lower salaries than their counterparts in developed countries, so companies can reduce labor costs by outsourcing there. In this case the cost per engineer fell by more than 50% once space, hardware, and benefits were factored in. Second, access to skilled labor, since India has a large pool of highly qualified engineers. Third, productivity gains from time zone differences that let work continue around the clock, which directly helps deliver designs on time. Fourth, the flexibility to scale the team up or down as demand changes. Fifth, a strong tradition of engineering education with a focus on quality and attention to detail, which helps keep outsourced work to a high standard.

With both the appetite and the access to use outsourced labor, the company defined the inputs it needed to solve for, starting from the number of seasoned engineers it wanted to keep full-time at the home office. The parameters were as follows.

Solve for the least cost by altering the number of each type of engineer.

Given the requirements:

• Return the completed design in less than 24 hours, 95% of the time or higher.

Given the inputs:

• Quantity of arrivals (per day of the week and by hour of the day).
• The percentage of type 1, type 2, and type 3 engineering requests.
• The cost of each engineer type (A, A0, A1, A2, A3, and so on).
• The time needed to solve each engineering request.

Engineers:

• Home office engineers, full-time, maintained year-round.
• Quantity: X, Y, 2.
• Cost: A, B, $45/hr.
• Type, home office permanent: type 1 year-round, type 2 year-round, type 3 year-round, with the ability to train other engineers at all three levels.

Seasonal engineers:

• Quantity: X0, Y0, Z0.
• Cost: A0, B0, C0.
• Type, home office seasonal: type 1, type 2, type 3 seasonal.

Same shift as the home office:

• Quantity: X1, Y1, Z1.
• Cost: A1, B1, C1.
• Type, overseas on the home office shift: type 1, type 2, type 3 seasonal.

Shift 2:

• Quantity: X2, Y2, Z2.
• Cost: A2, B2, C2.
• Type, overseas on shift 2: type 1, type 2, type 3 seasonal.

Shift 3:

• Quantity: X3, Y3, Z3.
• Cost: A3, B3, C3.
• Type, overseas on shift 3: type 1, type 2, type 3 seasonal.

The goal was to solve for each quantity (X, X0, X1, X2, X3, and the rest) that delivered the lowest total cost.

Creating a process model to evaluate the problem

Process simulation turned out to be a powerful way to understand and improve a genuinely complex staffing problem. The company used it to work out how many people it needed to complete all of its tasks, which mattered because the work spanned different levels of complexity and widely varying task times.

The approach followed a clear sequence. First, the team defined the process and collected data on how long each task took and what resources it required. Next, they used ProcessModel to build a digital model of the process, including every task, resource, and supporting element. They then ran the simulation and used the results to adjust the model. Finally, they applied optimization to find the best staffing mix and confirm they could hold the 24-hour turnaround. Process simulation proved to be a real turning point for the company.

Other companies that outsource engineering services to India

Management was initially cautious about outsourcing, until they realized that some of the largest and most productive companies in the world were doing the same thing for the same reasons. A small sample:

1. Microsoft
2. Ford Motors
3. CISCO
4. Amazon
5. Google
6. IBM
7. American Express
8. Dell
9. Hewlett Packard (HP)
10. AT&T

Seeing companies of that caliber rely on outsourcing made the decision far easier.

At the deep end of the pool

Process simulation is a strong tool for understanding and improving even the most tangled processes. It is especially useful when you have a large number of tasks to manage, a range of complexities to handle, and task times that vary from one job to the next. It helps you determine how many people you need and what they will cost. For any team working through complex processes and trying to make confident, well-grounded decisions, process simulation is hard to beat. To see how it could fit your own operation, explore what ProcessModel does.