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Why Optimization?

Why Optimization?. Ron Robertson rrobertson@commandalkon.com (205) 879-3282 x 2104. Session Objective.

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Why Optimization?

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  1. Why Optimization? Ron Robertson rrobertson@commandalkon.com (205) 879-3282 x 2104

  2. Session Objective • Today’s session will examine a new Command Alkon tool that can help Ready Mixed Concrete companies do their business differently. This decision making tool attacks the inefficiencies that threaten financial bottom lines. Hopefully our discussion will help you see how more profitable results are possible even with today’s economic climate.

  3. Looking for Results? Dispatch Optimization 2012 Customer Training & Technology Conference

  4. Are you looking for different results? On-TimeDelivery Fleet Utilization MarginalContribution Quantity per Driver Hour 15%+ 15%+ 20%+ 5%+ 10%+ 50%+ 15%+ 40%+ In YardbetweenTickets LastAt PlantuntilWashout InServicetoFirst Ticket OnJobWaiting

  5. What are your costs? Average Cost is $97.39/cy ($127.39 /m3) according to NRMCA Fixed costs: Fixed Delivery costs, Dispatch Salaries, Selling Costs, Admin

  6. Delivery Costs • Optimization can minimize • Driver Time • Start Up • Shutdown • Driver Overtime • Hours of Service • Round Trip Times • Job Wait Time • Plant Wait Time DELIVERY(18%) Cost per cubic yard (m) OKC reported a $2.00/cy ($2.61/m3) delivery cost savings. Harrison Ready-Mix saw a 21% decrease in non-productive time.

  7. Material Costs • Do your shippers know the cost of all mixes from all plants and consider it in each shipping decision? • Optimization considers constituent/mix costs in each and every recommendation. MATERIAL (52%) Cost per cubic yard (m) Titan American reported an almost 2% decrease in Material Costs with dispatch optimization. Another customer reported savings of $0.44/cy.

  8. Plant Costs • Optimization considers Plant costs in each dispatch decision to drive down cost per cy (m3) • Start-up costs • Hourly costs • Plant loading times PLANT(15%) Cost per cubic yard (m) Syar Concrete received an increase of 9.7% in quantity/man hour.

  9. Total Variable Costs • Optimization has the ability to impact all of your variable costs (Delivery, Material and Plant) • Up to 85% of your average cost/cy or m3 PLANT MATERIAL DELIVERY Cost per cubic yard (m) Optimization users have reported savingsranging from $1.00 -$1.90/cy ($1.31 - $2.50/m3).

  10. What is the Cost of Good Service? • How do your dispatchers currently evaluate the cost of good service in each dispatch decision? • Optimization can and does balance cost and service in each dispatch decision.

  11. What is Dispatch Optimization? • Evaluating and reevaluating a multitude of criteria to make sure each and every dispatch decision is based on your desired balance between cost and customer service.

  12. What is Dispatch Optimization? • Can a dispatcher consider all of these factors to make each and every decision? • Driver call-in rules • Union rules • Driver seniority • Plant opening times • Deadhead costs • Time of day • Order and customer priorities • Truck types required • Truck type exclusions • Truck attribute requirements • Truck attribute exclusions • Driver Overtime • Plant loading speeds • Mix loading variances • Mix cost • Job start times • Job start ranges • Linked orders • Plants down • Pre-loading requirements • Trucks unavailable and on tasks • Cost of being late • Escalating cost of being late • Cost of not recycling trucks to same job

  13. How does Optimization make a difference? Optimization allows dispatch personnel to stay many moves ahead!

  14. Dispatch Decision Complexity Job 4 Job 1 Plant A Job 5 Plant B Job 3 Job 2

  15. Average DispatcherTrucks go to and from the same order at the same plant. Job 4 Job 1 Plant A Job 5 Plant B Job 3 Job 2

  16. Good DispatcherTrucks are “juggled” across orders. Job 4 Job 1 Plant A Job 5 Plant B Job 3 Job 2

  17. Better DispatcherTrucks are “juggled” across orders and plants. 0 Job 4 Job 1 Plant A 0 Job 5 Plant B Job 3 Job 2

  18. Best DispatcherTakes into account all orders, plants, and drivers in all delivery areas, “juggling” to minimize time and overtime. 0 Job 4 Job 1 Plant A 0 Job 5 Plant B Job 3 Job 2

  19. Ideal Dispatcher Trucks and drivers return to their domicile plant taking into consideration time at the other plants. 0 Job 4 Job 1 Plant A 0 Job 5 Plant B Job 3 Job 2 In RealityHumans cannot think this many moves ahead.Plus the situation and solution keeps changing.

  20. OptimizationPerforms this analysis every second of your dispatch day. 0 Job 4 Job 1 Plant A 0 Job 5 Plant B Job 3 Job 2

  21. How does Optimization work? • All concrete distribution factors are assigned a “cost” • Delivery factors • Production factors • Service factors • These “costs” are all set by you

  22. How does Optimization work?

  23. How does Optimization work?

  24. How does Optimization work?

  25. How does Optimization work?

  26. How does Optimization work?

  27. Two Facets of Optimization • 1 - Capacity Plan/Resource Scheduling • Optimized scheduling of future Work • Plans the best schedule with the orders, trucks, drivers and plants available. • An order’s loads are scheduled for the best plant based upon material, delivery and customer service costs. Evaluating Cost of Customer Service Penalty ($) Lateness (minutes)

  28. Two Facets of Optimization • 2 - Realtime Schedule • Optimizing the current days ever-changing situation • Re-evaluates the entire days plan with each truck status or order change • Immediately produces new dispatch plan when incidents or emergencies arise

  29. Dispatch Optimization • How often is the dispatch day optimized? • About once every minute! Time since last optimized With optimization, your dispatch plan is evaluated for the perfect balance between cost and service about 480 times in an 8-hour day.

  30. What is needed? • Software • COMMANDconcrete (CS08) or Integra • Truck Tracking • Map Order Entry • Functioning Map Pages with travel times to/from each plant • COMMANDoptimize or INTEGRAoptimize • Hardware • Statusing system • GPS with Autostatusing preferred • High percentage of accurate and timely statuses • Dedicated Optimization server

  31. Optimization Interfaces • Highly Recommended Interfaces to use with Optimization • Time Clock • Driver Login enabled Signaling • Batch system interface with begin“Load” status • ScheduleCom voice-basedDriver Call-In system

  32. Optimization Background • Optimization has been in use in other industries for years.

  33. Optimization Background • ORTEC is our experienced optimization partner • Over 1,650 customers worldwide • Over 30 years of experience • Our optimization engine is “Ready Mix” specific

  34. Optimization Questions • How will the tool perform in my market? • How much more efficiency can we gain? • How will we measure improvement? • What kind of results can I expect?

  35. Customer Case Study Number of Plants/Trucks: 10/71 Delivery Area: North to South 80 miles, 15-20 miles wide, bordered by Everglades and Ocean Project Goals: Improve customer service, decrease delivery costs, increased dispatch efficiency, better incident handling, focus on the exceptions, material cost savings Optimization Analysis PROFILE Quarterly Averages

  36. Customer Case Study Number of Plants/Trucks: 10/71 Delivery Area: North to South 80 miles, 15-20 miles wide, bordered by Everglades and Ocean Project Goals: Improve customer service, decrease delivery costs, increased dispatch efficiency, better incident handling, focus on the exceptions, material cost savings Optimization Analysis cont. PROFILE Jan-Jun 4th Qtr Avg

  37. Customer Case Study Optimization Analysis Number of Plants/Trucks: 15/120 Delivery Area: 1,250 square miles serviced by 4 dispatchers Volume: 750,000+ cy per year Project Objective: With declining market demand and new entrants, need to increase/maintain competitive advantage. PROFILE Market Condition Change Market Condition Change Market Condition Change Previous year without Optimization compared to 1st year with Optimization

  38. Customer Case Study Optimization Analysis Number of Plants/Trucks: 10/85 Delivery Area: Metropolitan Area servicing approximately 1000 square miles (3 Southeastern US Counties) Project Goals: Improved Financial Performance (Marginal Contribution) PROFILE Feb – Aug of 2010

  39. Customer Case Study Anonymous Customer Optimization Analysis Number of Plants/Trucks: 4/60 Delivery Area: : Metropolitan Area servicing approximately 500 square miles (Southwestern US) Project Goals: Improve financial performance by reducing operating costs PROFILE Market Condition Change Market Condition Change Jan - Jun of 2010

  40. COMMANDperformanceMeasuremnet Managing Performance Understanding Information Effectiveness COMMANDperformance Efficiency Automating Transactions Collecting Data Oracle JDE SAP Oracle CommandSeries Apex Enterprise Applications

  41. COMMANDperformance Data Mart

  42. Optimization Compliance Reporting

  43. COMMANDperformance Delivery Cycle - Online

  44. Performance by Plant

  45. Performance by Driver

  46. Key Performance Indicators

  47. Optimization Report Card

  48. Optimization Report Card

  49. Are you looking for different results? On-TimeDelivery Fleet Utilization MarginalContribution Quantity per Driver Hour 15%+ 15%+ 20%+ 5%+ 10%+ 50%+ 15%+ 40%+ In YardbetweenTickets LastAt PlantuntilWashout InServicetoFirst Ticket OnJobWaiting

  50. Looking for Results? Look no further than Dispatch Optimization

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