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Analyzing Demand Data Presented By: Jonathan D. Washko, BS-EMSA Director of Deployment – REMSA President – Washko & Associates, LLC HPEMS & Public Safety.

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Presentation on theme: "Analyzing Demand Data Presented By: Jonathan D. Washko, BS-EMSA Director of Deployment – REMSA President – Washko & Associates, LLC HPEMS & Public Safety."— Presentation transcript:

1 Analyzing Demand Data Presented By: Jonathan D. Washko, BS-EMSA Director of Deployment – REMSA President – Washko & Associates, LLC HPEMS & Public Safety Consulting Partner – Stout Solutions, LLC & FirstWatch

2 Analyzing Demand Data Discussion Topics –What is a Demand Analysis –What kind of data do you need to calculate it –What are some of the pitfalls to watch out for –What formulas do you use to calculated it –What tools do you use to calculate it –What do you do with this information when completed

3 Analyzing Demand Data What is a Temporal Demand Analysis? A Temporal Demand Analysis (or TDA) is an analysis of arrayed and aggregated historical call volume by week, hour of day and day of week. It is used to help predict and determine the number of Quality Unit Hours needed (Demand) for each hour of the day and day of week. When completed, the analysis will provide staffing needs for a total of 168 hours (total number of hours in a week). From this analysis, a Peak Load Staffing Schedule can be built to match the prediction model (Matching Supply with Demand).

4 Temporal Demand Analysis Fundamental Assumptions –Assumes Each Call Takes one hour to complete (1:1 S/D Ratio) –Needs to be adjusted to each system accordingly –Use Task Time to adjust as needed if average is >< 60 minutes –Systems with lower Task Times require less resources –Systems with higher Task Times require more resources –Adjustments can be made through demand multipliers or the performing of a Task Time TDA (A much more complex analysis) Efficiency Alert! Controlling your system’s Task Time can have a HUGE financial impact on your system staffing costs so long as controls are kept to balance the triad. Pitfall Alert! Inaccurate Task Time calculations can substantially impact the outcome of a demand analysis and put patient lives or an organization at risk. Perform the Task Time Analysis with due diligence and caution ensuring accuracy and validity! Analyzing Demand Data

5 Data Set Characteristics –Bad in / bad out concept –What to measure and why Requests, Responses or Transports? Call Priorities to include or exclude Standby / Special Events Multi-Unit Responses Other Variables (CCT, Specialized Units, Special Calls, Special Circumstances, etc.) Analyzing Demand Data

6 Other Things You Need to Know –Desired response time reliability percentage –Inefficiency (LUH) buffer / cushion –Call volume seasonality –Some “Art” (SWAG) Response time requirements Response time zone balancing requirements Effects of city infrastructure (or lack there of) Effects of traffic patterns Effects of political “Posts” Effects of other unique system anomalies Analyzing Demand Data

7 A Temporal Demand Analysis for Monday

8 Raw Demand Analysis Data. P1, P2, P3, P4 & P7 Count of responses that arrived on scene by hour of day, day of week, chronologically ordered by date. A total of 20 weeks worth of most recent data from the CAD system. A Temporal Demand Analysis for Monday

9 Raw Demand Analysis Data. P1, P2, P3, P4 & P7 Count of responses that arrived on scene by hour of day, day of week, chronologically ordered by date. A total of 20 weeks worth of most recent data from the CAD system. Military Date Format of Arrayed Days (Mondays) in Chronological Order In this case the date is Monday February 03, 2003 A Temporal Demand Analysis for Monday

10 Raw Demand Analysis Data. P1, P2, P3, P4 & P7 Count of responses that arrived on scene by hour of day, day of week, chronologically ordered by date. A total of 20 weeks worth of most recent data from the CAD system. Hours of Day in Hour Ending Format e.g. 21 = 20:00 through 21:00 A Temporal Demand Analysis for Monday

11 Raw Demand Analysis Data. P1, P2, P3, P4 & P7 Count of responses that arrived on scene by hour of day, day of week, chronologically ordered by date. A total of 20 weeks worth of most recent data from the CAD system. Total of All Hours for Each Week (Totaled Across) In this case, there were 196 Responses on Feb. 10, 2003 A Temporal Demand Analysis for Monday

12 Raw Demand Analysis Data. P1, P2, P3, P4 & P7 Count of responses that arrived on scene by hour of day, day of week, chronologically ordered by date. A total of 20 weeks worth of most recent data from the CAD system. Represents that on February 17, 2003 there were 13 Responses between 11:00 and 12:00 A Temporal Demand Analysis for Monday

13 A Temporal Demand Analysis for Mondays Section II – EMS Production Model Art & Science, IV.c Demand Analysis Analytics. Used to calculate the required number of Quality Unit Hours (Demand) by Hour of day for this particular day of the week (In this case, Monday) There are various statistical methods used to calculate system demand, all are accurate and correct. Experience has shown that Average Peak (a formula created by Jack Stout’s team) consistently yields an accurate prediction of the 90 th Percentile of demand. A Temporal Demand Analysis for Monday

14 Total Responses for the Hour Totaled by column (hour) In this case the total is 72 responses for 03:00 to 04:00 XL Formula = sum(CR:CR) A Temporal Demand Analysis for Monday

15 Totals are for entire 20 week period (All Hours all Mondays) XL Formula = sum(CR:CR) A Temporal Demand Analysis for Monday

16 Min or Minimum number of Calls for the 20 week period for the hour of day and day of week. In this case the Min for 03:00 to 04:00 = 1 (Which occurs twice during the 20 week period) XL Formula = min(CR:CR) A Temporal Demand Analysis for Monday

17 Total of Min or Minimum number of Calls by hour for all hours. Totaled by row (horizontally) In this case the Total Min = 79 XL Formula = sum(CR:CR) A Temporal Demand Analysis for Monday

18 Max or Maximum number of Calls for the 20 week period for the hour of day and day of week. In this case the Max for 03:00 to 4:00 = 9 (Which occurs once during the 20 week period) XL Formula = max(CR:CR) A Temporal Demand Analysis for Monday

19 Total of Max or Maximum number of Calls by hour for all hours. Totaled by row (horizontally) In this case the Total Max = 357 XL Formula = sum(CR:CR) A Temporal Demand Analysis for Monday

20 Average number of Calls for the 20 week period for the hour of day and day of week. In this case the Average for 03:00 to 4:00 = 3.6 XL Formula = average(CR:CR) A Temporal Demand Analysis for Monday

21 Total of Average number of Calls by hour for all hours. Totaled by row (horizontally) In this case the Total Average = XL Formula = sum(CR:CR) A Temporal Demand Analysis for Monday

22 TMT (Total Mission Time) Multiplier is used to adjust demand calculations by taking the number and multiplying it times the Demand Measurement. Example: if your Average TMT = 75 Minutes then Take 75 / 60 (minutes in an hour) = 1.25 This means that your Demand Measurement will be adjusted by 1.25 or 125% In this case the TMT Multiplier = 0 for simplicity A Temporal Demand Analysis for Monday

23 Average of TMT Multiplier for all hours of this day. Totaled by row (horizontally) In this case the Average = 0.0 XL Formula = Average(CR:CR) A Temporal Demand Analysis for Monday

24 The Standard Deviation of Responses for the hour. In this case the Standard Deviation for 03:00 to 04:00 = 2.0 XL Formula = stdev(CR:CR) A Temporal Demand Analysis for Monday

25 Total of Standard Deviation for all hours of this day. Totaled by row (horizontally) In this case the total Standard Deviation = 72.6 XL Formula = Sum(CR:CR) A Temporal Demand Analysis for Monday

26 The Average High is a Stoutian Measurement that represents approximately the 75 th percentile of demand. It is calculated by taking the maximum number of calls in each consecutive 5 – 4 week periods of a 20 week analysis then dividing the sum of these number by 5 (or average of the 5 periods) In this example, the Average High for 03:00 to 04:00 = 5.8 The XL Formula: =(Max(CR:CR) + Max(CR:CR) + Max(CR:CR) + Max(CR:CR) + Max (CR:CR)) / 5 The resultant is then multiplied by the TMT Multiplier for TMT Adjustments A Temporal Demand Analysis for Monday

27 Total of Average High for all hours of this day. Totaled by row (horizontally) In this case the total Average High = XL Formula = Sum(CR:CR) A Temporal Demand Analysis for Monday

28 The 90 th Percentile (or X Percentile) is a statistical ranking method used to determine the demand at X percent. In this case the 90 th Percentile Rank for 03:00 to 04:00 = 6.1 XL Formula = percentile(CR:CR,.9) where.9 = 90% The resultant is then multiplied by the TMT Multiplier for TMT Adjustments A Temporal Demand Analysis for Monday

29 Total of 90 th Percentile for all hours of this day. Totaled by row (horizontally) In this case the total 90 th Percentile = XL Formula = Sum(CR:CR) A Temporal Demand Analysis for Monday

30 The Average Peak is a Stoutian Measurement that represents approximately the 90 th percentile of demand. It is calculated by taking the maximum number of calls in each consecutive 2 – 10 week periods of a 20 week analysis then dividing the sum of these number by 2 (or average of the 2 periods) In this example, the Average Peak for 03:00 to 04:00 = 8.0 The XL Formula: = (Max(CR:CR) + Max(CR:CR) ) / 2 The resultant is then multiplied by the TMT Multiplier for TMT Adjustments A Temporal Demand Analysis for Monday

31 Total of Average Peak for all hours of this day. Totaled by row (horizontally) In this case the total Average Peak = XL Formula = Sum(CR:CR) A Temporal Demand Analysis for Monday

32 The Smoothed Average Peak is a statistical smoothing of the Average Peak and is used to “blend” the severity of hour to hour demand fluctuations for easier peak- load scheduling. It is calculated by taking 20% of the previous hour (Blue) + 60% of the current hour (Red) + 20% of the next hour (Yellow). In this example, Smoothed Average Peak for 03:00 to 04:00 = 7.6 The XL Formula: = (CR*.2)+(CR*.6)+(CR*.2) A Temporal Demand Analysis for Monday

33 Total of Smoothed Average Peak for all hours of this day. Totaled by row (horizontally) In this case the total Smoothed Average Peak = XL Formula = Sum(CR:CR) A Temporal Demand Analysis for Monday

34 2x StdDev + Mean is a Statistical Process Control methodology used by industry as an upper control chart limit. It represents approximately the 95% of demand. It is calculated by taking the Standard Deviation (Red) calculated previously for the hour, multiplying it by 2 then adding it to the previously calculated average (Blue). In this example, 2x StdDev + Mean for 03:00 to 04:00 = 7.67 The XL Formula: = (CR*2)+(CR) The resultant is then multiplied by the TMT Multiplier for TMT Adjustments A Temporal Demand Analysis for Monday

35 Total of 2x StdDev + Mean for all hours of this day. Totaled by row (horizontally) In this case the total 2x StdDev + Mean = XL Formula = Sum(CR:CR) A Temporal Demand Analysis for Monday

36 The UH Adj / Eff Buffer is used to allow managers the ability to adjust up or down their staff to lines based on individual system needs. This is where some of the “art” comes in helping to determine this figure. This can also be used to adjust the demand for contractual unit minimums and other needs. In this case, the UH Adj / Eff Buffer for 03:00 to 04:00 = 2 A Temporal Demand Analysis for Monday

37 Total of UH Adj / Eff Buffer for all hours of this day. Totaled by row (horizontally) In this case the total UH Adj / Eff Buffer = 48.0 XL Formula = Sum(CR:CR) A Temporal Demand Analysis for Monday

38 Adjusted Supply / Inefficiency Buffer UH Adjustment Variables –The part of the “Art” of HPEMS (SWAG) –Response Time Requirements –Infrastructure Impacts –Geography / Coverage Area –System Idiosyncrasies and Their Impacts –Lost Unit Hours –Politics –Lots of Others A Temporal Demand Analysis for Monday

39 Demand Curve Adjustments Example: Average Peak + 4 = Minimal Staffing

40 The Staff To line is the number of QUH required for that hour of that day. It typically defines the minimum number of expected demand at X Percentile (Based on demand formula used). In this example, we are using the Average Peak + UH Adj / Eff Buffer as our Staff to Calculation. The definition of this calculation varies by system and is not set. Frequently HPEMS systems use the Smoothed Average Peak + UH Adj / Eff Buffer approach. In this Example the Staff to Line for 03:00 to 04:00 = 10.0 A Temporal Demand Analysis for Monday

41 Total of Staff to Line for all hours of this day. Totaled by row (horizontally) In this case the Staff To Line = XL Formula = Sum(CR:CR) A Temporal Demand Analysis for Monday

42 So What Do All These Numbers Mean? Analyzing Demand Data

43 So What Do All These Numbers Mean? The Temporal Demand Analysis results in telling you how many Quality Unit Hours need to be produced by hour of day and day of week. Each hour of each day will have its own number for a total of 168 Production / Demand Requirements You build your “Production Schedule” to match these numbers Analyzing Demand Data

44 So What Do All These Numbers Mean? The total columns come in handy as by adding the appropriate total for each day will give you the total QUH requirement for the week. This number can then be used to calculate FTE’s, UHU and other budget figures. Keep in mind this is the optimal requirement. It is very difficult (if not near impossible) to create a schedule that exactly matches the demand requirements. The best Schedule to Demand matching I have experienced is +/- 2% to 3% variation. Zoll’s Resource Planner allows you to take Demand Data from this analysis to easily build a schedule that ACCURATELY matches your system’s Demand (see next session). Analyzing Demand Data

45 Tricks of the Trade… If your system is responsible for multiple geographic regions that are not contiguous or operate as separate deployment centers, a separate TDA for each area may be warranted Microsoft Excel or Microsoft Access (for advanced programmers) is the best tool for creating a TDA Microsoft Excel Pivot Tables allow for immediate arraying of data into tables that can then be copied and pasted into a TDA template Analyzing Demand Data

46 Tricks of the Trade… You really only need a few key pieces of data to calculate the TDA raw data array –TDA Priority of the call Call clock start date and time –Hour of day and day of week calculations can be performed from this information –GDA (plusTDA data) Longitude of the call (or full address if not available) Latitude of the call (or full address if not available) Analyzing Demand Data

47 Tools That Can Help… FirstWatch –FirstWatch (Data Surveillance Tool) has created a Demand Analysis Tool that allows for a “button push” assessment of demand that has an output file that can be directly imported into Zoll’s Resource Planner based on the templates used in this session.www.first-watch.us Zoll Data Systems / Washko & Associates –Working on developing a Resource Planner Add On that will allow you to import demand data directly into Resorce Planner –Developed an exclusive arrangement for customers looking for additional expertise and help (Speak with me or your Zoll Sales Representitive) Analyzing Demand Data

48 Questions / Discussion… Analyzing Demand Data


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