DNA of Demand Capacity Planning A Primer

Define • • • • • • • • • Demand – the volume and mix of patient placed upon the process or value stream Theoretical capacity – Designed capacity Planned capacity Demonstrated capacity Demand utilization Cycle time TAKT White space

Define • • Sporadic losses – Infrequent – Easy to identify – Focused on due to emotions Chronic losses – Occur daily – Defects are hidden – Difficult to id – Major losses over time

Theoretical Capacity

The Big Capacity Losses

Planned Capacity Demand Utilization Throughput External Interruptions Outages / Shutdowns Rate Losses 100% Capacity Managed Availability Net Availability Throughput Demonstrated Capacity Quality Losses Net O.E.E.

24hrs 365 days 100% Rate 100% Quality Loss of energy Lack of sales demand Planned and unplanned outages including shutdowns Production rates < Best Demonstrated Practice (B.D.P.) Yield or Out or Specification

How do we assess time available for 100% OPE?

gross time available net time available gross time available = 365 days / yr X 24hrs/day external losses scheduled losses

scheduled losses

- time that machine not crewed to run (may vary if overtime is used) - time not planned to run due to lack of sales demand

external losses

- losses outside of factory control e.g. power dips availability performance quality Gross OPE = OPE Vs. gross time available = true capacity utilisation of an asset Net OPE = OPE Vs. net time available i.e non-impactable losses = true measure of manufacturing effectiveness

Theoretical cap Demand Takt Time Planned cap Demonstrated cap

Cycle Time – the time taken to complete the activity or task Time Operation Cycle Time Operation A Operation B Operation C

Takt = Available production time/demand Demand Takt Time Operation Cycle Time Operation A Operation B Operation C

Takt time is inversely proportional to demand: As demand goes up Takt goes down As demand goes down Takt goes up

Operation Cycle Time Demand Takt Time Operation A Operation B Operation C

CT is less that TT CT is greater that TT Constraint Demand Takt Time Inventory build up Operation Cycle Time Operation A Operation B Operation C

CT is less that TT CT is greater that TT Move work content from B to A Demand Takt Time Operation Cycle Time Operation A Operation B Operation C

Max Cycle Time for planning At 85% of Takt. This permits 25% Flexibility for drop in and/or losses Q Theory Level load the Work content across All operations Theoretical Demand Takt Time White space O1 O2 O3

Time Manual Cycle Times (MCT's) Bar Chart (loading diagram) TOTAL MCT: TAKT TIME:

(available time) (customer demand)

MIN. STAFFING:

(total MCT) (takt time)

People

Theoretical Cycle Time/Rate/Speed (As designed by Engineering Standards)

Issue TAKT is greater Than operation cycle time. Need to C/O or build inventory

Takt Time (decreased demand over same operational time span increases Takt per unit) White Space Most improve: •Availability •C/O •Reduced Speed •Idle •Start up loss •Yield loss

Issue TAKT is less Than operation cycle time. Can not meet Demand

Actual Cycle Time in Operational Conditions (Machine is in failure mode at less than design) Takt Time (increased demand over same operational time span decreases Takt per unit)

Operation DNA

Components in understanding flow

• • • Variation Waits and delays Fundament mismatch between demand and capacity 15

Five essential features of flow

1. Flow as efficiency and cycle times 2. Flow as reduced variation, increased predictability and improved forecasting 3. Flow as systems thinking 4. Flow as empowered provides exceeding expectations 5. Flow as demand-capacity management Every system is perfectly designed to achieve the results it achieves 16

Variation in flow

• • Reduction of variation must be supplemented by an ability to increase predictability so we can forecast the demands that will be placed on healthcare To the extend that we are able to forecast patient demand, we increase our ability to improve flow I knew you were coming – I just didn’t know your name!

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Variation in flow

• How much and what type of variation is the right variation I knew you were coming – I just didn’t know your name!

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Managing Variation in flow

• • • • Natural variation is clinical variability in diseases and professional variability in skills, patient arrival times and durations.

It is random It is part of flow It must be managed 19

Managing Variation in flow

• • • • Artificial variation is non random Elective procedures Time of discharge Must be smoothed so that they are predictable and steady and in fact the high variability often associated with it eliminated Artificial variation contributes significantly to problems with flow 20

System Thinking in Flow

• • Flow is a complex interaction between multiple systems, all of which are designed to improve the health and safety of the patient. Healthcare involves a series of service transitions in a complex system of various providers inputting their efforts into even the simplest of initiatives If these processes and the people who provide those processes are not positively and proactively cooperating to develop a seamless System, the provision of our healthcare begins to appear to the patient As having been functionally siloed in that handoffs and transitions are Not effectively handled 21

Empowered providers exceeding expectations

• • Those providing the service have the ability to adapt the service to meeting or exceed the needs of the patient or family during the course of the provision of that service Lead teams with a new spirit which encourages innovation in value identification and creation with a healthy

disrespect

for tradition in the merciless elimination of waste.

The simplest way to understand patients’ expectations is two Simple words: Ask them!

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Flow as demand-capacity management

• The more a system has bottlenecks built into it, the less it has flow as an essential characteristics. Matching service demand with service capacity is a critical component of flow Service capacity simply can not be stored and is in that respect A perishable commodity 23

Benefit to Burden Ratio

• Flow exists to the extent that value is added to the service during a patient’s journey through the queues and transitions in healthcare • The providers must be asking: – Does this add value?

– How does this add value?

Value comprises a simple ratio of benefits received versus burdens endured to receive those benefits 24

Benefit to Burden Ratio

• Value is defined as a ratio of the benefits received versus the burdens endured as the service is delivered Flow = Value Added Services = Benefits Received Burdens Endured 25

Benefit to Burden Ratio

• The benefit to burden ratio as a definition of flow through adding value, can be applied to virtually any process or activity in healthcare by asking three fundamental flow questions: 1. What are the benefits received?

2. What are the burdens endured?

3. Would you tolerate this ratio?

“No thanks, I’d rather enjoy the show!” 26

Benefit to Burden Ratio

Increase Value

Benefit Benefit Benefit Benefit Burden Burden Burden Burden

Decreased Value

Benefit Benefit Benefit All waste is burden, but not all burden is waste Burden Burden Burden 27

Six clinical elements that we need to get right

1. The right resources; 2. To the right patient; 3. In the right environment (bed/room); 4. For the right reasons; 5. With the right team; 6. At the right time – every time!

We can’t manage value unless we understand what benefits and burdens the patient expects.

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Seven key strategies for improving flow:

1. Demand – capacity management 2. Real time monitoring of patient flow 3. Forecasting service demand 4. Queuing theory 5. Theory of Constraints 6. Manage variation 7. System appreciation 29

Demand – Capacity Management :

• The most important aim in D-C Management is to establish a measure of patient demand by hour and design a system to handle it.

1. How many patients are coming?

2. When are they coming?

3. What resources are they going to need?

4. Is our service capacity going to match patient demand Staffing based on “averages” means half of the time demand will exceed capacity… 30

Demand – Capacity Management : Key Principles

1. Predict demand based on historical data 2. Match service capacity to patient demand 3. Make daily predictions and plans 4. Implement a real time dashboard for key cycles and monitor it 5. Respect the desires, concerns and goals fo the people on your team Managing demand and capacity together can be done in tow ways: • Smoothing patient demand or • Matching service capacity to meet it 31

Key questions for real time monitoring

1. How many patients are we currently caring for?

2. When do they need what services?

3. How does our service capacity match patient demand?

4. What are our contingency plans?

5. What does this patient need next?

6. What are the rate limiting steps?

Determine whether the unit or hospital requires a plan to meet the predicted demand if it will be greater than predicted capacity 32

Three methods of forecasting flow

1.

2.

3.

Percentage adjustment is the best estimate of what will happen in the future based on percentage increase or decrease in performance over the previous 12 months.

Moving average calculates the average number of patient visits for the previous 12 months; it recalculates each month based on the previous 12 A trend line statistically derives a best fit line using regression analysis based on historical data to determine how accurate earlier planning was compared with the actual number of admissions in the previous 12 months 33

Queuing Theory

• • • • The matching of fixed resources to unscheduled demand System with unscheduled or uncontrolled arrivals Running at 100% capacity in a system with unscheduled arrivals and variable service times is not the most effective way to operate Since 80 to 85% demand utilization is often optimal, this is where to plan capacity and better handle inflows and variation Does not mean completely unpredictable with the right data 34

Queuing Theory

• Consider the following: 1. When do admissions arrive?

2. What type of admissions are they?

3. When do admissions move into inpatient beds?

Used the data collected to predict what will happened tomorrow and form a plan to deal with it today 35

Psychology of Waiting

• Eight principles: 1. Occupied time beats unoccupied time 2. Being in process beats being preprocess 3. Anxiety is bad 4. Limited certainty beats uncertainty 5. Explained situations beats unexplained ones 6. Equitable treatment beats unfair treatment 7. The more valuable the service, the more tolerable the wait 8. Group waits beat solo waits 36

Theory of Constraint

• • • The capacity of the system equals the capacity of the bottleneck The slowest process or resource in the value chain governs throughput Bottleneck is any resource with capacity equal to or less than the demand place upon it 37

Appreciate the system

• To improve patient flow you need to decide what the aim of your work is. Is the aim clear to everyone in the system. If not, the system will include good people with differing priorities – Espoused theory – what teams believe is the commonly understood aim – Theory in action – what actually occurs in the day to day operations of the organization Optimizing flow through an entire system is more difficult than optimizing flow through one department…it requires leaders 38

Appreciate the system

• • • Will: the sustained commitment to make a difference Ideas: the lifeblood of the work Execution: the ability to actually carrey out plans This requires an engaged and informed leadership and a passionate, spirited team 39