Lean Risk Management
Options, Liquidity & Hedging
Risk using Kanban Systems

How Kanban is enabling a new
approach to risk...
Making Promises with Kanban
(and some often poorly understood fundamentals)

dja@djaa.com, @agilemanager
Commitment in Kanban
Pool
of
Ideas

Engineering
Ready

Ongoing

2

Testing

Development

3

Done

3

Verification Acceptan...
2nd Phase Delivery Commitment
Pool
of
Ideas

Engineering
Ready

2

Testing

Development
Ongoing

3

Done

F

3

Verificati...
Defining Lead & Cycle Time
Pool
of
Ideas

Engineering
Ready

2

Pull

Deploy-

The clock starts ticking when
ment
Testing
...
Little’s Law

=

Delivery Rate

Pool
of
Ideas

WIP
Lead Time

Avg. Lead Time
WIP

dja@djaa.com, @agilemanager

Ready
To
De...
Flow the
Efficiency
Flow efficiency measures

Pool
Enginpercentage of total lead time
of spent actually adding value
eerin...
Observe Lead Time Distribution as an enabler
of a Probabilistic Approach to Management
Lead Time Distribution
3.5
3

CRs &...
Mean
5 days

Change Requests

Production Defects

Filter Lead Time data by Type of Work (and
Class of Service) to get Sing...
Allocate Capacity to Types of Work
Pool
of
Ideas

Engineering
Ready

Ongoing

2
Change
Requests

Development

4

3

Done

...
Risks & Qualitative Assessment

dja@djaa.com, @agilemanager
Key Risk to Manage is What to Pull Next
Pool
of
Ideas

Engineering
Ready

4

∞

Development
Ongoing

3

Done

Deployment
R...
Lean Risk Management uses Qualitative
Assessment
But how do we determine the risks in
We need a work item that we must man...
impact

impact

Establish cost of delay (or urgency) by
qualitative matching

time

impact

impact

time

time

time

Inta...
Risk is a multi-dimensional problem
So understanding cost of delay
Yes, however, it isn’t always relevant! Cost of
enables...
Classes of Service Manage Cost of Delay
Risk
DeployEngineering
Development
Ready
Different distributions for

3

Ongoing
c...
impact

Cost of Delay has a 2nd Dimension
Working capital

impact

time
Working capital

impact

time

Extinction Level Ev...
Market Risk of Change

Market Risk

Potentia
l Value
Profits
Market Share
etc

Start
Late

Differentiators
Spoilers
Regula...
Product Lifecycle Risk
High

Not well understood
High demand for innovation &
experimentation

Low

Major
Growth
Market

I...
Risk is a multi-dimensional contextual
problem
These are just useful examples!
We must develop a set of
We can easily envi...
A middle-ground in effective Risk
Management

Qualitative Taxonomies
2 -> 6 categories
Cheap
Fast
We can easily envisage o...
Visualize Risks to provide Scheduling
Information
Outside:
Start Early

Market Risk
Items with the same shape carry the sa...
Hedging

dja@djaa.com, @agilemanager
Hedging Delivery Risk with Capacity
Allocation
DeployEngineering
Ready

2
Expedite

Development
Ongoing

3

Testing

3

Do...
Aligning with Strategic Position
or Go-to-Market Strategy
DeployEngineering
Ready

2
Table
Stakes

3

Cost
Reducer
s

2

D...
Hedging Risk in a Portfolio Kanban
Horizational position shows percentage complete
Allocation of personnel
Complete
Total ...
Options

dja@djaa.com, @agilemanager
Some Options Get Discarded
Pool
of
Ideas

Engineering
Ready

Ongoing

2

Testing

Development

3

3

Done

Verification Ac...
Bottleneck should always be downstream
of the commitment point
Pool
Enginof
Ideas

eering
Ready

Ongoing

2

Pull

F

Anal...
Competing pressure of Last Responsible
Moment versus Upstream Bottleneck
Pool
of
Ideas

EnginIn domains with Development
h...
impact

The Optimal Exercise Point
If we start too early, we forgo
the option and opportunity to do
something else that ma...
Liquidity

dja@djaa.com, @agilemanager
Where is the best place to place a work
order to best manage risk?
But can we view kanban systems as

Investment bankers k...
Liquidity in the housing market
Sellers

$100

Bank

Buyers

Cash
$100

dja@djaa.com, @agilemanager
Measuring Liquidity
The more transactions, the more
liquid the market
what is required are well matched
buyers, sellers an...
Adverse Market Conditions
In a market with lots of buyers but few well
matched sellers, inventory will be scarce, few
tran...
More Adverse Market Conditions
In a market with lots of sellers but few well
Hence, market grow and few
matched buyers inv...
So, how would we measure
liquidity?

dja@djaa.com, @agilemanager
Measuring Real Liquidity…

If we recall, liquidity is measured as
transaction volume in the market. So
what are the transa...
Pull Transactions in Kanban
Pool
of
Ideas

Engineering
Ready

2

F

Development
Ongoing

3

Done

Testing

3

Verification...
Variety & Specialization increase WIP
Pool
of
Ideas
∞

K

L

As a
DeployEngin- result, there will be a minimum level of
WI...
Liquidity is measured as volume of
pull transactions

Thus, I am proposing that system
liquidity be measured as the volume...
Normalizing Liquidity Measures
To normalize this figure across
multiple systems, we could divide it
by the number of worke...
Pull Transactions / Person

Greater values for pull transaction
volume serve to show us the most
trustworthy system.
They ...
Characteristics of Liquid Markets
A liquid financial market would exhibit
several characteristics…
Tightness – bid-ask spr...
Characteristics of a Liquid Kanban
Market
A liquid kanban system would exhibit these
characteristics…
Tightness* – varianc...
Liquidity of the system should be
considered against observed capability
before placing an order
Some kanban systems may a...
Liquidity is a Good Metric
Our measure of liquidity, as pull
transaction volume per person or unit
of currency in a time p...
Relevance of Liquidity as a Measure
Little’s Law

So our plans carry less
buffer for variation
Narrow spread of variation ...
Improving Liquidity through Labor Pool
Flexibility
Engineering
Ready

Teams

3

F
Cost
Reducer
s

Spoilers

2

1

3

Devel...
Conclusions

dja@djaa.com, @agilemanager
Kanban enables new powerful approaches to
risk management in knowledge work
Kanban systems enable us to visualize
many dim...
Lean Risk Management is Pragmatic
Qualitative approaches to risk
assessment are fast, cheap and drive
consensus
Stop specu...
Thank you!
dja@djaa.com, @agilemanager
About

David Anderson is a thought
leader in managing effective
software teams. He leads a
consulting, training and
publis...
Acknowledgements

Raymond Keating of CME Group in New Jersey has been instrumental
as a collaborator on the ideas in this ...
David J Anderson
& Associates, Inc.

dja@djaa.com, @agilemanager
Appendix

dja@djaa.com, @agilemanager
Identifying Buffers
Pool
of
Ideas

Engineering
Ready

Ongoing

2

F

GY

3

Done

verification Acceptance

I am a buffer!
...
Infinite Queues Decouple Systems
Pool
Enginof
eering
The infinite queue Development
decouples
Ideas
Ready

the systems. Th...
Change Requests

The psychology of a probabilistic approach
can be challenging…

I don’t want to take the risk of
being lo...
A lack of organizational social capital…
A lack of organizational social capital may
prevent trust in the kanban system fr...
…replace trust with comfort & reassurance

Deterministic planning provides a level of
When people take the blame, replacin...
Liquidity in the housing market
Sellers

dja@djaa.com, @agilemanager

$100

Bank

Buyers
Liquidity in the housing market
Sellers

$100

Bank

Buyers

Cash
$100

dja@djaa.com, @agilemanager
Fixed Date

Intangible

Standard

Expedite

Example Distributions

dja@djaa.com, @agilemanager
dja@djaa.com, @agilemanager
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Lean Kanban Netherlands 2012 - Lean Risk Management

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  • Work flows through a kanban system when we have well matched work order or items of WIP with suitable staff to add valuable new knowledge and progress work to completion.
  • Lean Kanban Netherlands 2012 - Lean Risk Management

    1. 1. Lean Risk Management Options, Liquidity & Hedging Risk using Kanban Systems How Kanban is enabling a new approach to risk management in knowledge work Lean Kanban Netherlands, Utrecht, October 2012 dja@djaa.com, @agilemanager
    2. 2. Making Promises with Kanban (and some often poorly understood fundamentals) dja@djaa.com, @agilemanager
    3. 3. Commitment in Kanban Pool of Ideas Engineering Ready Ongoing 2 Testing Development 3 Done 3 Verification Acceptance Deployment Ready ∞ Pull F D G P1 E PB I GY DE MN AB We are committing to getting started with a probabilistic expectation of delivery time 1st Commitment point dja@djaa.com, @agilemanager Done
    4. 4. 2nd Phase Delivery Commitment Pool of Ideas Engineering Ready 2 Testing Development Ongoing 3 Done F 3 Verification Acceptance D PB ∞ MN G DE Deployment Ready P1 E AB I GY We are now committing to a specific deployment and delivery date dja@djaa.com, @agilemanager 2nd Commitment point Done
    5. 5. Defining Lead & Cycle Time Pool of Ideas Engineering Ready 2 Pull Deploy- The clock starts ticking when ment Testing we Development accept the customers Ready 3 3 order, not when it is placed! Ongoing Done ∞ queue. Cycle time is an ambiguous term. It D This provides theP1correctmust be qualified, for example, G result for Little’s Law and Development Cycle Time E I ∞ Until then customer orders are merely available options Lead time ends when the item reaches the first F Verification Acceptance Done PB visualization on a Cumulative End-to-end Cycle Time = Time from 1st GY DE MN Flow Diagram AB commitment to delivery Lead Time Cycle Time Cycle Time dja@djaa.com, @agilemanager
    6. 6. Little’s Law = Delivery Rate Pool of Ideas WIP Lead Time Avg. Lead Time WIP dja@djaa.com, @agilemanager Ready To Deploy Avg. Delivery Rate
    7. 7. Flow the Efficiency Flow efficiency measures Pool Enginpercentage of total lead time of spent actually adding value eering is Development Ideas Ready (or knowledge) versus waiting 3 Ongoing 2 Done Testing 3 Verification Acceptance Deployment Ready ∞ Until then customer orders are merely available options Flow efficiency = Work Time E PB GY DE Waiting Working x 100% Lead Time Flow efficiencies of 2% have been F reported*. 5% -> 15% D normal, P1 is > 40% is good! G I Done MN AB Waiting Working Waiting Lead Time * Zsolt Fabok, Lean Agile Scotland, Sep 2012, Lean Kanban France, Oct 2012 dja@djaa.com, @agilemanager
    8. 8. Observe Lead Time Distribution as an enabler of a Probabilistic Approach to Management Lead Time Distribution 3.5 3 CRs & Bugs 2.5 2 1.5 1 0.5 1 4 7 0 3 6 8 14 14 13 12 12 11 10 99 92 85 78 71 64 57 50 43 36 29 22 8 15 1 0 Days This is multi-modal data! The workexpectation of SLA is of two types: Change Requests (new 105 and Production features);days with 98 % Defects Mean of 31 days SLA expectation of 44 days with 85% on-time dja@djaa.com, @agilemanager on-time
    9. 9. Mean 5 days Change Requests Production Defects Filter Lead Time data by Type of Work (and Class of Service) to get Single Modal Distributions 98% at 25 days 85% at 10 days dja@djaa.com, @agilemanager 98% at 150 days Mean 50 days 85% at 60 days
    10. 10. Allocate Capacity to Types of Work Pool of Ideas Engineering Ready Ongoing 2 Change Requests Development 4 3 Done Testing 3 Verification Acceptance Consistent capacity allocation E some consistency to should bring more consistency to MN delivery rate of work of each D AB type F Lead Time PB DE Productio n Defects I Deployment Ready 3 G P1 GY Separate understanding of Separate understanding of Lead Lead Time for each type of Time for each type of work work Lead Time dja@djaa.com, @agilemanager ∞ Done
    11. 11. Risks & Qualitative Assessment dja@djaa.com, @agilemanager
    12. 12. Key Risk to Manage is What to Pull Next Pool of Ideas Engineering Ready 4 ∞ Development Ongoing 3 Done Deployment Ready Testing 3 Verification Acceptance ∞ Replenishing the system is an act of commitment – selecting items for delivery – for conversion from options into real value. J K L G Pull Selection is choosing from immediate options – ideally have 4 options, which one item I dynamic selection of the Pull D most immediateErisk attached to it with the should I choose? I System Replenishment F Pull Pull Selection dja@djaa.com, @agilemanager Done
    13. 13. Lean Risk Management uses Qualitative Assessment But how do we determine the risks in We need a work item that we must manage? a fast, cheap, accurate, consensus forming approach to risk assessment. We need Lean Risk Management! The answer is to use a set of qualitative methods to assess different dimensions of risk such as urgency dja@djaa.com, @agilemanager
    14. 14. impact impact Establish cost of delay (or urgency) by qualitative matching time impact impact time time time Intangible – cost of delay may be significant but is not incurred until much later; important but not urgent impact time Fixed date – cost of delay goes up significantly after deadline; Start early enough & dynamically prioritize to insure on-time delivery Standard - cost of delay is shallow but accelerates before leveling out; provide a reasonable lead-time expectation impact impact time Expedite – critical and immediate cost of delay; can exceed other kanban limit (bumps other work) time dja@djaa.com, @agilemanager
    15. 15. Risk is a multi-dimensional problem So understanding cost of delay Yes, however, it isn’t always relevant! Cost of enables us to know what to pull delay attaches to a deliverable item. What if next? that item is large? Whole projects, minimum marketable features (MMFs) or minimum viable products (MVPs) consist of many smaller items. We need to understand the risks in those smaller items too, if we are to know how to schedule work, replenish our system and make pull decisions wisely dja@djaa.com, @agilemanager
    16. 16. Classes of Service Manage Cost of Delay Risk DeployEngineering Development Ready Different distributions for 3 Ongoing classes of Testing 3 different 2 increases the level of trust that an item will be delivered in a Expedite 1 timely manner, demonstrating that cost of delay is a risk under management AB Fixed Date 2 Done service Verification Acceptance P1 E D MN PB Standard 3 F G GY Intangible 1 I dja@djaa.com, @agilemanager DE ment Ready ∞ Done
    17. 17. impact Cost of Delay has a 2nd Dimension Working capital impact time Working capital impact time Extinction Level Event – a short delay will completely deplete the working capital of the business Major Capital – the cost of delay is such that a major initiative or project will be lost from next year’s portfolio or additional capital will need to be raised to fund it Discretionary Spending – departmental budgets may be cut as a result or our business misses its profit forecasts impact time ? time Intangible – delay causes embarrassment, loss of political capital, affects brand equity, mindshare, customer confidence, etc dja@djaa.com, @agilemanager
    18. 18. Market Risk of Change Market Risk Potentia l Value Profits Market Share etc Start Late Differentiators Spoilers Regulatory Changes Cost Reducers Scheduling Highly likely to change Table Stakes Highly unlikely to change dja@djaa.com, @agilemanager Start Early
    19. 19. Product Lifecycle Risk High Not well understood High demand for innovation & experimentation Low Major Growth Market Investment Growth Potentia l Product Risk Innovative/New Cash Cow Low Well understood Low demand for innovation dja@djaa.com, @agilemanager Low High
    20. 20. Risk is a multi-dimensional contextual problem These are just useful examples! We must develop a set of We can easily envisage other risk dimensions risk such as technical risk,that work in context for taxonomies vendor dependency risk, organizational maturity risk and so forth. a specific business. It may be necessary to run a workshop with stakeholders to explore and expose the real business risks requiring management dja@djaa.com, @agilemanager
    21. 21. A middle-ground in effective Risk Management Qualitative Taxonomies 2 -> 6 categories Cheap Fast We can easily envisage other risk dimensions Accurate such as technical risk, vendor dependency Consensus risk, organizational maturity risk and so forth. Managed Risk It may be necessary to run a workshop with stakeholders to explore and expose the real business risks requiring management Homogenous Cheap Fast High Risk dja@djaa.com, @agilemanager Heterogeneous Expensive Time Consuming Fake Precision? May still be High Risk
    22. 22. Visualize Risks to provide Scheduling Information Outside: Start Early Market Risk Items with the same shape carry the same risks and should be scheduled into the kanban system TS at approximately the same time. CR It is also wise to hedge risk by Do not Tech Risk Lifecycle New allocating prioritize items. From a whichever ones capacityprofile pick group for in the system of items Spoilrisk with the same items of differentMidprefer most Start Late risk profiles.Inside: you like or Unknown Soln Diff Cow Known but not us Done it before Commodity Intangible Disc Std Maj. Cap. ELE Delay Impact dja@djaa.com, @agilemanager FD Expedite Risk profile for a work item or deliverable Cost of Delay
    23. 23. Hedging dja@djaa.com, @agilemanager
    24. 24. Hedging Delivery Risk with Capacity Allocation DeployEngineering Ready 2 Expedite Development Ongoing 3 Testing 3 Done Verification Acceptance 1 P1 AB Fixed Date 2 E D MN PB Standard 3 F G GY Intangible 3 I dja@djaa.com, @agilemanager DE ment Ready ∞ Done
    25. 25. Aligning with Strategic Position or Go-to-Market Strategy DeployEngineering Ready 2 Table Stakes 3 Cost Reducer s 2 Development Ongoing 3 Testing 3 Done Verification Acceptance E D MN 1 F GY Differenti ators ∞ Market segmentation can be used to narrow the necessary table stakes for any given market G niche! Enabling early delivery for narrower P1 markets but potentially including value AB DA generating differentiating features PB Spoilers ment Ready 1 dja@djaa.com, @agilemanager I DE Done
    26. 26. Hedging Risk in a Portfolio Kanban Horizational position shows percentage complete Allocation of personnel Complete Total = 100% 0% Cash Cows 10% budget Innovative/New 30% budget B A Growth Markets 60% budget D C K E G F dja@djaa.com, @agilemanager Complete 100% Projects-in-progress Color may indicate cost of delay (or other risk) H
    27. 27. Options dja@djaa.com, @agilemanager
    28. 28. Some Options Get Discarded Pool of Ideas Engineering Ready Ongoing 2 Testing Development 3 3 Done Verification Acceptance Deployment Ready ∞ Pull F D G P1 The discard rate can be as Emuch as 50% PB GY DE Reject Discarded I dja@djaa.com, @agilemanager MN AB have value Options because the future is uncertain 0% discard rate implies there is no uncertainty about the future Done
    29. 29. Bottleneck should always be downstream of the commitment point Pool Enginof Ideas eering Ready Ongoing 2 Pull F Analysis 3 Done Development Testing 3 Verification Acceptance Ongoing Done Bottleneck workers should never be asked to work on something that is optional and may be discarded. This includes any risk analysis (or estimation in legacy processes) that may be D P1 required to assess viability of an option G E PB GY DE Reject MN AB Discarded I Commitment point dja@djaa.com, @agilemanager Bottleneck should be here 3
    30. 30. Competing pressure of Last Responsible Moment versus Upstream Bottleneck Pool of Ideas EnginIn domains with Development high uncertainty the eering Testing Analysis Ready 3 3 bottleneck should be Done Verification Acceptance 3 deliberately Done Ongoing late in the2workflow. We should be prepared to discard options very Keeping the bottleneck early in the workflow means all downstream functions have slack late. Ongoing F capacity. Reduces our need to manage WIP and reduces negative effects of variability in demand D P1 Consider Lean Startup?... G PB GY E Where is the MN bottleneck? DE AB Last Responsible Moment Commitment point dja@djaa.com, @agilemanager Bottleneck early in workflow
    31. 31. impact The Optimal Exercise Point If we start too early, we forgo the option and opportunity to do something else that may provide value. If we start too late we risk Ideal Start incurring the cost of delay When we need it Here With a 6 in 7 chance of on-time delivery, we can always expedite to insure on-time delivery 85th percentile Commitment point dja@djaa.com, @agilemanager
    32. 32. Liquidity dja@djaa.com, @agilemanager
    33. 33. Where is the best place to place a work order to best manage risk? But can we view kanban systems as Investment bankers know how to answer this markets for software question! They prefer to place orders in liquid markets. In a highly liquid market they have development? trust that an order will be fulfilled accurately, quickly and at the correct price. Highly liquid markets are markets with a high level of trust. High liquidity inherently gives us high confidence in the market. dja@djaa.com, @agilemanager
    34. 34. Liquidity in the housing market Sellers $100 Bank Buyers Cash $100 dja@djaa.com, @agilemanager
    35. 35. Measuring Liquidity The more transactions, the more liquid the market what is required are well matched buyers, sellers and access to capital such as mortgages, bridging loans or cash measured Market liquidity is buyers injecting capital into the system, to fund the transaction volume transactions . when these conditions are present transactions will take place! dja@djaa.com, @agilemanager as
    36. 36. Adverse Market Conditions In a market with lots of buyers but few well matched sellers, inventory will be scarce, few transactions will occur. When a property comes on the market it could sell quickly but there will be anxiety over the correct price. This may delay the sale or cause the buyer to overpay through fear of losing the purchase to competitive buyers. In some markets like England, the seller may refuse to close the transaction in hope of a higher price (gazumping). Lack of liquidity causes a lack of trust in the system and delays transactions dja@djaa.com, @agilemanager
    37. 37. More Adverse Market Conditions In a market with lots of sellers but few well Hence, market grow and few matched buyers inventory will liquidity can be transactions will happen.rate of transactions measured as Uncertainty will develop over the correctconcluded! trust price. A lack of will result in a disparity between asked prices and offered prices. Additional information may be sought to establish a fair price. Transactions will be delayed dja@djaa.com, @agilemanager
    38. 38. So, how would we measure liquidity? dja@djaa.com, @agilemanager
    39. 39. Measuring Real Liquidity… If we recall, liquidity is measured as transaction volume in the market. So what are the transactions in a kanban system? dja@djaa.com, @agilemanager
    40. 40. Pull Transactions in Kanban Pool of Ideas Engineering Ready 2 F Development Ongoing 3 Done Testing 3 Verification Acceptance Deployment Ready ∞ For work to flow freely in a kanban system, we must have work available to pull and suitably matched workers available to pull it. Hence, the No Pull act of pulling is the indicator that an item of Workwork was matched to available workers and flows through a kanban system when we have well matched work order or items of WIP flow happened. with suitable staff to add valuable new G D knowledge and progress work E completion. to I dja@djaa.com, @agilemanager Done
    41. 41. Variety & Specialization increase WIP Pool of Ideas ∞ K L As a DeployEngin- result, there will be a minimum level of WIP ment eering required to facilitate flow. For systems Testing Development with inherent liquidity problems - lots Ready of Ready 4 5 Done heterogeneity in work types or variance in Ongoing Verification Acceptance 4 ∞ demand for quality (non-functional requirements) and|or lots of specialists workers, non-instant availability problems or No Pull J variability in skill and experience of workers, then the WIP in the system will need More WIP increases liquidity & freely. to be larger in order for work to flow The liquidity measure will not rise until the G increase flow! D E WIP rises. And Cost! I F Pull Pull dja@djaa.com, @agilemanager Done
    42. 42. Liquidity is measured as volume of pull transactions Thus, I am proposing that system liquidity be measured as the volume of pull transactions happening in a given time period. dja@djaa.com, @agilemanager
    43. 43. Normalizing Liquidity Measures To normalize this figure across multiple systems, we could divide it by the number of workers involved, or the (fixed) cost of running each system over a time period. This would give us pull transactions/person Or, pull transactions/€ dja@djaa.com, @agilemanager
    44. 44. Pull Transactions / Person Greater values for pull transaction volume serve to show us the most trustworthy system. They represent the system most likely to offer the most predictable results. dja@djaa.com, @agilemanager
    45. 45. Characteristics of Liquid Markets A liquid financial market would exhibit several characteristics… Tightness – bid-ask spread Immediacy - how quick an order is filled Breadth - ability to handle large orders Depth - processing orders at different prices Resiliency - ability of the market to swing back to normal or adjust after a surge in orders off the market or one large order that moves the price.... dja@djaa.com, @agilemanager
    46. 46. Characteristics of a Liquid Kanban Market A liquid kanban system would exhibit these characteristics… Tightness* – variance between customer expectations and probability of meeting it within current lead time capability (Due Date Performance???) Immediacy – flow efficiency or waiting time until pull** Breadth – variety of types of work handled Depth – variety of risks under management (and depth of taxonomies) Resiliency - ability of the system to recover to normal or adjust after a surge in orders breaching WIP constraints or swarming on expedite orders… * Is this even relevant without a market maker? ** Some work still required to determine whether time blocked should be included or not dja@djaa.com, @agilemanager
    47. 47. Liquidity of the system should be considered against observed capability before placing an order Some kanban systems may appear faster and cheaper but carry more inherent risk as they have poorer liquidity, handle less variety, are less resilient (can’t cope with or recover from burst traffic) Slightly longer to deliver but with greater certainty may be preferable to a system with a lower average lead time but poorer liquidity & greater risk dja@djaa.com, @agilemanager Observed Capability
    48. 48. Liquidity is a Good Metric Our measure of liquidity, as pull transaction volume per person or unit of currency in a time period, meets Donald Reinertsen’s criteria for a useful global Liquidity is ametric… system measure. Simple Self-generatingup should not cause Driving it Relevant optimization or undesired local Leading Indicator consequences! dja@djaa.com, @agilemanager Observed Capability
    49. 49. Relevance of Liquidity as a Measure Little’s Law So our plans carry less buffer for variation Narrow spread of variation in lead And time for a fixed WIP means a more predictable delivery rate. This is Our planning horizons turn means greater predictability on delivery date for a given volume be shorter! of work and therefore a more accurate price. dja@djaa.com, @agilemanager can
    50. 50. Improving Liquidity through Labor Pool Flexibility Engineering Ready Teams 3 F Cost Reducer s Spoilers 2 1 3 Development Testing 3 Verification Acceptance Steven Brian Done Ongoing Done flexibly across rows on the board to keep work flowing G GY Differenti ators 1 3 It’s typical to see splits of Promotions from fixed team workers versusjunior team member to flexible flexible system workers Joe Dworker with David of between 40-60% an avatar P1 clearly visualize why a pay PB DE rise is justified. Flexible Peter Roughly half the labor E Rhonda workers help manage Generalist or T-shaped pool are flexible workers MN people who can move liquidity risk better! AB Ongoing 2 Table Stakes Team LeadAnalysis Joann Ashok Junior who will be rotated through all 4 teams dja@djaa.com, @agilemanager
    51. 51. Conclusions dja@djaa.com, @agilemanager
    52. 52. Kanban enables new powerful approaches to risk management in knowledge work Kanban systems enable us to visualize many dimensions of real business risks. Kanban is enabling the practical with capacity Hedging risks is possibleapplication of allocation in the system real option theory and related concepts like real liquidity dja@djaa.com, @agilemanager
    53. 53. Lean Risk Management is Pragmatic Qualitative approaches to risk assessment are fast, cheap and drive consensus Stop speculating about business value and ROI. There is no crystal ball gazing! Risk Instead assess real risks analysis is not speculative! and design kanban systems to manage them! dja@djaa.com, @agilemanager
    54. 54. Thank you! dja@djaa.com, @agilemanager
    55. 55. About David Anderson is a thought leader in managing effective software teams. He leads a consulting, training and publishing and event planning business dedicated to developing, promoting and implementing sustainable evolutionary approaches for management of knowledge workers. He has 30 years experience in the high technology industry starting with computer games in the early 1980’s. He has led software teams delivering superior productivity and quality using innovative agile methods at large companies such as Sprint and Motorola. David is the pioneer of the Kanban Method an agile and evolutionary approach to change. His latest book is published in June 2012, Lessons in Agile Management – On the Road to Kanban. David is a founder of the Lean Kanban University, a business dedicated to assuring quality of training in Lean and Kanban for knowledge workers throughout the world. dja@djaa.com, @agilemanager
    56. 56. Acknowledgements Raymond Keating of CME Group in New Jersey has been instrumental as a collaborator on the ideas in this presentation. Real liquidity emerged as an idea from discussions on real options theory with Chris Matts, Olav Maassen, Mike Burrows and Julian Everett over a period totaling greater than six years. Some final refinement of the concepts came about as a consequence of a conversation with Jon Jagger in October 2012. dja@djaa.com, @agilemanager
    57. 57. David J Anderson & Associates, Inc. dja@djaa.com, @agilemanager
    58. 58. Appendix dja@djaa.com, @agilemanager
    59. 59. Identifying Buffers Pool of Ideas Engineering Ready Ongoing 2 F GY 3 Done verification Acceptance I am a buffer! P1 PB I 3 D G Testing Development Deployment Ready DE The clue isis in my name “… The clue in my name – – E Ready” “… Ready” MN AB I am buffering non-instant availability or activity with a availability or an activity with acyclical cadence cyclical cadence dja@djaa.com, @agilemanager ∞ Done
    60. 60. Infinite Queues Decouple Systems Pool Enginof eering The infinite queue Development decouples Ideas Ready the systems. The deployment 3 Done Ongoing system uses batches and is 2 separate from the kanban system F The 2nd commitment is actually a commitment for PB the downstream deployment system DE Deployment Ready Testing 3 Verification Acceptance D ∞ MN G P1 E AB The Kanban System gives us confidence to make that I downstream commitment GY 2nd Commitment point dja@djaa.com, @agilemanager Done
    61. 61. Change Requests The psychology of a probabilistic approach can be challenging… I don’t want to take the risk of being longer than 60 days. Mean I need a precise estimate of when it 50 days will be delivered! 98% at 150 days 85% at 60 days dja@djaa.com, @agilemanager
    62. 62. A lack of organizational social capital… A lack of organizational social capital may prevent trust in the kanban system from There isemerging. The result is a degeneration to a a trust in individual people rather than the system. Individuals are held system. deterministic accountable via their commitments. Everything must have an estimate. Plans are Deterministic planning means a high likelihood drawn deterministically. Overhead and rework of incurred as things (of plans) isbroken promises. change. Early and specific commitments are requested People take the blame! dja@djaa.com, @agilemanager
    63. 63. …replace trust with comfort & reassurance Deterministic planning provides a level of When people take the blame, replacing the comfort. Deterministic plans seem accurate and people provides a level of comfort that plausible. remedial action has been taken. When promises are broken it further The organization is caughtsocial capital in the undermines the in a vicious cycle of distrust, individual organization. commitment, disappointment, blame and repercussions! dja@djaa.com, @agilemanager
    64. 64. Liquidity in the housing market Sellers dja@djaa.com, @agilemanager $100 Bank Buyers
    65. 65. Liquidity in the housing market Sellers $100 Bank Buyers Cash $100 dja@djaa.com, @agilemanager
    66. 66. Fixed Date Intangible Standard Expedite Example Distributions dja@djaa.com, @agilemanager
    67. 67. dja@djaa.com, @agilemanager

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