Metrics in project management

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Metrics Examples for Project Management

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To reinforce Magento team with some ideas about metrics and their usage in project management

To share positive knowledge

Goal

'To know your future you must know your past‘George Santayana, a philosopher

Year 1944. The US Third Fleet, under the command of Admiral "Bull" William Halsey aboard the USS New Jersey, began moving toward the Philippines Islands. The admiral decided to find a short way through the Calamian Islands. He sent a spy plane to make some photos of the route. After having analyzed the photos experts discovered that shapes of some islands differed from previous ones….

In the early morning, fleet of bombers took off towards a target area some 350 miles away from their carriers. At the time it was the longest range air raid in history. At 09.00 the Planes reached Busuanga Island, found 15-18 large Japanese enemy ships anchored in CORON BAY. 45 minutes later it was all over, the planes returned home leaving behind a hell of burning oil, explosions and sinking vessels….

Preface

Preface

Now a quick question:

How do you think, Admiral William Halsey was good at mastering metrics or not?

Preface

I think yes because he:

•Was good in analysis and regularly worked on the metrics.•Kept comprehensive historical data of the project he managed•Performed quick and correct action to fix problem that had been showed by the metrics.

Preface

I think yes because he:

•Was good in analysis and regularly worked on the metrics.•Kept comprehensive historical data of the project he managed•Performed quick and correct action to fix problem that had been showed by the metrics.

Preface

Year 2011, our team is doing all their best to successfully deliver the project in time, with high level of quality …

So , let’s go over metrics we use !

Attention : You do not find here real metrics values from our project due to NDA. All the values are made-up

Estimation/Time MetricsEstimation Accuracy (EA)

DescriptionEA shows resulting deviation from original estimations which was made by developers. Could be positive (work took more efforts than planned) or negative when the task was overestimated.

EA = (actual efforts/planned efforts)-1

Estimation/Time MetricsEstimation Accuracy (EA)

History

Feature Size EE 1.10 EE 1.11 Diff.

<100h 1.6 0.9 44%

101-199h 1.3 1.28 1.5%

200+ 1.95 1.7 13%

Conclusion We are becoming better in estimations; however, estimations aren’t very precise so far.


QA MetricsCustomer Reported Unique Defects ratio (CRUD)

Description

CRUD = amount of unique defects which were reported by customers/total amount of bugs

CRUD = 0 means that QA can see the system in the same way as customers do, 100% means we do not have the same system vision with our customers

QA MetricsCRUD

History (July-August 2011)

Conclusion There is a very small positive trend of adjusting our internal QA procedures to customer’s demand.

7/13

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1

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1

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1

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8/1/

2011

28.5

28.6

28.7

28.8

28.9

29

29.1

CRUD(%)

CRUD(%)


QA MetricsBug Density (BD)

DescriptionBug density is a ratio of changed (added or deleted) or total number LOC of code to quantity of unique bugs during defined period of time.

BD = total strings / unique bugs

This metric is a way to express the system’s quality as a function from lines of code and bug amount. The highest quality a system has the bigger value BD gets. Anyway, this metric is useless when is unlinked from time.

QA MetricsBug Density


Conclusion System quality fluctuates now. We need to perform some actions to get strong increasing trend.

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8/1/

2011

490500510520530540550560570580

Bug density(Loc/bug)

Bug density(Loc/bug)


QA Metrics

Critical Mass (CM)

CM shows how many bugs from the total amount are critical.

CM=quantity of critical bugs/total amount of bugs

Only when CM=Zero, Core team makes the release.

QA MetricsCritical Mass


Conclusion The peak on 7/21/2010 is because PO added some bugs to be fixed in the release.

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2011

0

0.5

1

1.5

2

2.5

3

Critical mass(%)

Critical mass(%)


HR Metrics

Total Available Resources (TAR )

TAR = (team size-absent people)/team size.

TAR allows better understanding consequences of team member’s unavailability. For instance, 5 absent people for project of 10 people could be a disaster while 5 people for project of 100 people won’t affect it at all.

TAR = 1 - all is OK, TAR = 0 team is totally absent. Usually, TAR=70 is an edge on which the manager should become worried

HR MetricsTotal Available Resources (TAR )


Conclusion You can see that TAR was on 70% level a few times during this month. That could be a reason of putting off the release for a week.

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1405060708090

100

TAR(%)

TAR(%)


Questions ?

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The end.

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Metrics in project management