Implementing a successful metrics system

Dec 16, 2013Download as PPTX, PDF1 like542 views

Implementing a successful metrics system in an IT company involves defining goals and key performance indicators from both a top-down and bottom-up approach. Quality metrics should track factors like cost of quality, defects, and rework trends over time. Regular collection and analysis of metrics on projects, processes, and people can provide insights into trends and areas for improvement. Both business objectives and individual project success can be better managed through an iterative process of planning, collecting, analyzing, and evolving organizational metrics.

Implementing a successful metrics system in an IT company
Muntean Ramona
Measurements & Best Practices @ISDC

IT��S IMPORTANT TO YOU
IT��S REDUCING UNCERTAINTY
TELLS YOU MORE THAN YOU KNEW BEFORE

Better informed decisions
Tracking the progress of the objectives
Managing the achievements of goals

WE CAN MANAGE WHAT WE CAN EASILY MEASURE

GOALS

Goal

Business growth rate
Profit margin
Bids success rate
Personnel turnover

Success
Factors

SUCCES FACTORS

Key Performance
Indicators

Productivity
Predictability
Quality
Competitiveness
Client Satisfaction
Employee Satisfaction

Metrics / Data

Projects, Processes, People

TOP DOWN APPROACH �C COMPANY GOALS

QUALITY
Cost of Quality
(CoQ)
Cost of Appraisal
(CoA)

Reviews (1st time)
Code
Requirements
Design
Test plans, test scripts

Testing (1st time)
Audits

Cost of Prevention
(CoP)

Training
Procedures, methods
Tools, systems
Planning
Quality improvement
Measurements

Cost of Non-Conformance
(CNC)

Fixing defects
Re-work code review
Re-work doc review
Re-reviews
Re-testing

Improve

KPI��s
Productivity
Predictability
Quality
Client Satisfaction
Team Satisfaction

Metrics,
Trends
Key Performance
Indicators

METRICS ANALIZED
Velocity: Story Points/sprint
Estimation deviation
%Re-work, DDR, CoQ trends
Demo / Release success score

Tooling, Data

Projects, Processes, People

BOTTOM UP APPROACH �C PROJECT��S KPI

TRENDS
Story Points done / sprint
60
55
50
45
40
35
30
25
20
15
10

55
43

41

43
32
29
23

22

S4

S5

S6

S8

S9

S10

22

S11

S12

S13

TRENDS
Defect Detection Rate (DDR)
90.00%

We can learn how
review is
influencing the
product quality in
correlation with
defects found by
testers.

80.00%
70.00%
60.00%
50.00%
40.00%
30.00%
20.00%
10.00%
0.00%

S4

S5

S6

DDR_Review

S7

S8
DDR_Testing

S9

S10

S11

DDR_Customer

S12

S13

DEVELOPING MEASUREMENT PROCESS
DO

PLAN
Define procedures:

Collect metrics:

- Metrics to be collected
- Collection practices & tooling
- Analysis & reporting
- Feedback integration

- Tailor procedures (if the case)
- Record and store data
- Use proper tools & templates
- Check data accuracy

Identify scope:
- Goals, objectives
- ��Problems�� that need answer
- Measurements needs

Evolve process:
- Evaluate progress
- Evaluate process
- Recommend improvements

ACT

Analyze metrics:
- Aggregate, correlate data
- Prepare reports
- Discuss trends, identify thresholds
- Revise procedures

CHECK

MEASUREMENT PARADOX?
I want a car that uses as little petrol as possible.
I have chosen 2 cars and will do 3 test drives with both of them.
Test drive 1

Test drive 2

Test drive 3

Average

Car A

1 km/l

1 km/l

4 km/l

2 km/l

Car B

1.5 km/l

1.5 km/l

1.5 km/l

1.5 km/l

Test drive 1

Test drive 2

Test drive 3

Average

Car A

1 l/km

1 l/km

0.25 l/km

0.75 l/km

Car B

0.667 l/km

0.667 l/km

0.667 l/km

0.667 l/km

The car that uses less
petrol is car A which does
more kilometres per litre.
But, if I had measured
litres per kilometre, car B
uses less litres per
kilometre and is the better
car.

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Implementing a successful metrics system

1. Implementing a successful metrics system in an IT company Muntean Ramona Measurements & Best Practices @ISDC

2. IT��S IMPORTANT TO YOU IT��S REDUCING UNCERTAINTY TELLS YOU MORE THAN YOU KNEW BEFORE Better informed decisions Tracking the progress of the objectives Managing the achievements of goals WE CAN MANAGE WHAT WE CAN EASILY MEASURE

3. GOALS Goal Business growth rate Profit margin Bids success rate Personnel turnover Success Factors SUCCES FACTORS Key Performance Indicators Productivity Predictability Quality Competitiveness Client Satisfaction Employee Satisfaction Metrics / Data Projects, Processes, People TOP DOWN APPROACH �C COMPANY GOALS

4. QUALITY Cost of Quality (CoQ) Cost of Appraisal (CoA) Reviews (1st time) Code Requirements Design Test plans, test scripts Testing (1st time) Audits Cost of Prevention (CoP) Training Procedures, methods Tools, systems Planning Quality improvement Measurements Cost of Non-Conformance (CNC) Fixing defects Re-work code review Re-work doc review Re-reviews Re-testing

5. QUALITY TRENDS

6. Improve KPI��s Productivity Predictability Quality Client Satisfaction Team Satisfaction Metrics, Trends Key Performance Indicators METRICS ANALIZED Velocity: Story Points/sprint Estimation deviation %Re-work, DDR, CoQ trends Demo / Release success score Tooling, Data Projects, Processes, People BOTTOM UP APPROACH �C PROJECT��S KPI

7. TRENDS Story Points done / sprint 60 55 50 45 40 35 30 25 20 15 10 55 43 41 43 32 29 23 22 S4 S5 S6 S8 S9 S10 22 S11 S12 S13

8. TRENDS Defect Detection Rate (DDR) 90.00% We can learn how review is influencing the product quality in correlation with defects found by testers. 80.00% 70.00% 60.00% 50.00% 40.00% 30.00% 20.00% 10.00% 0.00% S4 S5 S6 DDR_Review S7 S8 DDR_Testing S9 S10 S11 DDR_Customer S12 S13

9. DEVELOPING MEASUREMENT PROCESS DO PLAN Define procedures: Collect metrics: - Metrics to be collected - Collection practices & tooling - Analysis & reporting - Feedback integration - Tailor procedures (if the case) - Record and store data - Use proper tools & templates - Check data accuracy Identify scope: - Goals, objectives - ��Problems�� that need answer - Measurements needs Evolve process: - Evaluate progress - Evaluate process - Recommend improvements ACT Analyze metrics: - Aggregate, correlate data - Prepare reports - Discuss trends, identify thresholds - Revise procedures CHECK

10. MEASUREMENT PARADOX? I want a car that uses as little petrol as possible. I have chosen 2 cars and will do 3 test drives with both of them. Test drive 1 Test drive 2 Test drive 3 Average Car A 1 km/l 1 km/l 4 km/l 2 km/l Car B 1.5 km/l 1.5 km/l 1.5 km/l 1.5 km/l Test drive 1 Test drive 2 Test drive 3 Average Car A 1 l/km 1 l/km 0.25 l/km 0.75 l/km Car B 0.667 l/km 0.667 l/km 0.667 l/km 0.667 l/km The car that uses less petrol is car A which does more kilometres per litre. But, if I had measured litres per kilometre, car B uses less litres per kilometre and is the better car.

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Implementing a successful metrics system

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