Presentation at the Royal Statistical Society Annual Conference, Sheffield 2014. Communication of Statistical Ideas Stream

1. Five Steps for
Analytical Insight
Paul Askew
CONFERENCE
SEPTEMBER 2014
SHEFFIELD

2. Five Steps for Analytical Insight - Contents
A. Context
B. Five Steps
C. Key Message

3. The only statistics you can trust
are those you falsified yourself.
Winston Churchill
Statistical thinking will one day be as
necessary for efficient citizenship as
the ability to read and write.
HG Wells
You cannot ask us to take sides
against arithmetic.
Winston Churchill
The War Office kept three sets of
figures: one to mislead the public,
another to mislead the Cabinet, and a
third to mislead itself.
Herbert Asquith
It is by the art of Statistics that law in the
social sphere can be ascertained and
codified, and certain aspects of the
character of God thereby revealed. The
study of statistics is thus a religious service.
Florence Nightingale
Smoking is one of the
leading causes of statistics.
Fletcher Knebel
If you want to inspire confidence, give
plenty of statistics. It does not matter that
they should be accurate, or even
intelligible, as long as there is enough of
them. Lewis Carroll
A small error at the outset can lead to
great errors in the final conclusions.
Saint Thomas Aquinas
Facts are stubborn, but
statistics are more pliable.
Mark Twain
Errors using inadequate data are much
less than those using no data at all.
Charles Babbage

4. Skills for Life Survey 2011 (England)
Department for Business Innovation and Skills
% Adults at GCSE+ Levels
The numeracy challenge is big and getting bigger…
7.5m
adults with
GCSE+
17m
adults at
primary school
level Maths

5. A Framework for Understanding
Statistical Performance
Paul Askew

6. Policy Gap
Aging Population 2x [36%, actually 16% 65+]
Immigration 2x [31%, actually 13%
immigrant]
Religion 5x [24%,
actually 5% muslim]
Teenage Pregnancy 25x [15%, actually 0.6% under 15 girls
annually]
Benefit Fraud 34x [£24/£100, actually 70p/£100]
RSS & Ipsos Mori

7. Confirmation Bias Clustering Illusion
Hindsight Bias
Overconfidence
Effect
Incentive Super
Response Tendency
Illusion of Control
Endowment Effect
Scarcity Error
Loss Aversion
Cognitive
Dissonance
Hyperbolic discounting
The Art of Thinking
Clearly, Dobelli
Conjunction
Fallacy
Forecast
Illusion
Fundamental
Attribution Error
Contrast Effect
Availability Bias
Outcome Bias

9. Operational
Delivery
Methodological
Leadership

11. ✗ Yes but it’s up
compared the same
month last year
✗ Yes but its up for the
calendar year so far
✗ Yes but they are
reducing faster than we
are this year
Performance Pantomime
✓ Burglary is down compared
to last month
✓ Yes but it’s down overall for the
financial year to date
✓ Yes but we’re still
better than our
neighbours
✓ “Yes but we’re still on target”

12. Five Steps for Analytical Insight - Contents
A. Context
B. Five Steps
C. Key Message

13. B. Five Steps
1. Snapshot
2. Trend
3. Benchmark
4. Trajectory
5. Target

14. 1. Snapshot
5.
Define
6.
Specify
8.
Record
7.
Collect
9.
Enter
10.
Process
12.
Store
11.
Validate
Plan
Implement
Manage
1.
Purpose
2.
Require-ments
4.
Design
3.
Const-raints

15. Aggregated Data
or Real Data
Aggregated Data
This aggregated (averaged)
data is derived from any of
these underlying raw data
examples.
Two month step Three month step Six month step
Increasing Decreasing Increasing convergence
High and low Highs and lows
Decreasing convergence
Smoothed Data – 12 month rolling average
Example Real Data
Notes: Real data for 12 months, previous 12 months is exactly the same, to create 12 month rolling average (mean).

16. 2. Five Steps
1. Snapshot 2. Trend 3. Benchmark 4. Trajectory 5. Target
Purpose Week National Future Estimate
Requirements Month Regional Intervention
Constraints Quarter Neighbours Impact
Design Six Months Similar
Define Annual Specific
Specify FYTD
Collect
Record
Enter
Process
Validate
Storage

17. Value
1. Snapshot – we have a number which is important to us
Time

18. Value
Time
2. Trend – what’s happening over time (s)

19. Value
3. Benchmark – how this measure compares to others
Time

20. Value
3. Benchmark-Trend - comparison to others over time
Time

21. Value
Time
4. Trajectory - the future for our measure

22. Value
Time
4. Trajectory Benchmark - comparison to others

23. Value
Time
5. Target Consideration

24. Five Steps for Analytical Insight - Contents
A. Context
B. Five Steps
C. Key Message

25. C. Key Message
Framework
Multidimensional
measures - times - comparisons

26. C. Key Message
42

27. Five Steps for
Analytical Insight
Thank you
CONFERENCE
SEPTEMBER 2014
SHEFFIELD