A Presentation Delivered to the Senior Management Board of the NWDA on Data Stewardship and the Impact of Data-Driven Evidence-based PolicyMaking at Business Link Northwest

1. “How Evidence can
influence policy and the
role of Business Link in
the North West”
A Presentation to
Business Link Northwest
by
Ged Mirfin

2. Definition
“Data-driven decision-
making is using data
to better understand
what is actually going
on rather than what is
assumed to be going
on”

3. The Curse of Bad Data
•Data is now far easier & cheaper to gather, store, analyze and disseminate than ever
before
•Unfortunately this means that it is much easier to collect data that is inaccurate, out-
of-date or at worst simply wrong
•Results in a lack of trust of data by end-users
•Decision-makers are thus forced trust to their own intuition.
•Tendency to rely on the infallibility of their own “judgemental opinion” because it is
simple & convenient.
•Results in a “Traditionally it has always been done that way mentality”.
•No one is able to prove conclusively otherwise or show policymakers they are wrong.
•The result – badly formulated and more poorly applied policy!
•Works fine in a benign economic environment. In a harsher climate when assumptions
are being fundamentally challenged it is much more difficult to defend the indefensible
and to find a solution when you are sometimes forced to justify not only your very
existence but the funding rationale!
•Need for Hard evidence: high quality validated quantitative data
•Is why Policymakers have turned to a data-driven approach

4. Governing by Numbers: Data-driven
evidence based policymaking: what is it?
•Collection and analysis of data to spotlight problem areas and
potential solutions – data capture & accessibility!
•Development of quantifiable measures & indices to assess
policy performance and draw comparisons across similar
circumstances, geographical boundaries or peer groups so
“best practice” can be identified & widened – segmentation &
benchmarking!
•Public dissemination of data and metrics/indices to assist in
policy formulation, policy making and ultimately in assessing
the impact of policy and policy performance – should it be
done? has it been done? and has it been done well?

5. Data Driven Evidence-based Policy
Formulation
Evidence- Evidence-
influenced based
BLNW Data Warehouse
Experian
Aim: Facilitate change
Northwest
from Anecdotal &
Business Judgmental to
Evidence-based
Database Policy formulation
Evidence-
Opinion-based influenced
Political Inputs Policy Making Environment

6. +100% Building of Data
Lack of clean
+90%
BLNWs Capability Levels: Warehouse to
separate and
up-to-date
prospect
report on new data
marketing data
delivers highly
+80% How Data has affected this functional web
begins to impact The
on BLNW’s development of
accessed granular
+70% ability to meet a Web
reporting capability
Data Import into CRM penetration Accessed
+60% - manually fills the targets Reporting
system with very poor Dashboard with
+50% quality & aged data the ability to
from legacy systems. represent data
+40% via GIS Mapping
BLNW Capability
software and the
+30% development of
a Marketing
Data
+20%
Warehouse
Arrival of taking BLNW
+10% Experian NBD Reporting &
Poor attempt to with access to Analytical
0% address data quality Yell, Thomson, Capabilities to
CRM 3 – Powerful issue via “Data Commercial, & the Next Level.
-10% Engine. Huge Cleanse” carried out Origins Mosaic
Development by Third Party results gives BLNW
Potential. Vanilla in the overwriting of access to a rich
-20% Version no current data with
Customisation. even older data. This
Rate data source
which it can be
-30% affected CRM system segmented to
and hampered target specific
-40% operational customer details
performance in a scientific
-50%
manner
-60% 1% -1%
-70%
-80% Source: Morgan Stanley as at 30 June 2006
-90%
-100%

7. Experian’s NBD
536k
100k
-Experian profiled Business Link data and found 536k
businesses (both Ltd. And unincorporated) at location in its
-Business Link had 100k company records in its
National Business database for the Northwest.
database.
-Business Link acquired the data from Experian. Each Experian
-The companies had been assisted by Business Link over
record had in excess of 180 data characteristics (appends)
the last 20 months
-The extra data records allowed a significant level of analytics to
-The data captured was used to satisfy contract outputs
be done. The data had access to classification systems (YELL
and as such was very specific Thompson) and allowed for detailed segmentation
-We needed to increase the data set both in terms of size -One of the Primary data attributes was “Risk Scores and
and data richness Financial Performance data”

8. Data Attributes
•Data is “real time” - updated monthly and in case
Commercial Risk Data the plan is fortnightly with Weekly
Alerts for Businesses experiencing a serious worsening in
their performance
•Is the first (b2b) business profiling system in the public
sector
•Offers real time intelligence to support our efforts to
address the current market conditions
•Data is very granular and can be segmented to very
specific levels
•Key data segmentation is geographic (down to postcode)
and sectoral (RES, SIC group, Yell classification code,
Thompson directory classification code)

9. Benefits to Key Stakeholders
Marketing Operations Executive Cluster Orgs. NWDA
Build increased Improve take-up Meeting of Make definitive Provision of
penetration of intensive Strategic pronouncements relevant and up-
amongst assists for Priorities: To be about the to-date
service users Broker Team by recognized as effectiveness of information on
through increasing lead the leader on BLNW services emerging
delivered to the business trends
improved generation regional
NW Business allowing the
segmentation business
Community NWDA to service
and targeting intelligence and including requests from
playing a vital Membership & Government,
role in Cluster Orgs, Local Political Parties
informing Councils, & Lobbying Orgs
business Politicians &
support policy Opinion Leaders
making
“Advanced “Vastly “Delivering “Sharing of Key “One Version of
Customer Improved Lead Strategic Data across the the Truth”
Segmentation” Quality” Priorities” Region”
INTERNAL The Business Support Environment EXTERNAL

10. Data becoming more relevant
for decision making bodies
Internal
Sector specialists
and cluster
management
teams
First interaction
with third party
data consumers
and political
oganisations

11. Dependency building
Business Support Community Partners look to BLNW for Data
& Analysis as their first point of call
Internal Sector
Geographically
dispersed bodies
require data to
confirm Business
support activities
or to quantify the
impact of future
plans and policies

12. Allows Business Support
Community Partners to
Engage with Decision Makers
on an Evidence-Based Basis
Internal Sector Geography
Local hierarchy of
business support
functions demand
input to decision
making and
assessment of
economic impact.
The User Base is Being Significantly Widened

13. The Response to companies in the North West
adversely affected by the current economic downturn
The BPI (“Business Performance Index”: A Consolidation of
Business Intelligence
Internal Sector Geography Local
Govt. Demand for joined up
information sources and
“one version of the truth”
among all business
support organisations.
Tie together regional
strategy and delivery with
a system of quantifiable
evidence based results

14. The BPI: Identifying High Risk Businesses
Risk Category Description
Maximum risk High value of unsatisfied CCJs, accounts overdue, start-up
business with adverse data, proprietor with adverse data or
maiden accounts show loss
High risk Large company with weak balance sheet, medium sized firm with
very weak balance sheet, combination of above average risk
features, start-up with adverse trading
Above Large company with very weak balance sheet, medium to small
average firms with (high levels of credit search, payment difficulty, weak
balance sheets), start-up firm without adverse information
The BPI Portal: The Hub of the Action for
Response Framework
• Experian/BLNW – Business Performance Index Structured
Intelligence that can be immediately disseminated to partners
• Business Link to provide region-wide data-pool and reporting at
Regional, Sub-regional and Local levels

15. The Action for Response Hub
Figure 1 Data Capture >20 Redundancies
within 90 days
CLUSTERS
& TRADE
ASSOCIATIONS NWDA
TUC / UNIONS HR1 to BERR
LOCAL JOB CENTRE
AUTHORITIES PLUS
BUSINESS LINK
DATA WAREHOUSE
SUB-
GOVERNMENT
REGIONAL
OFFICE NW
PARTNERS
RECORD BY COMPANY BUSINESS
CHAMBERS OF Company Name LINK NW
COMMERCE Registered Number
Company Address
Local Authority & Ward
Sector
Turnover & GVA Estimate
No. of Perm employees
No. of Jobs at Risk
ESTABLISH RAPID RESPONSE TEAM
DEVELOP STRATEGY /POLICY FOR
SUPPORTING COMPANIES IN CRISIS
COMMUNICATE STRATEGY /POLICY TO
PARTNERS (JCP, LSC, BLNW, TRADE
ASSOCIATIONS ) & INTERNAL PARTNERS

16. The Power of the BPI: Project Rapier – Liverpool Vision’s Objective
of Spending £10M to Save 40 Businesses specifically in the Retail
Sector by End Q1 2009
• How do you Identify a……………………..
•…Company that is at least of
Above Average Risk
•Which is based in Liverpool
•Which Employs 50 or more
Liverpool (13,704) Employees at Site
•Specifically in the Central Ward
•Which is in the Retail Sector
•Whose payment profile is
Employs 50 or more (207) deteriorating
Central Ward (66) £729.71 £48,309.18 £151,515.15
In Retail Sector (4)
Deteriorating Payment Profile (1) £2.5M £10M
This information is based on data provided by Experian. The data has been subject to further analysis by Business Link North West.

17. And that Business was?
• Demonstrates that the
Liverpool Vision’s
approach needs
revising
• Also demonstrates
that coordinated
action by Local
Authorities has the
ability to provide
financial assistance to
some of the big High
Street Retail Chains if
they so wished

18. Data Driven Evidence-Based: BLNW
Making an Impact
Decision Making Based on Intuition, Judgemental Opinion or
Data Driven Evidence-based Decision Making
Tradition
Joined-Up programmes based on highly focussed
Disjointed programmes and policy initiatives targeted strategies to address identified need based on
documented evidence
Budget allocations to programmes based on data-
Budgetary decisions based on prior practice and historic priorities
informed needs
Spending allocations based on volume of voices of special Spending allocations based on market failure gaps as
interests and eligibility criteria of existing regimes indicated by the data
Detailed reporting on a range of indices to relevant
Generic reports to all stakeholders based on historic aggregate stakeholders on a regularised basis - weekly, fortnightly,
data inappropriate for policymaking at a a micro-economic level monthly, quarterly, half yearly based on agreed service
level agreements
Goal setting based on accurate estimates of the
Goal-setting by board members, administrators, project managers financial consequences of proposed policy options
with special treatment given to pet projects and initiatives or the allowing for prioritisation thus helping to predict the
current fads of the day. impact of policy options to stakeholders in a “winners
and losers” format
Highly focussed report-back and monitoring forums
Death by committee: Undue focus on ensuring that money is spent which ensure that not only is money spent well but also
and that it is seen to be spent that the impact of spending can be tracked and
measured