Presentation at the Westminster Sustainable Business Forum organized Roundtable on Big Data and the Built Environment at Portcullis House, 12th October 2015

1. CK
IWWORKING with
Infrastructure Creation of Knowledge and Energy strategy Development
http://www.energy.ox.ac.uk/wicked/
1
Generating Insight from Big Data in Retail
Prof David Wallom

2. W I
CK
ED
http://www.energy.ox.ac.uk/wicked/W I
CK
ED
What do you consider Big Data to be?
Big data is a broad term for data sets so
large or complex that traditional data
processing applications are inadequate.
Challenges include analysis, capture, data
curation, search, sharing, storage, transfer,
visualization, and information privacy.

3. W I
CK
ED
http://www.energy.ox.ac.uk/wicked/W I
CK
ED
14 July 2015
Scale matters
for problems and solutions
in the built environment
“stock” at the city, national, international scale
The building
(or leaseable unit)

4. W I
CK
ED
http://www.energy.ox.ac.uk/wicked/W I
CK
ED
The Challenge
 In UK, £1.7 Bn of energy
consumed is not managed
 Large businesses waste around
15% of energy due to lack of
efficiency measures
 £5Bn spent on new buildings
each year, which use 2-3 times
more than designed
 Return on investment (ROI) of
48% available for many measures
 Effective management will
reduce risk and increase security
of supply
 Market transformation via
  Awareness of problem
  Understanding of technical
performance
  Opportunities for socio-
technical change
14 July 2015
Source: Sweett Group, Verco, UCL, &
Energy Foundation. 2014. Operational
Energy Use and the Use of 'Bigger, Better
Data". GCB230. Green Construction Board:
London
The Opportunity

5. W I
CK
ED
http://www.energy.ox.ac.uk/wicked/W I
CK
ED
What can analytics say about energy usage?
 Turning Data into Actionable Information;
 Predicting and classifying costs when there is a shift in the type of
tariff, e.g. shifting to a real-time tariff from a fixed price tariff.
 Clustering of load profiles, determining behaviour type and
response by the consumer
 Determining fundamental drivers of energy consumption

6. W I
CK
ED
http://www.energy.ox.ac.uk/wicked/W I
CK
ED
Clustering load profiles using Bayesian analytic
techniques

7. W I
CK
ED
http://www.energy.ox.ac.uk/wicked/W I
CK
ED

8. W I
CK
ED
http://www.energy.ox.ac.uk/wicked/W I
CK
ED
Normalised daily
power demand
profiles for all
businesses by sector
Commercial energy consumption and real time
pricing
 Analyse the impact of introduction of time-of-use and real-
time pricing strategies

9. W I
CK
ED
http://www.energy.ox.ac.uk/wicked/W I
CK
ED

10. W I
CK
ED
http://www.energy.ox.ac.uk/wicked/W I
CK
ED
How is big data best collected and stored, and
who ought to have access?
 Data costs, to both move and store, BIG DATA costs A LOT!
 Maximise value of data once you have it by making it uniformly
accessible to business functions
 Increasingly common that energy information is handled on
behalf of the retailer by a third party contractor.
 Lack of standards in all aspects of data formats
 Changing energy management provider is an epic task.
 Example, we have partnerships within WICKED with four
different retailers, four different configurations of data and
inconsistent metadata.

11. W I
CK
ED
http://www.energy.ox.ac.uk/wicked/W I
CK
ED
 Retail uses analytics regularly in sales, now it can move to
other parts of the business,
 Answer fundamental questions on efficacy of operational
changes w.r.t energy
 Connect consumption to overall business performance.