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Generating Insight from Big Data in Retail
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Transcript of Generating Insight from Big Data in Retail
CK EDIWWORKING withInfrastructure 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
W ICK ED
http://www.energy.ox.ac.uk/wicked/W ICK 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.
W ICK ED
http://www.energy.ox.ac.uk/wicked/W ICK 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)
W ICK ED
http://www.energy.ox.ac.uk/wicked/W ICK 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 2015Source: Sweett Group, Verco, UCL, & Energy Foundation. 2014. Operational Energy Use and the Use of 'Bigger, Better Data". GCB230. Green Construction Board: London
The Opportunity
W ICK ED
http://www.energy.ox.ac.uk/wicked/W ICK 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
W ICK ED
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Clustering load profiles using Bayesian analytic techniques
W ICK ED
http://www.energy.ox.ac.uk/wicked/W ICK ED
W ICK ED
http://www.energy.ox.ac.uk/wicked/W ICK 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
W ICK ED
http://www.energy.ox.ac.uk/wicked/W ICK ED
W ICK ED
http://www.energy.ox.ac.uk/wicked/W ICK 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.
W ICK ED
http://www.energy.ox.ac.uk/wicked/W ICK 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.