• Like
  • Save

Why UK Utility Suppliers Can Get 'Smarter' with Advanced Analytics

  • 1,926 views
Uploaded on

In the face of deregulation, green consciousness, and smart metering, UK energy suppliers are increasingly turning to a holistic approach to analytics. Some major approaches include distributed; …

In the face of deregulation, green consciousness, and smart metering, UK energy suppliers are increasingly turning to a holistic approach to analytics. Some major approaches include distributed; offshore, on-site; front-end, back-end; and Centre of Exellence models.

More in: Business
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
  • I have read uku utility supplier is smarterby advance analytic ,very nice one .i like to know its supply power ,gas in u.k information ,it any load shelling ,
    Are you sure you want to
    Your message goes here
No Downloads

Views

Total Views
1,926
On Slideshare
0
From Embeds
0
Number of Embeds
1

Actions

Shares
Downloads
0
Comments
1
Likes
1

Embeds 0

No embeds

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
    No notes for slide

Transcript

  • 1. • Cognizant 20-20 InsightsWhy UK Utility Suppliers Can Get ‘Smarter’with Advanced Analytics Executive Summary per payment method. It has also proposed to standardize the format of these tariffs, with Utility suppliers in the UK operate in an increas- suppliers allowed to compete on a single “per ingly complex environment driven by ever- unit” price. Consumers would then be able to escalating demands on capital, continually tell at a glance whether they can save money evolving technology and continuously changing either by switching suppliers or by moving to a regulations. new deal. This is expected to impact over 75% The UK electricity and gas sector, in particular, of customers who are on standard products. is amongst Europe’s most competitive markets, • Growth and heritage systems challenges. addressing the energy needs of approximately 29 Given the competitive nature of the market, million customers. The industry is deregulated and controlling operational costs and improving consists of numerous big-to-medium suppliers. By efficiency have emerged as top priorities for nature, deregulation brings fierce competition, suppliers. By and large, operational inefficiency and the supply side of this market is no different. is caused by legacy IT systems that have not Since May 1999, all customers, whether they are kept pace with suppliers’ torrid growth, which domestic, commercial, or industrial, are eligible has created unintended waste and redundancy. to change their gas or electricity supplier. In fact For example, many suppliers struggle to obtain during 2010, 17% of electricity consumers and a single view of the customer, which leads to 15% of the gas consumers switched suppliers.1 numerous operational shortcomings in some basic functions (i.e., debt collections, customer Three major issues have emerged: service, etc.). This directly impacts the top and bottom line of suppliers. • Deregulation is fuelling increased com- petition. Ofgem, the government body that • The advent and pressures of smart meters. regulates the electricity and gas markets in Among the key benefits of proliferating smart Great Britain, is pushing for even more compe- meters placed across the UK’s power generation tition to bring down any barrier to switching. grid is the access suppliers will have to a large On the back of its recent Retail Market Review, amount of accurate billing data (50 million new Ofgem has recommended that to make it meters will be added over a seven-year period 2). simpler for domestic consumers to compare This data will enable suppliers to increase prices and choose a better deal the number billing accuracy, customize their offerings (e.g., of tariffs for standard evergreen products time of use (ToU) tariffs) and reduce opera- from each supplier be restricted to only one tional costs. Suppliers could optimally use cognizant 20-20 insights | february 2012
  • 2. From Data to Insights Sales Channel Campaigns Revenue Cross-sell Up-sell Lifetime Cost to Customer Customers Value Churn Serve Segment Experience Loyalty Products Pricing Margin Competition Portfolio Capacity Operations Planning Forecasting Leakage Effectiveness Performance Vendor Efficiency OptimisationFigure 1 this data to deliver more customer value (i.e., Creating Competitive Advantage by more relevant and “greener” services), thereby Applying Analytics Holistically increasing customer loyalty. Analytics is one tool suppliers can leverage toGiven these challenges, suppliers will need to address market-driven challenges. Traditionally,differentiate and take necessary steps to breed suppliers’ business processes generate a streamcustomer loyalty and increase efficiency. Inaction of useful data collected during the entire meter-means that the gap between proactive and to-cash operating cycle.reactive suppliers in this market will only widenat a faster rate. This white paper discusses the As a result, a variety of analyses can be conductedrole analytics can play in making UK utilities which can individually and collectively deliversuppliers smarter about how they move forward extremely useful business insights (see Figure 1).to seize market opportunities. It also covers These insights can inform a series of actions andvarious models that can be deployed to leverage drive the overall strategy of any given supplieranalytics, depending on supplier maturity and (Figure 2).risk profile.Holistic Approach to Analytics Strategy Action Business Initiatives, Tracking Enterprise Metrics, Balanced Scorecard, Strategy Maps Advanced Analytics Insight Predictive & Optimisation Modeling, Business Processes Analysis, Functional Analysis BI/Reporting Information Data Mining, OLAP Modeling, Performance Reporting, Dashboards, Scorecard Data Integration & Management Data Data Warehousing, Data Quality, Master Data Management, Metadata ManagementFigure 2 cognizant 20-20 insights 2
  • 3. Historically, supplier organisations have used Holistic Approach to Analyticsanalytics on an ad hoc basis. This “ad hoc-ism”originated from the fact that analytics weretriggered by discrete events. For example, thecustomer service team might want an analysis Demographicsof agent handling time (AHT) in order to reduceoperational costs. Although this analysis mightlead to certain actions which reduce AHT,enacting these measures may directly impact Risk Valuean individual agent’s ability to cross- or up-sell Customercustomers (these customers would have to Lifetimehave been identified through a different set of Indexanalyses). Hence, the need for a more holisticapproach to analytics (see Figure 3). Cost to Loyalty ServeBut with fierce competition, coupled with thedeluge of data, utilities are beginning to realizethe benefits of a holistic approach. We illustratethis through an example. A customer’s lifetimevalue can potentially combine a variety of factors Figure 3such as demographics (age, location, segment,etc.), value (consumption, tariff plan, range ofproducts purchased, etc.), cost to serve (debt,customer contact, call center operations, etc.), Challenges to Implementationloyalty (renewals, stickiness, net promoter score) The previous example showcases the efficacyand risk (churn and payments). of a holistic approach to analytics. In the UK’s competitive energy markets, suppliers are con-In our opinion, this represents an optimisation tinuously seeking more innovative and effectiveproblem that can be resolved progressively. ways of operating to gain market share. TheyTo start with, we can optimise the individual work hard to understand market dynamics,parameters in each silo and then integrate the customer behaviour and their impact on internalprocesses over the medium to long term (see activities, but their inability to identify andFigure 4).Progressive Optimisation Approach Tackle more holistic Optimise at the parameters in medium term organisation level in Customer Lifetime Index the long term Long Term Demographics Value Cost to Serve Loyalty Risk Time scale Customer Consumption Contact Cost Debt Call Centre Churn Account Medium Segmentation Analysis Servicing Modelling Receivables Term Market/ Tariff Plan Online/ Agent Offline Early/ Late NPS Product Analytics Collections Efficiency Theft Segmentation Efficiency Short Cross Sell/ Contact Debt Agent Term Up-sell Reduction Servicing Handling Time Analytics Contact Efficiency In short term, optimise the individual point-based parametersFigure 4 cognizant 20-20 insights 3
  • 4. Analytics’ Challenges Organisation Process People Technology Analytics is not seen as Structuring of analytics Lack of proficiency in Unavailability of data at a lever for supporting function to optimise only quantitative methods granular levels. corporate innovation. a single business area. applicable for utilities. Analytics is not classified Focus on current and Unclear career pro- High cost of technology as a distinct capability. future goals rather than gression and lack of for enterprise-wide historical trends across mentorship. solution. enterprise. Unclear roles and respon- Insights from analytics More confidence on Over-reliance on sibilities for modelling are tested only for experience and intuition technology as an between IT and analytics. limited business areas. rather than facts. analytical solution. Deployment of multiple Inability to select right Focus on meeting Inability to validate data point solutions in data and in right format individual or business integrity and quality at an isolation rather than for analysis. unit’s objectives rather enterprise level. looking at the big picture. than working towards a balanced scorecard model. Lack of single view of Focus on incorrect or Time to design an customers and relating unnecessary metrics. enterprise-wide analytics them to customer solution. segments. Not involved in planning Relating analytics to Complexity involved in process of strategising KPIs of a business area integrating data from for business units/propo- and not on multiple multiple sources. sitions. aggregated levels.Figure 5correct inaccurate/inconsistent data typically Various Operating Modelscreates misalignment between expectation and for the Analytics Functionresults. Multiple data sources and disparate silos As analytics emerges as a key ingredient forof data often mean individuals or business units organizational success, different variations ofare using different information than their coun- operating models have emerged that can beterparts, which generally results in misleading or deployed depending on the supplier’s maturitycomplicated messages for stakeholders. There and business goals. The effectiveness ofis also an opportunity cost due to their inability any of these models also depends on seniorto identify potential or existing customers who management buy-in and application for tactical/can be acquired or retained to maximise value, strategic decision-making.rather than targeting each and every one withgeneric offers and gaining minimal conversion.Key analytics challenges faced by suppliers are • Distributed model: Different functional or business units have separate groups that collectsummarised in Figure 5. and analyse data. This is the easiest model to implement but it brings with it a very immatureAs utilities move towards providing products approach to analytics, especially where variousand services for smarter homes and businesses, business units within the supplier’s organisa-they are also making significant investments in tion intersect with one another. For example,new technologies that will streamline data and a customer can be considered an existing orprocesses. IDC’s “2011 Vertical IT & Communi- potential residential, business and servicescations Survey” found that 86.7% of utilities account, all at the same time.worldwide had invested in analytics and overone-third have been able to demonstrate positive • Offshore/On-site model: An on-site or cus-business benefits.3 However, most organisations tomer facing team is used for data gathering,are a long way away from achieving “analytical scoping, model creation and liaising with func-maturity.” tional or business areas while offshore teams cognizant 20-20 insights 4
  • 5. generate reports based on these models and “social media analytics,” “predictive analytics,” interpret outcomes for decision-making. “Web analytics,” “customer value analytics” and “real-time decisioning,” which take the analytics• Front-end/Back-end model: Responsibility for discipline to another level. With these techniques, analytics and providing meaningful insights is utilities can obtain more real-time, accurate split between external facing and operational and effective ways of delivering meaningful and teams. Data related to customers, competi- relevant insights and foresights that have the tors, suppliers and industry are analysed by potential to project/predict customer behaviour. a front-end team for decision-making related to sales, marketing, campaign management Due to the growing importance of collecting and and customer experience. At the same time, analysing vast amount of data there is a logical a back-end team works on data related to call shift from the distributed or individual functional volumes, agent performance, cost and opera- area level analytics to a more enterprise-wide, tional activities. corporate-level model. Suppliers can adopt a• Centre of Excellence model: A corporate progressive approach to building analytics with centre of excellence (CoE) supervises the enter- a view toward getting to a level where analytics prise-wide collection of data and analysis. The can be provided as a service to various stakehold- CoE helps individual business units with their ers in the organisation. From ad hoc analytics, specific analytics requirements and provides suppliers can move into complete processes and the latest and most relevant insights. Individual then to platform-based enterprise-wide function- business units/functional areas are assigned ality (see Figure 6). members from a central pool of resources for providing analytics and business intelligence. Conclusion These members can work on a project or Given shifting regulatory sands, the proliferation business as usual (BAU) mode, depending on of smart metering and a greater green conscious- the requirement. All resources report to the ness that is sweeping the business and consumer central pool and can be redeployed in other worlds, UK utilities have reached a major shift areas of business when necessary. Knowledge point. management and communication between BUs As such, holistically harnessing the power of and the CoE is the key to success in this model. enterprise analytics, across various silos andEffective implementation and management of data functional areas, can enable them to reduce oper-or information depends on the ability to collect, ational costs and achieve greater levels of opera-analyse, interpret and act quickly and effectively. tional agility, while more effectively meeting newMost organisations are not only working on data regulatory and market mandates, with minimalfrom traditional sources, but embracing emerging operation disruption.Taking Analytics to a Higher Plane Analytical Outsourcing & Analytics- Analytical Outsourcing & as-a-Service Analytics-as-a-Service Analytical Analytical Applications & Platforms Applications Increasing & Platforms Analytical Maturity Joining, Leaving and Movement, Analytics Maturity In-process Meter, Billing & Consumption, Business Payment & Collections Analytics Commercial, Risk & Fraud Management Basic Customer Service Ad Hoc Analytics Analytics Services Ad Hoc Analytics Energy Analytics TimeFigure 6 cognizant 20-20 insights 5
  • 6. Energy suppliers that attempt to leverage establish analytics practices will determine whichanalytics without consistent and accurate companies achieve fact-based advantage in ainformation will struggle to compete and miss fast-changing and ultra-competitive environ-emerging business opportunities. The speed ment. Inaction will only widen the gap betweenwith which supplier organisations adopt and proactive and reactive suppliers.Footnotes1 http://www.ofgem.gov.uk/Markets/RetMkts/rmr/Documents1/IpsosMori_switching_omnibus_2011.pdf2 http://www.ofgem.gov.uk/Media/FactSheets/Documents1/consumersmartmeteringfs.pdf3 http://www.teradata.com/WorkArea/DownloadAsset.aspx?id=170134 http://www.gartner.com/it/content/1322300/1322319/april_7_top_5_technology_trends_to_disrupt_crm_ ethompson.pdfAbout the AuthorsArvind Pal Singh is a Senior Manager within the Energy and Utilities Practice of Cognizant BusinessConsulting. He has more than 13 years of energy industry and consulting experience and has led andexecuted multiple consulting engagements. At present, Arvind leads Cognizant’s UK E&U ConsultingPractice. He holds a master’s degree in international business and an engineering degree. He is also aTOGAF certified Enterprise Architect. Arvind can be reached at Arvindpal.Singh@cognizant.com.Vinitesh Gaurav is a Senior Consultant within the Energy and Utilities Practice of Cognizant BusinessConsulting. He has more than five years of consulting and business analysis experience, working withUK and European customers in the energy and utilities, insurance and reinsurance industries. Hisareas of expertise include customer acquisition and retention, customer self-service, smart metering,business energy management, billing, energy services, service-oriented architecture, e-commerce andWeb technologies. He has an MBA in systems and marketing and an engineering degree in computerscience. He is also a certified Prince 2 practitioner and Agile Scrum Master. Vinitesh can be reached atVinitesh.Gaurav@cognizant.com.About Cognizant’s Energy & Utility PracticeCognizant’s Energy & Utilities (E&U) Practice is among the company’s fastest growing business units. Backed by strongfocus and commitment to service delivery excellence, our E&U practice has established a unique position for itself bydelivering strategic blueprints, technology frameworks and innovative consulting solutions to various players acrossthe global energy and utilities industry. In addition, we provide vital business transformation, process optimization andinformation management solutions across the industry value chain.About CognizantCognizant (NASDAQ: CTSH) is a leading provider of information technology, consulting, and business process out-sourcing services, dedicated to helping the world’s leading companies build stronger businesses. Headquartered inTeaneck, New Jersey (U.S.), Cognizant combines a passion for client satisfaction, technology innovation, deep industryand business process expertise, and a global, collaborative workforce that embodies the future of work. With over 50delivery centers worldwide and approximately 137,700 employees as of December 31, 2011, Cognizant is a member ofthe NASDAQ-100, the S&P 500, the Forbes Global 2000, and the Fortune 500 and is ranked among the top performingand fastest growing companies in the world. Visit us online at www.cognizant.com or follow us on Twitter: Cognizant. World Headquarters European Headquarters India Operations Headquarters 500 Frank W. Burr Blvd. 1 Kingdom Street #5/535, Old Mahabalipuram Road Teaneck, NJ 07666 USA Paddington Central Okkiyam Pettai, Thoraipakkam Phone: +1 201 801 0233 London W2 6BD Chennai, 600 096 India Fax: +1 201 801 0243 Phone: +44 (0) 20 7297 7600 Phone: +91 (0) 44 4209 6000 Toll Free: +1 888 937 3277 Fax: +44 (0) 20 7121 0102 Fax: +91 (0) 44 4209 6060 Email: inquiry@cognizant.com Email: infouk@cognizant.com Email: inquiryindia@cognizant.com©­­ Copyright 2012, Cognizant. All rights reserved. No part of this document may be reproduced, stored in a retrieval system, transmitted in any form or by anymeans, electronic, mechanical, photocopying, recording, or otherwise, without the express written permission from Cognizant. The information contained herein issubject to change without notice. All other trademarks mentioned herein are the property of their respective owners.