Queens University Business Intelligence in the real world Gareth Diamond www.pwc.com.

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Presentation transcript:

Queens University Business Intelligence in the real world Gareth Diamond

PwC Contents 1.Recap on last week's lecture 2.Key Messages 3.Emerging trends in Business Intelligence 4.How clients are implementing BI to realise value 5.Hype versus reality 2

PwC 1. Covered last week 1.What is Business Intelligence and Analytics? 2.Why do businesses need BI&A? In a moment... 3.Business challenges in implementing BI 4.BI isn’t new, so what’s different? 3

PwC 2. What is Business Intelligence and Analytics? Enterprise Reporting Scorecards Mobile BI Business Process Modelling Predictive Analytics Text Mining Data Visualisation Data Mining OLAP Analysis BI Competency Centre Modelling Alerts and Notifications BI Strategy and Roadmap Dashboards Forecasting BI&A is the collective term for strategies, methods and tools that empower an organisation to unlock value from their data. It is the key to an organisation making better decisions using relevant, reliable and timely data. Without it, businesses would make poor decisions based on gut instinct alone. Data Cubes 4

PwC 3. Why do businesses need BI&A? BI&A provides a solution to key client challenges… 5 New Insights – How can I obtain insights that can help pinpoint new revenue-generating opportunities and improve operational efficiencies and visibility across the organization? Spreadsheet Reporting – How do I reduce my reliance on spreadsheets for forecasting or reporting, and reduce resources spent on manual reworking of data? Increased regulatory pressures – How do I provide the necessary reports and analysis to meet future regulatory demands? Relevant, reliable and timely data – How do I ensure I have the right data at the right time to improve my decision- making capability? Optimise IT Investment – How do Optimizing the return on existing business and IT investments such as data management, relationship management and enterprise resource planning technology. Single Version of the truth – How do I get insights on a comparable basis from across the organisation, e.g. a global view of my customer, product or brand.

PwC 6 4. Business Challenges in implementing BI 1.Unclear Business objectives 2.Ownership – CFO, CIO? 3.Business buy-in due to previous failures 4.Business changes 5.Lack of Skills Business Technical 6.Requirements are Technology led 7.Existing technology complexity 8.Data Quality 9.Implementation approach 10.Cost & Return on investment

PwC 7 5. BI isn’t new, so what’s different? 1.Competitive advantage – what value is first mover advantage? 2.Rapidly changing external environment e.g. Market – need to be more competitive and reduce costs Regulations – increasing post the crash on all businesses Shareholders – want better performance and transparency Customers – demanding greater value for money 3. Information overload - ‘drowning in data but starved for knowledge’ (John Naisbitt) 4.Technology investments failing to deliver promised RoI; Lack of business ownership ERP & Operational/’silo’d’ reporting solutions Data is not managed as a corporate asset

PwC Key Messages 1.Business Intelligence, while always important, is now critical to allow businesses to; Manage risk and regulatory challenges Drive operational efficiency Enhance value and revenues 2.Helps businesses overcome the underlying technological complexity 3.Increasing volume of data requires businesses to have good underlying data management 4. Businesses are likely to have different levels of ‘maturity’ in the skills and abilities required to deliver good business intelligence 5.Implementing BI in a business is not easy and has a number of business, and then, technology challenges 8

PwC 1. Emerging trends in BI 9 Drill-Down Reporting Data Visualisation Cloud Computing SOA (Service Orientated Architecture) On-demand Analytics Operational Data warehouses Big Data SaaS/PaaS Master Data Management BI Competency Centres Hardware Analytics Enterprise Information Integration Data Quality Bureau Information Asset Management Competitive Intelligence

PwC 1. Emerging trends in BI – Data 10 Cloud Computing Operational Data warehouses Big Data Master Data Management BI Competency Centres Enterprise Information Integration Data Quality Bureau Information Asset Management

PwC 1. Emerging trends in BI – Data 11 Cloud Computing Operational Data warehouses Big Data Master Data Management BI Competency Centres Enterprise Information Integration Data Quality Bureau Ensuring trusted definition of key information Dedicated skills/business function to support Business intelligence with business and technology skills Information Asset Management Connecting information across the enterprise Data sources containing specific operational data e.g. HR, Finance A means by which to deliver technology – renting rather than owning A service (internal or external) that provides DQ capabilities Utilise ever growing sources and volumes of data to achieve new insight Approach to treat Information as an asset in the same way as £ or staff

PwC 1. Emerging trends in BI – Reporting & Analytics 12 Drill-Down Reporting Data Visualisation Cloud Computing On-demand Analytics Operational Data warehouses Big Data SaaS/PaaS BI Competency Centres Hardware Analytics Competitive Intelligence

PwC 1. Emerging trends in BI – Reporting & Analytics 13 Drill-Down Reporting Data Visualisation Cloud Computing On-demand Analytics Operational Data warehouses Big Data SaaS/PaaS BI Competency Centres Hardware Analytics Software or Platform – as a service Ability to ‘drill’ down from high level report/figures to underlying detail Prebuilt Servers and software bundles, optimised for analytics Having Analytics carried out by a 3 rd party using your Data. Combining and presenting Data using visually rich techniques so as to derive new insight Competitive Intelligence

PwC 2. How clients are implementing BI to realise value CubesData Mart Client Data Analytical Queries Reporting & Analytics Layer Operational Data Store CRM Enterprise Resource Platform Transaction DataOther Data PwC Analytic Team Data Management Data Profiling Master Data Management ETLData Quality Economics Data Warehousing AnalyticsDocument Exports Operational Reports Dashboards Analytical Services Business Intelligence ApplicationsAnalytics Applications Enterprise Information Platform BI&A Platform Source FinanceOperationsPeopleStrategyTechnologyGRC Output Business Intelligence Competency Centre

PwC 5. Hype versus Reality 15

This publication has been prepared for general guidance on matters of interest only, and does not constitute professional advice. You should not act upon the information contained in this publication without obtaining specific professional advice. No representation or warranty (express or implied) is given as to the accuracy or completeness of the information contained in this publication, and, to the extent permitted by law, PricewaterhouseCoopers LLP, its members, employees and agents do not accept or assume any liability, responsibility or duty of care for any consequences of you or anyone else acting, or refraining to act, in reliance on the information contained in this publication or for any decision based on it. © 2011 PricewaterhouseCoopers LLP. All rights reserved. In this document, “PwC” refers to PricewaterhouseCoopers LLP which is a member firm of PricewaterhouseCoopers International Limited, each member firm of which is a separate legal entity. Business Intelligence and Analytics Any Questions?