Business Insight and Big Data Maturity in 2014

Size: px

Start display at page:

Download "Business Insight and Big Data Maturity in 2014"

Dominic Bryan
6 years ago
Views:

1 Ben Nicaudie 5th June 2014 Business Insight and Big Maturity in 2014 Putting it into practice in the Energy & Utilities sector

2 blues & skills issues A disproportionate portion of the time spent on analytics projects is about data preparation: acquiring/preparing/formatting/normalising the data In addition to raw data, augmented data/analytical assets can significantly speed up the analytics process and partially bridge the talent gap

Business scenarios we see Subject matter experts want access to their

access information using their terminology with an underpinning of protection

Marketeer seeking data for new campaigns.

Supporting analysis and decision making.

3 Business scenarios we see Subject matter experts want access to their organization s data to explore the content, select, control, annotate and access information using their terminology with an underpinning of protection and governance. Scientists seeking data for new analytics models. Marketeer seeking data for new campaigns. Fraud investigator seeking data to understand the details of suspicious activity. Day-to-day activity. Requiring ad hoc access to a wide variety of data sources. Supporting analysis and decision making. Using the subject matter experts terminology. Providing the flexibility of spreadsheets that can scale to large volumes, a wide variety of information types whilst protecting sensitive information and optimizing data storage and provisioning.

The interesting dilemma A man goes into a jewellers and buys an expensive watch Is it

bank must report it Threat Obligation Does he have an expensive trophy wife in which

Has he just won the lottery should the bank improve the services offered?

There is major overlap in the data required to answer the question.

4 The interesting dilemma A man goes into a jewellers and buys an expensive watch Is it fraud in which case the bank must stop it Is it money-laundering in which case the bank must report it Threat Obligation Does he have an expensive trophy wife in which case perhaps he would be interested in a loan? Has he just won the lottery should the bank improve the services offered? Opportunity The same event is of interest by different departments. There is major overlap in the data required to answer the question. It may not be possible to determine the answer with just the information in the channel - Previous or subsequent activity is required It is all a matter of coordination and timing

5 What is a data lake? A Lake provides data to an organization for a variety of analytics processing including: Discovery and exploration of data Simple ad hoc analytics Complex analysis for business decisions Reporting Real-time analytics It is possible to deploy analytics into the data lake to generate additional insight from the data loaded into the data lake. A data lake manages shared repositories of information for analytical purposes. Each Lake Repository is optimized for a particular type of processing. Real-time analytics, deep analytics (such as data mining), exploratory analytics, OLAP, reporting, Lake Services Lake Repositories Management and Governance Fabric Lake values may be replicated in multiple repositories in the data lake. However the data lake ensures the copying and updating of this data is managed and governed using well-defined information supply chains. in the data lake can be accessed through different types of interfaces and provisioning mechanisms provided the Lake Services.

6 lake logical architecture Deploy Real-time Decision Models Service Calls Export Import Deploy Decision Models Understand Sources Advertise Source Understand Compliance Events to Evaluate Advanced Provisioning Catalog Interfaces Understand Sources Notifications Federation Calls Service Calls 2 Refineries 1 Lake Repositories 4 Analyst Interaction Search Requests Curation Interaction Service Calls Export Out In Import Inter-lake Exchange Report Queries 3 Integration & Governance Lake Management

7 lake logical architecture Deploy Real-time Decision Models Service Calls Export Import Deploy Decision Models Understand Sources Advertise Source Understand Compliance Events to Evaluate Notifications Federation Calls Service Calls Out In Refineries Real-time Analyics STREAMING ANALYTICS Real-time Interfaces Publishing Feeds Ingestion Descriptive Shared Operational Deposited Harvested Advanced Provisioning CATALOG ASSET HUB CONTENT HUB INFORMATION WAREHOUSE DEEP DATA INFORMATION VIEWS ACTIVITY HUB OPERATIONAL STATUS CODE HUB Catalog Interfaces Lake Repositories Analyst Interaction Access Find Curate Access Provision Reporting Marts Understand Sources Search Requests Curation Interaction Service Calls Export Import Inter-lake Exchange Report Queries Integration & Governance INFORMATION BROKER CODE HUB STAGING AREAS OPERATIONAL GOVERNANCE HUB MONITOR WORKFLOW Management Lake

Key usage patterns for have emerged in Energy & Utilities How can I detect and act on power outages before customers call?

Smart Metering How can I anticipate asset failures and predict the need for maintenance?

utility Analysis of Time Series energy usage, flag & event data combined with other customer asset & work data North American natural gas distributor Correlated

8 Key usage patterns for have emerged in Energy & Utilities How can I detect and act on power outages before customers call? Grid Operations How can I use smart meter information to improve customer service? Smart Metering How can I anticipate asset failures and predict the need for maintenance? Asset & Workforce Management Utility company in Italy Captured and analyzed data from grid sensors for a comprehensive view of grid performance North American utility Analysis of Time Series energy usage, flag & event data combined with other customer asset & work data North American natural gas distributor Correlated data from multiple sources to better plan and deploy inspection, detection, maintenance, repair and replacement resources and personnel 99.9% faster problem diagnosis by providing a comprehensive, nearreal-time view of the grid Saved $176M as a result of capital investment & operations savings 25% improvement in crew utilization and 10-15% fuel savings

9 Client Engagement Approach DEATH OF THE SALESMAN?

10 CAMS acquisitions seen as essential for our growth Growth Initiatives Acquisitions (since 2008) Cloud Network automation 2010 Automated data migration 2012 Cloud integration 2010 Protection and recovery 2008 Mobile Customer Engagement 2013 base-as-aservice 2014 Analytics Governance, compliance, risk management 2010 Financial governance 2010 Business intelligence and Perf. mgt warehouse appliances 2010 Financial risk management 2011 Master data management 2010 Predictive analytics 2009 Automated BI 2013 navigation & exploration 2012 Compensation & sales performance mgt 2012 Customer & network analytics 2013 Mobile Mobile computing platform 2012 Mobile mgt 2010 Web fraud detection 2013 Mobile customer experience management 2012 Mobile Customer Engagement 2013 Mobile Device Mgt 2013 Social Small business server solutions 2008 Hosted, multilingual service 2009 Talent Management 2012 Smarter Commerce B2B integration 2010 Enterprise marketing mgt 2010 Customer experience mgt 2012 Pricing, promotion and product mix optimization 2012 Procurement & contract mgt 2011 Web fraud detection 2013 Web analytics 2010 Cloud based market automation 2014

11 Our engagement model aims to benefits our clients by addressing three key questions critical to their success Opportunity Identification Expertise Engagement Model Customer View Do you understand my problem? Do you have the expertise to solve my problem? Can you engage and mobilize quickly and easily? Method Response Use a common language to simplify our message and frame offerings that demonstrate our understanding Ensure our methods are comprehensive and leading edge in all areas relevant to our increasingly informed clients Provide flexible and componentized offerings to accelerate and support our client teams and anticipate future trends

12 Applying data and analytics in day to day operations STRATEGIC ASSET MANAGEMENT

13 Asset Management impacts all aspects of our clients, and increasingly uses data from many sources.. this is driving a need for increased use of a wide range of analytics in the asset management space

14 New capabilities required Asset Managers are continually looking to improve the way they maintain and develop their assets Level of Excellence V. Total Productive Maintenance Better asset operation, maintenance and replacement decisions IV. Reliability-based Maintenance Improved ability to review and report asset and network performance END-TO-END PROCESS VISIBILITY CONSISTENT, QUALITY DATA Ability to optimise an integrated delivery plan in real time III. Predictive Maintenance II. Preventive Maintenance Better and easier asset and operations data capture and sharing AND INTEGRATED PLANS Improved planning and construction portfolio and Alliance management I. Run to Failure Maintenance the pursuit of excellence means the extent of our ability to collect, share and analyse information is key to improvement

15 So, how can we be smart and easy to use..? To investigate, we went back to first principles Analytics Sophistication performance management strategic planning Use structured and unstructured data Numeric Text Image Audio Captured Detected Inferred Made consumable and accessible to everyone, optimized for their specific purpose, at the point of impact. What happened? Reporting How many, how often, where? Questioning What exactly is the problem? Visualisation What actions are needed? Decision support What could happen? Simulation What if these trends continue? Forecasting What will happen next if? Predictive Modelling How can we achieve the best outcome? Optimization How can we achieve the best outcome and address variability? Stochastic Optimization Video Management Descriptive Analytics Predictive Analytics Prescriptive Analytics

16 Thank you Questions?

Fred Balboni Global Leader, Business Analytics and Optimization IBM Corporation. Delivering Breakaway Performance Business Analytics and Optimization

Fred Balboni Global Leader, Business and IBM Corporation Delivering Breakaway Performance Business and Increasing the organization s level of analytical sophistication allows an organization to build breakaway