Storytelling with Data (Data Visualization) www.pwc.com Storytelling with Data (Data Visualization) June 12, 2014

Jason Josko Data Solutions, PwC Over 14 years of experience helping clients transform their underlying data into actionable intelligence, focusing on large scale data analytics, visualization, reconciliation and data quality assurance. Helps Internal Audit teams develop their analytics strategy as well as conduct targeted audit analytics. Experience developing procurement compliance programs, dashboard reporting packages, and working capital improvement solutions. BS in Accounting from University of Iowa Interests and Passion:   Storytelling with Data - Data Visualization June 12, 2014

Paba DMello Data Solutions, PwC Over 6 years of experience in data analytics Focus on Data Visualization and understanding business analytics needs of the clients Experience in integrating information from multiple data sources a efficiently executing assignment using dynamic tools. Involved in data cleansing, data preparation and visualization stages of a project BS in Computer Science from University of Mumbai, India Interest and Passion:   Storytelling with Data - Data Visualization June 12, 2014

Kate Reva Data Solutions, PwC Over 4 years of industry experience in corporate accounting and data analytics Focus on Data Analytics to facilitate External and Internal Audit engagements as well as Fraud Analytics and Data Visualization tools Served clients in a variety of industries, including financial services, manufacturing, insurance, pharmaceuticals, consumer products and technology BS in Accounting from DePaul University CISA certified Interests and Passion:   Storytelling with Data - Data Visualization June 12, 2014

Today’s Discussion Data Creates Opportunities What are the benefits, characteristics and value of Data Visualization Analytics? Analytics in Action QlikView and Tableau case study and live demonstration of analytics through data visualization Data Visualization Tool Landscape What are the key players? What is the difference between them? Storytelling with Data - Data Visualization June 12, 2014

Data Creates Opportunities Storytelling with Data - Data Visualization June 12, 2014

Data Visualization What is it? Data Visualization is an emerging area of data analytics that combines quantitative information with technology and graphical design to tell stories, convey ideas and make decisions. An exciting new way to incorporate raw information into a visual interactive medium A way to dissect increased volumes of rows and columns of information to understand trends, patterns and make strategic, operational and tactical decisions A powerful way to simplify the ever increasing size and complexity of information Storytelling with Data - Data Visualization June 12, 2014

Data Visualization Why is it a hot topic? Data discovery became a mainstream BI and analytic architecture - Gartner Provide an intuitive, interactive user experience with immediate response time, and eliminate the need for training and IT assistance. Increase user autonomy with self-service discovery of relevant insights – anytime, anywhere Help business users see the big picture while navigating the details – for fully informed decisions Empower users to uncover connections and trends in new and unexpected areas Storytelling with Data - Data Visualization June 12, 2014

Data Visualization Data to Insight Quickly answers questions: Which product-region pair is the best seller? Which product-region pairs have high sales but lose money? Storytelling with Data - Data Visualization June 12, 2014

Data Visualization Data to Insight Quickly answers questions: Which product-region pair is the best seller? Which product-region pairs have high sales but lose money? Storytelling with Data - Data Visualization June 12, 2014

Benefits of Data and Visual Analytics Traditional Approach vs Visual Analytics Static queries and reports Takes time to adjust and refresh Reduces the time spent creating analysis Faster and more informed decision making Core Capabilities of Visual Analytics Trending analysis Collaborative data discovery Better understand Relationships Interactive charts and reports Shorter time to insight KPI monitoring Identify Prove Scale Repeat Clean Data Define Baseline Hard Analytics Soft Refine Analysis Quick Hits Baseline Time Performance Storytelling with Data - Data Visualization June 12, 2014

Characteristics of analytics today Analytics; discovery and communication of meaningful patterns in data Big data; collection of large and complex data sets Data Financial, Operational Structured, Unstructured, Internal, External Visualization Trending & comparisons Accessibility and portability; available anytime, anywhere Dashboarding Storytelling with Data - Data Visualization June 12, 2014

Analytics in Action: Tableau Product Pricing Override Audit Storytelling with Data - Data Visualization June 12, 2014

Auditing Approach Leveraging Data Analytics Business Development 1 5 4 2 3 Foundation Fieldwork Quality Reporting Planning Foundation: Leverage data to identify key risks to be addressed through the Audit Plan Planning: Plan and scope the audit to focus on high risk areas and newly identified risks Fieldwork: Develop risk based and value added analytics for the audit Reporting: Analyze results to quantify impact, and report findings utilizing data visualization Quality: Monitor managements responses through Dashboards Storytelling with Data - Data Visualization June 12, 2014

I. Foundation: Risk Assessment Issue Analyze financial data to gain insight over declines in net revenue. Internal audit identified product pricing as a key risk area Action Analyze key financial data and adjust their audit plan to address their high risk areas. Impact Annual quarter over quarter revenue decline Storytelling with Data - Data Visualization June 12, 2014

II. Planning: Project Risk Assessment Issue Varying gross margins across 3 retail channels Utilized data visualization software to analyze the stores by retail channel. Action Identified limited controls around product price overrides/adjustments have been identified Impact Unexpected spikes in price overrides Storytelling with Data - Data Visualization June 12, 2014

II. Planning: Audit Scoping Issue Identify high risk stores affecting gross profit through the use of overrides Utilized data visualization software to analyze the total price override amounts against gross profit to identify outliers and anomalies Action Identified stores that had negative gross profits or negative overrides Discovered that products can have price overrides that result in losses Impact Negative gross profit due to price overrides Storytelling with Data - Data Visualization June 12, 2014

III. Fieldwork: Targeted Analytics Testing Instances where the override amount is less than the cost of the item. Total amount and frequency of overrides by store and sales associate. Total amount and frequency of overrides by override code. Trending of overrides by store over the audit time period. Override reason codes leading to negative gross profit Storytelling with Data - Data Visualization June 12, 2014

IV. Reporting: Confirm and Report Results Internal Audit team determined there were no controls around overrides of product prices Sales associates overriding to negative gross profit Sales associates entering in negative override amounts Outlier of sales associate with potential unusual activity Storytelling with Data - Data Visualization June 12, 2014

V. Quality: Remediation Follow Up Issue Monitor managements response to the findings of the pricing audit Utilized data visualization software to leverage the analytics and dashboards created during the assessment, scoping, and testing phases Action Ability to continuously monitor the compliance in a consistent manner with minimal manual effort Impact Storytelling with Data - Data Visualization June 12, 2014

Analytics in Action: QlikView KPI (Key Performance Indicators) Dashboard Storytelling with Data - Data Visualization June 12, 2014

KPI (Key Performance Indicators) Dashboard Enable effective Risk- Based Internal Audit Approach Improve the cost and effectiveness of audits Uncover trends in new and unexpected areas Develop KPI Dashboard in QlikView Identify High Risk Areas Directly communicate with data Refresh Data on monthly basis KPI Dashboard to be included as part of the Risk Assessment package See the big picture while navigating the details – for fully informed decisions Enable Continuous Monitoring Storytelling with Data - Data Visualization June 12, 2014

Data Visualization Tool Landscape Storytelling with Data - Data Visualization June 12, 2014

Who are some of the key players? - Gartner BI magic quadrant Source: Magic Quadrant for Business Intelligence and Analytics Platforms. February 20, 2014 http://www.gartner.com/technology/reprints.do?id=1-1QLGACN&ct=140210&st=sb Storytelling with Data - Data Visualization June 12, 2014

Limited data mining and analytic capabilities Governance, consistency and skill silos challenges Limited data mining and analytic capabilities Lower licensing costs per user Connects to a variety of data sources Low cost to implement Easy to use for ordinary business users and developers Strengths Strengths Strengths Strengths Higher annual maintenance fee Cautions Cautions Source: Magic Quadrant for Business Intelligence and Analytics Platforms. February 20, 2014 http://www.gartner.com/technology/reprints.do?id=1-1QLGACN&ct=140210&st=sb June 12, 2014

Limited data mining and analytic capabilities Security and administering large number of users concerns Limited data mining and analytic capabilities Mobile functionality Associative search function Relatively low cost of ownership Highly customizable and easy to use Strengths Strengths Strengths Strengths Higher developer learning curve Cautions Cautions Source: Magic Quadrant for Business Intelligence and Analytics Platforms. February 20, 2014 http://www.gartner.com/technology/reprints.do?id=1-1QLGACN&ct=140210&st=sb June 12, 2014

Limited data mining and analytic capabilities Support quality and cost of software concerns Limited data mining and analytic capabilities Higher quality (stability, reliability and free from bugs) Enterprise deployment readiness Easy to use for end users Advanced modeling and building analytical models Strengths Strengths Strengths Strengths Limited formatting options Cautions Cautions Source: Magic Quadrant for Business Intelligence and Analytics Platforms. February 20, 2014 http://www.gartner.com/technology/reprints.do?id=1-1QLGACN&ct=140210&st=sb June 12, 2014

Contact Information Jason Josko Office: (312) 298-3146 Email: jason.k.josko@us.pwc.com Paba DMello Office: (312) 298-5183 Email: prabhavi.dmello@us.pwc.com Kate Reva Office: (312) 298-4496 Email: ekaterina.v.reva@us.pwc.com