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TDWI Best Practices Awards 2016 Winner Summaries

Category: Analytics and Data Science

Toyota Financial Services

One of the toughest questions any company can ask itself is, “Do we really know what our customers want?” With 13 million customer interactions per month, customer information dispersed across multiple applications (billing, payment, services, and marketing) as well as numerous unstructured interactions (logs, call center notes and audio, and surveys), getting to the answer can seem daunting. To begin with, we need to identify our customer experience pain points; assess the current and future customer needs; and determine which customer channels provide the best returns.

By applying machine learning and Toyota’s Kaizen philosophy of improvement, TFS performed, what we call, a digital genba walk (an observation of work) by combing through millions of customer interactions per month, parsing out insights, and diagnosing root causes of problems. Both supervised and unsupervised machine learning methods were employed on over 12 TB of customer data, which enabled TFS to better understand the customer voice and map the customer journey.

The genba walk has allowed for effective, efficient, and automated identification of process improvements. TFS is now able to explain channel usage, identify pain points, predict future behavior, and prescribe recommended actions, resulting in significant financial savings. Machine learning has also allowed for an automated performance measurement system for planning new improvements, setting targets, checking results, and providing course corrections.

Category: BI and Analytics on a Limited Budget

Oregon State University

Supported with existing resources and staff, the Cooperative Open Reporting Environment (CORE) system is a 21st century business intelligence solution for Oregon State University. The six participants formed the Business Intelligence Center (BIC), which successfully re-architected the data warehouse and built the infrastructure to support next-generation university BI practices.

Throughout CORE development and design, university subject matter experts provided short-term assistance to the BIC team. The engagement of data owners to create agile data governance has created a position- and role-based security access model that makes data readily available to employees—with a user-centric design for meaningful reports in formats that meet informational needs.

The evolution of CORE continues and has shifted the long-standing centralized control of university data and information. CORE will become the standard—the only source for accurate information. During this era of limited resources for public universities, additional funding for CORE is not anticipated. This small band of “misfits” will continue to engage users, broadly communicate the CORE story, and develop a reporting and analytics system that informs tuition and fees, budgets, and student metrics for years to come.

Category: BI, Search, and Data Discovery

Microsoft

Microsoft’s Finance Business Intelligence and Finance Cross Service Platforms IT teams partnered to create and deliver on a vision to provide an innovative enterprise-level Measure Management Service (M2) through a three-year initiative. Currently 18 months into that journey, Microsoft’s Sales and Marketing Group (the first adopter of the M2 service) is seeing dramatic gains in data quality, timeliness, and business measure publishing support. 

Other Microsoft groups are preparing to implement M2 to take advantage of the service’s ability to easily define, maintain, and change their measure definitions and calculations; mesh with governance and data steward processes; and provide and manage source data from various systems. The groups that implement Microsoft’s M2 will find a service that provides the timely, high fidelity, highly governed business performance measures widely used by Microsoft decision makers to measure company performance-to-target, leading indicator trends, and forecasts.

Microsoft’s M2 Service initiative continues to deliver on the vision set forth 18 months ago—and by delivering a complete set of innovative services that help business leaders and decision makers understand and monitor business performance, and guide business decisions to improve that performance, M2 intends to make a big mark at Microsoft.

Category: Big Data

Verizon Wireless

The rise of big data created unprecedented challenges in providing Verizon employees with data-driven decision-making capabilities.

The goal was to manage internal and external data with powerful and secure storage and processing solutions at a relatively low cost—while providing more employees, in both the IT and business organizations, with access to data.

We extended our analytics ecosystem to integrate big data discovery with existing analytics capabilities to give employees access to data and insights via easy-to-use tools that facilitated widespread adoption, data discovery, and analysis at scale. The result: Integrated big data helps drive our Verizon Lean Six Sigma (VLSS) program, reduce churn, improve customer satisfaction, and lower business costs—leading to billions in measurable benefits.

Some specific benefits include:

  • Verizon Wireless leads the industry in customer loyalty with the lowest retail postpaid churn rate among all carriers at 0.96 percent.
  • Increased self-service and millions of fewer calls in 2015.
Add a Line (AAL)—big data platform analyzes behavior, propensity models predict most likely device for each customer and CRM launches multichannel AAL campaigns to target customers with best device offer. The result: A significant increase in AAL gross adds in 2015 representing millions in monthly revenue.

Category: Data Management Strategies

VMware, Inc.

Solution Sponsors: SAP

Our program began with the realization that VMware needed to manage data as a true, reliable corporate asset. We created a vision for master data management (MDM) to invoke a hub-and-spoke, publish-and-subscribe architecture with embedded information governance and data quality measures. This was initially implemented on Oracle platforms, but we are in the process of migrating our ERP and MDM capabilities to an SAP multi-domain platform. We have completed the first phase with a new vendor master using SAP Master Data Governance and continue to drive value in the legacy environment, given a 2-3 year migration plan to SAP.

The success of our data management program is due to the active support of the information governance business and IT community, which agreed to includeindividual, annual performance goals for information governance—the framework that drives vision into value. Moving from reactive data cleanup to proactive data management and governance requires extensive change management around business practices and processes. The technical part, however, is easy compared to the people side of change management. Constant education, along with understanding the value achieved, is key to maintaining the necessary participation.

We have discussed our program with many peer organizations that have not achieved a comparable level of success in their data management and information governance programs. We believe that VMware’s success makes us pioneers in managing data as a true, reliable corporate asset

Category: Emerging Technologies and Methods

Arizona State University Analytics & Data Services (co-winner)

Solution Sponsor: Snowflake Computing

Arizona State University’s Self-Service Analytics Initiative, launched at the beginning of 2013 and completed in the fall of 2014, has brought a revolutionary change to the way that data is accessed, manipulated, and published around the institution.

The core goal of the project was driven by an increasing demand for university data across all of ASU’s departments, administrative units, and leaders. With this goal in mind, the University Analytics & Data Services Team created their vision: to provide an easy-to-use, Web-based reporting platform that facilitates efficient access to data.

To meet this challenge, the initiative developed a two-tier solution leveraging the Microsoft BI stack of tools. For power users and the analytics team, the initiative selected tabular and multidimensional modeling tools (SSAS, PowerPivot) to curate, organize, and publish data sets. For casual users and other university constituents, the team developed a custom-themed SharePoint environment designed to host analytics assets as various as Excel Web Services, SSRS, Tableau, and Splunk.

With this combination, Arizona State has created an innovative self-service environment that meets the needs of its constituency and leaves room for the addition of new tools and methods as soon as they become available.

IAC Publishing Labs, operator of Ask.com (co-winner)

Solution Sponsor: Snowflake Computing

By completely transforming its relationship to the data upon which it depends, IAC Publishing Labs’ BI team went from business barrier to business value creator. The legacy data environment simply could not keep pace with IAC Publishing Labs’ rapid growth.

Cloud data warehouses represent the leading edge of analytics and BI innovation. By choosing to replace its legacy environment with the cloud-based Snowflake Elastic Data Warehouse, IAC Publishing Labs immediately jumped to the forefront of modern best practices.

Achievements include:

  • Establishing one source of truth in a centralized data warehouse that serves both data scientists and business analysts and provides value across all the company’s businesses
  • Consolidating technologies and eliminating outmoded systems, which has given the data greater responsiveness and usefulness and lowered IT costs
  • Providing enhanced BI service levels because the data environment is more consistent and responsive
  • Enhancing visibility into the data analytics for business executives and marketing teams as well as data scientists and BI experts
  • Changing the BI team from a cost center to a value center and making it a respected, often-consulted resource within the company
  • Significantly decreasing expenses (by 78 percent) for the data warehouse environment

Category: Real- and Right-Time Operational Intelligence

Aircel Limited, India

In today's Indian prepaid mobile market, understanding a subscriber’s interests, needs, preferences, and consumption patterns in real time and providing personalized products and services across all customer touchpoints is a unique strategic advantage. With this in mind, Aircel initiated a project to capture customer transactions in near real time and to leverage that data for event-based actions, as well as to update customer profiles for use by various touchpoints, campaign systems, and the end-user community.

By virtue of having customer consumption and network usage data available in real time, Aircel is committed to recommending services and products best suited to the needs of every customer. A few examples of business value derived with this solution include:

  • A campaign management system that leverages the Unified User Profile (UUP), increasing monthly revenue by more than $7 million by promoting best-fit offers to selected customer segments
  • The ability for retailers to fetch best-fit recharge options for prepaid customers in real time (on USSD channel), generating more than $18 million intertiary revenue
  • Realizing synergy among network teams and sales and marketing by having a single view of network and business KPIs in near real time