Implementing Self-Service BI to Improve Business Decision MakingLearn how the Intel Technology Manufacturing Engineering organization is using Microsoft BI tools to help drive innovation at the speed of Moores Law.

Executive Summary Self-service business intelligence (BI) represents a paradigm shift in the way businesses use their data. By enabling end users to combine and analyze large amounts of data, self-service BI provides a pathway to better decision making across the enterprise. Yet effective decision making for core business processes often requires trusted reports that are best developed by centralized teams of experts who can validate data quality and deliver more sophisticated analyses and reports.

This white paper explores the approach used by the Intel Technical Manufacturing Engineering (Intel TME) organization to balance these very different requirements using a Microsoft BI solution stack based on SQL Server*, SharePoint*, and Excel*. By integrating self-service BI with a centralized BI development model, the Intel TME BI team is creating a more flexible and efficient environment for supporting end-to-end information needs.

The Microsoft solution stack simplifies this integration by enabling consistent tabular data models to be used across the entire BI environment. Development teams can deliver plan of record (POR) reports and dashboards that users can rely on for accuracy and reliability. Individual users and small teams can use those data models and reports or create their own. They can also adapt and extend them as needed within their personal sandbox environments, including adding data from other sources and altering existing data models.

The Intel TME BI team is evolving its environment to integrate these new capabilities. The result is an increasingly agile approach to information delivery that is helping employees get the information they need to manage one of the worlds most complex capital supply chains more effectively. This white paper describes the solutions and processes the Intel TME BI team is using to implement self-service BI to the hundreds of users within the Intel TME organization. The paper also discusses how Intel IT is using a similar approach to support thousands of additional users in its broader business environment.

Authors Kalpesh Shah, Software Engineer, Technology Manufacturing and Engineering

Eduardo Gamez, Software Engineer, Technology Manufacturing and Engineering

David Yantis, PMP, SPBI Product Manager, Information Technology (IT)

Rob Shiveley, Software Alliance Marketing Manager, Software and Solutions Group

WHITE PAPERIntel Xeon processor E5 familyBusiness Intelligence

Table of Contents

Executive Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1

Coordinating a Global Technology Ecosystem . . . . . . . . . . . . . .1

The Information Challenge: Scattered Data and Static Reports . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2

Implementing Next-Generation BI . . . . . . . . . . . . . . . . . . . . . . . .3

New Technologies Create New Opportunities . . . . . . . . . . . . . . . .3

Implementing the Microsoft BI Solution Stack . . . . . . . . . . . . .4

Ensuring Data Quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .5

Unifying BI across All User Groups . . . . . . . . . . . . . . . . . . . . . . . . . . .6

Optimizing BI for Agility and Effectiveness . . . . . . . . . . . . . . . .6

Targeting Big Needs with a Centralized Team . . . . . . . . . . . . . . . .6

Extending Value with BI Soft-Serve . . . . . . . . . . . . . . . . . . . . . . . .8

The Need for Speed Improving Velocity through Self-Service BI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .9

A Decentralized Approach to Training and Support . . . . . . . 10

Moving Forward . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .11

Success to Date . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

Future Plans . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

Additional Resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

Coordinating a Global Technology EcosystemIn 1965, Intel founder Gordon Moore published a paper predicting that the number of transistors that could be manufactured on a chip would continue to double every two years. That pace of innovation now provides the foundation for Intels Tick-Tock model of development, in which Intel alternates new silicon manufacturing technologies with new microarchitecture designs to deliver new products on an annual timetable.

This fast, predictable cadence is key to Intels success and to the success of many Intel customers. Yet every new product generation introduces greater design complexity and a slew of new technology demands. Lithography must be more precise and new materials and manufacturing processes are often needed, all of which require new fabrication equipment and processes. Multiply these demands across Intels global manufacturing footprint, which currently includes 11 major manufacturing sites, and the task of continually upgrading and managing Intels capital assets becomes a very complex undertaking.

The Intel Technical Manufacturing Engineering (TME) organization is responsible for keeping this process on track, and for doing it affordably. This group of approximately 600 employees manages Intels capital supply chain across five technology generations (Figure 1). Intel TMEs responsibility for each generation begins with research and development and continues on through design, manufacture, installation, use, maintenance, and end-of-life management.

Intel TME works with hundreds of internal and external groups, including commercial and academic research teams, tool design and manufacturing vendors, and many others. The decision matrix for keeping core processes on track is complex. Issues such as technology, velocity, sustainability, and affordability must be balanced in every decision.

COLLABORATIVERESEARCH

INTERNALRESEARCH

DEVELOPMENT MANUFACTURING END OF LIFE

LeveragingInvestments

Securing the RightTechnologies

Choosing the RightPartners

Delivering to the Core

Extending the Value

Spending MoneyWisely

Extracting FullValue

Figure 1. From research and development to end-of-life, the Intel Technology Manufacturing and Engineering group manages the lifecycle of Intels capital manufacturing equipment to deliver affordable innovation at the speed of Moores Law.

2

Implementing Self-Service BI to Improve Business Decision Making

The Information Challenge: Scattered Data and Static Reports Intel TME generates large amounts of data in managing Intels capital supply chain. Much of this data is scattered throughout the organization. It resides within production applications, databases, and data warehouses at the departmental and enterprise levels, and also within Excel spreadsheets and Microsoft Access* databases owned and managed by individual employees. In most cases, employees use Excel and manual methods to process, update, and maintain the data, and they create presentations on an ad hoc basis by copying and pasting Excel tables and graphs into Microsoft PowerPoint* presentations (Figure 2).

Until recently, there has been no unified focus on standardizing supply chain data and validating its quality across the Intel TME organization. However, the pace of business continues to accelerate at Intel, as it does throughout the business world. Faster access to data and better, faster decision making is increasingly necessary to keep pace with demands, especially as complexity continues to climb. It is no longer tenable to take months to deliver data and information. Better tools and methods are needed.

Implementing Next-Generation BIIn most cases, the first step in improving decision making is to speed time-to-data. This enables individuals to devote more of their time and effort to exploring and analyzing the available data before their decision window closes (Figure 3). Ideally, this results in both faster and better decisions that deliver higher value to the business.

Other DataSource(s) Microsoft

SQL Server*

Individual Access

Business User, Data Analyst,Commodity Manager, etc.

MicrosoftExcel*

MicrosoftPowerPoint*

Figure 3. The first step in improving decision making is speeding time-to-data, so employees can focus more of their time and effort on analyzing the available information to make higher quality decisions in less total time.

Figure 2. In most cases, Intel Technology Manufacturing and Engineering employees currently use Microsoft Excel* and manual methods to process, update, and maintain data, and they create presentations by copying and pasting Excel tables and graphs into Microsoft PowerPoint* presentations.

TIME-TO-DATA

TIME-TO-DATA

TIME-TO-DECISION

TIME-TO-DECISION

TIME-TO- INFORMATION

TIME-TO- INFORMATION

DECISION

DECISION

New Technologies Create New OpportunitiesA number of technologies and solutions have emerged recently that can help organizations speed time-to-data for individual decision makers. Two new capabilities stand out as particularly relevant.

Real-time analytics acting on large data sets. This capability is typically delivered by a combination of several database technologies, such as in-memory analytics, columnar data