Implementing Self-Service BI to Improve Business Decision Making

Transcription

1 WHITE PAPER Intel Xeon processor E5 family Business Intelligence Implementing Self-Service BI to Improve Business Decision Making Learn how the Intel Technology Manufacturing Engineering organization is using Microsoft BI tools to help drive innovation at the speed of Moore s 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 world s 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

2 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 Moving Forward...11 Success to Date Future Plans Conclusion Additional Resources Coordinating a Global Technology Ecosystem In 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 Intel s 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 Intel s 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 Intel s global manufacturing footprint, which currently includes 11 major manufacturing sites, and the task of continually upgrading and managing Intel s 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 Intel s capital supply chain across five technology generations (Figure 1). Intel TME s 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. COLLABORATIVE RESEARCH Leveraging Investments INTERNAL RESEARCH Securing the Right Technologies DEVELOPMENT MANUFACTURING END OF LIFE Choosing the Right Partners Spending Money Wisely Extracting Full Value Delivering to the Core Extending the Value Figure 1. From research and development to end-of-life, the Intel Technology Manufacturing and Engineering group manages the lifecycle of Intel s capital manufacturing equipment to deliver affordable innovation at the speed of Moore s Law. 2

3 The Information Challenge: Scattered Data and Static Reports Intel TME generates large amounts of data in managing Intel s 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). Individual Access Microsoft Excel* Microsoft PowerPoint* Other Data Source(s) Business User, Data Analyst, Commodity Manager, etc. Microsoft SQL Server* 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. 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 BI In 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. TIME-TO-DATA TIME-TO-DATA TIME-TO-DECISION TIME-TO- INFORMATION TIME-TO-DECISION TIME-TO- INFORMATION DECISION DECISION 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. New Technologies Create New Opportunities A 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 structures, and data compression. These technologies take advantage of the parallel execution capabilities and large memory capacities delivered in recent server generations. For example, a four-socket server based on the Intel Xeon processor E7 family 1 now provides up to 80 execution threads and supports up to 2 terabytes of memory. With these resources, even very large data sets can be held entirely in memory and large numbers of concurrent queries can be executed in parallel. Self-service BI. Historically, an end user interested in accessing business data and creating visualizations would require end-toend assistance from IT staff. A new class of easy-to-use BI tools is now available that allows typical business decision makers to quickly access, combine, and analyze data, create presentations, and then share the results with others. In combination, these innovations allow IT organizations to shift their focus. Instead of delivering reports, they have the option of delivering data models and visualization tools to the business and allowing users to create their own reports. Although there are many sophisticated analytic techniques that still require expert data analysts and developers, these self-service tools fill a critical gap to enable more efficient and flexible delivery of enterprise information. 3

4 Implementing the Microsoft BI Solution Stack Intel TME s initial drive to improve BI came from two directions. The lengthy timelines associated with traditional BI projects were delaying business access to information and also placing a heavy burden on BI development teams. A business analyst in the Intel TME capital planning organization was engaging with key staff to address this issue. At the same time, a software developer in the Intel TME Systems Engineering group was exploring technical solutions using the Microsoft BI stack and Kimball data warehousing methodologies. The employees driving these independent efforts connected, providing a fortuitous combination of need and solution. Initially the two employees focused on a single business need: measuring supplier delivery performance. This first project delivered sufficient business value to justify the creation of a formal Intel TME BI team to develop and execute a roadmap. The Microsoft BI solution stack aligns well with Intel needs and requirements. Most Intel TME data resides in SQL Server databases and multi-dimensional cubes, personal Microsoft Access databases, and Excel spreadsheets. Microsoft BI tools make it easier to take advantage of these data sources and to leverage existing knowledge and skillsets. The Intel TME implementation of the Microsoft BI solution stack is shown in Figure 4. The back end of the BI environment consists of an organizational data mart built on SQL Server. The team uses a number of built-in services to manage the data mart, including the following: SQL Server Integration Services (SSIS) for deploying extract, transform, and load (ETL) packages to configure data feeds from external sources SQL Server Analysis Services (SSAS) for deploying and managing cubes and tabular models within the data mart SQL Server Reporting Services (SSRS) for creating reports Microsoft Visual Studio* with BI Development Studio (BIDS) and SQL Server Data Tools (SSDT) for development teams to write BI applications, including ETL packages, data models, reports, and dashboards INTEL TME BI ARCHITECTURE Personal BI Team BI Organizational BI Microsoft Internet Explorer PowerPivot for Excel Microsoft Excel Third Party Apps Microsoft SharePoint Excel Services Power View for SharePoint (Reporting Services) PowerPivot for SharePoint (Analysis Services) Microsoft SQL Server Analysis Services (SSAS) Multidimensional Mode Tabular Mode Hardware Infrastructure Virtual Machines 4 vcpus, 12GB memory (production, test, development) 4vCPUs, 6GB memory (production, test, development) Clustered Virtual Hosts Storage 5 ProLiant BL490c G7 Blades (2 x Intel Xeon processor 5600 series and 400GB memory per blade) 16TB shared SAN Figure 4. The Intel Technology Manufacturing and Engineering BI implementation provides users with flexible access to data, reports, and BI tools using a Microsoft BI solution stack that includes Excel*, Internet Explorer*, SharePoint*, and an organizational data mart built on Microsoft SQL Server*. 4

5 SharePoint provides the foundation for managing end-user access to data and libraries of shared reports. End users have the option of logging onto SharePoint with their browsers and using server-side instances of Excel to view and interact with data and reports. Alternatively, they can download data and reports for local execution on their personal instances of Excel. (Note: The Intel TME BI team currently provides access to shared reports. Providing users with direct access to data models is a work in progress. See the sidebar, Upgrading the Software Stack to Deliver Higher Value.) The Intel TME BI team manages access rights using Microsoft Active Directory*. The security model extends into SQL Server, which enables granular control of data access. This is important, since the Intel TME data mart contains some of Intel s most sensitive intellectual property (IP). The hardware infrastructure for the Intel TME BI implementation consists of five clustered, two-socket blade servers, each configured with two six-core Intel Xeon processors and 400 GB of memory. These servers currently host nine virtual machines: two for the production environment, two for staging, and five for development. All instances of SQL Server run in a single virtual machine configured with 4 vcpu and 6 gigabytes (GB) of memory. All instances of SharePoint Server run in a single virtual machine configured with 4 vcpu and 12 GB of memory. Infrastructure teams are currently exploring the advantages of increasing memory to 16 GB for the SharePoint virtual machines. The large amount of system memory is provided to support Microsoft xvelocity In-Memory Technology (discussed below), which provides fast data manipulation and queries by holding all data in memory, rather than shuttling data back and forth between memory and disk. Ensuring Data Quality Data quality and completeness are critical success factors for all BI efforts. Most data in the Intel TME data mart comes from Intel TME production applications and databases. As the Intel TME BI team starts processing data for BI consumption, they also perform basic auditing to ensure validity. This is especially critical for data that will be used for measures and indicators. Since data is consumed differently for BI than it is in other use cases, auditing often uncovers data quality issues that would most likely go unnoticed without these efforts. Once an issue is identified and a root cause is determined, a project is launched to close the data quality gap. Upgrading the Software Stack to Deliver Higher Value The Intel Technology Manufacturing and Engineering BI solution stack currently includes Microsoft SQL Server* 2012, SharePoint* 2010, Windows Server* 2008 R2, and Excel* 2010, as well as System Center 2007 for assisting infrastructure management teams. Intel is currently in the testing and planning stages of an upgrade that will include moving to SharePoint 2013, Windows Server 2012, Excel 2013, and System Center The upgrade will most likely include a move to new blade servers based on the latest Intel Xeon processor E5 family to reduce the data center space and power footprint. There are many advantages to this updated solution stack. One of the most valuable for Intel TME is that PowerPivot and Power View will be fully integrated across all software components, so tabular data models will be supported throughout the BI environment, with no need for plug-ins or workarounds. This will allow the team to provide users with direct access to data models within the Intel TME data mart to support full self-service BI functionality. As part of the move to Windows Server 2012, the team is currently testing the latest version of Hyper-V*, and anticipates being able to reduce software licensing costs for supporting the virtualized server environment. For more information about Microsoft BI solutions and the Intel Xeon processor E5 family, see the resource links at the end of this paper. 5

6 The Intel TME BI team uses several tools to audit data, including those provided in SQL Server The team recently began providing select business users with direct access to the data mart s staging environment, facts, and dimension tables using Excel. They have found that business users provide valuable insights into data quality and usability. Unifying BI across All User Groups The Intel TME data mart was initially deployed on SQL Server 2008 R2. However, a recent upgrade to SQL Server 2012 has delivered important new features. Combined with capabilities available in Excel and SharePoint, these enhancements are key to delivering effective self-service BI and integrating it efficiently with centralized BI development efforts. The Microsoft BI Semantic Model (BISM) in SQL Server 2012 includes new tabular data models in SSAS, as well as more traditional multidimensional models. These tabular models can be accessed and consumed directly by business decision makers using PowerPivot and Power View. PowerPivot allows end users to manipulate large pivot tables and tabular data models at high speed within an Excel workbook. High performance and scalability are enabled by Microsoft xvelocity In-Memory Technology, which combines in-memory analytics processing with columnar data models and advanced data compression. PowerPivot is available as a plug-in for Excel 2010, and is supported in SharePoint Microsoft has also integrated xvelocity In-Memory Technology into SQL Server 2012 to accelerate performance for server-side data analytics. Power View is a self-service reporting tool for business users that is integrated into SharePoint 2010 and into SQL Server 2012 (as part of SSRS). Power View provides an interactive interface for users to explore, manipulate, and present the data located in tabular data models and pivot tables. Both PowerPivot and Power View will be included in Excel 2013, which the Intel TME BI team is currently testing and plans to deploy in conjunction with SharePoint With BISM, PowerPivot, and Power View, tabular data models are now supported across the entire Microsoft BI solution stack, including SQL Server, SharePoint, and Excel. This consistency enables a unified BI environment across all usage models. For Intel TME, this is one of the primary advantages of the Microsoft BI solution. It is now relatively simple and seamless for development teams to: Create BISM tabular models using Visual Studio SQL Server Data Tools (SSDT). These models are then deployed to SSAS tabular instances to be consumed by Power View reports. Use the Data Analysis Expressions (DAX) language within tabular models to quickly create and deploy both simple and extremely complex data aggregations. Unlike SSIS, DAX provides a very efficient way to create new measures and indicators and quickly deploy them from development, to testing, to production environments. With this foundation, centralized teams have an efficient BI development framework for developing tabular data models. End users can potentially access, manipulate, and consume those same data models using Excel with PowerPivot and Power View. The result is a flexible and unified BI environment capable of supporting the full range of Intel TME BI requirements. Optimizing BI for Agility and Effectiveness Like most organizations, Intel TME has a continuum of data needs. At one end are the big deals that are directly tied to core business processes and objectives, such as vendor assessment and procurement tracking. These processes depend on large amounts of scattered data and have a direct and significant impact on Intel s overall success. At the other end of the continuum are the data needs of individuals and small groups. Improving data access for these users would not have a major impact on core business functions but might, collectively, have a substantial impact on overall business success. Targeting Big Needs with a Centralized Team The Intel TME BI Working Group was formed to drive organizational alignment on the big deals by initiating and managing BI deliverables and working to enable successful integration into Intel TME operations. The team gathers requirements from each participating department and develops a prioritized roadmap for implementation by the Intel TME BI team. Seven major user groups within Intel TME are represented within the Intel TME BI Working Group, with responsibilities ranging from equipment development and capital planning, to training and factory ramping, to business operations and capital equipment resale. Most of the representatives are data stewards for their organizations. These data stewards are typically Excel power users and have a good, practical understanding of business processes, data sources, and information needs. A few are experts in data analytics, but most are not. A few organizations lack anyone with the required skillsets, in which case advocates are enlisted from other groups. 6

7 Once high-level requirements have been gathered, projects are evaluated and prioritized by the Intel TME BI Working Group. In an attempt to avoid the kinds of political issues that can arise in cross-organizational decision making, the group developed a standardized process for evaluating projects based on estimated risk and reward (Figure 5). Projects with low risks and high rewards get top priority (see the sidebar, Characteristics of a Successful BI Project). Business Value Project G Project C Project I Project A Project B Project F Project D Depending on the requirements, some combination of database administrators (DBAs), data analysts, business analysts, and BI software developers work together on each project. These teams have found that BI development is very different from traditional application development. Instead of building a functional map based on business process needs, developers must begin with a clear understanding of data sources and then map business needs to create measures and indicators of the available data. The process for a typical BI project includes four key steps. 1. Engage with business teams to develop user stories that define requirements, including data, measures, indicators, and reports. This step typically consumes approximately three-fourths of the total time and effort for each project, and the refinement of these requirements typically extends throughout the development process. Project E Project H 2. Develop ETL packages, tabular data models, and data mart changes using Microsoft Visual Studio, SSIS, and SSAS. At this stage of Intel TME s BI evolution, this step often involves accessing, auditing, and integrating new data sources. Risk Figure 5. To allocate resources in the most effective manner, the Intel Technology Manufacturing and Engineering BI Working Group developed a standardized process for evaluating projects based on estimated risk and reward. 3. Create the associated reports and dashboards using Power View. Work with data stewards and their business teams to test and refine the solution. 4. Release the finalized reports to production and publish them on SharePoint as part of the Intel POR. Characteristics of a Successful BI Project The Intel Technology Manufacturing and Engineering BI development team has found that active support from targeted business groups is crucial to the success of BI development projects. When assessing the viability of BI requests from business units, proposed projects should be: Tied to a documented business process with a clearly envisioned end-state. Supported actively by business representatives during requirements definition, data validation and business process alignment. These phases typically account for about three fourths of the work in BI development, and it is important the business representatives are available and responsive. Championed by one or more key business users to fuel post-rollout adoption and to provide some level of training and support for novice business users. 7

8 Extending Value with BI Soft-Serve Intel TME POR reports can be published only by the Intel TME BI team, which follows standardized procedures to maintain quality and reliability. Decision makers can use Power View to access these POR reports (Figure 6). They can also copy the reports into their personal sandbox areas and adapt them in any way they choose. These altered reports are no longer POR, but they can be widely shared. Access is limited only by the Active Directory groups the Intel TME BI team maintains to control access to sites, sub-sites, and libraries. Since these sandbox reports point to the same tabular database, the data is secured no matter who views a specific sandbox report. SOFT-SERVE BI Intel TME calls this BI model soft-serve. Unlike a full self-service BI model, the soft-serve model does not allow end users to access and manipulate data from the data mart, only reports. However, even this interim soft-serve model has substantial value, since it enables the Intel TME BI team to standardize data, measures, indicators, reports, and visualizations, while empowering end users to modify reports as needed to address their unique requirements. Microsoft SharePoint TME Depts Business User Reports Business User Analyst BI Working Group Prioritized Roadmap Additional BI Requests Analyst User Stories Microsoft SQL Server Developer TME Data Mart Self-Service BI Opportunity Other Data Sources Figure 6. As an interim step before implementing full self-service business intelligence (BI), the Intel Technology Manufacturing and Engineering soft-serve BI approach allows users to access reports and adapt them to meet their specific requirements. 8

9 The Need for Speed Improving Velocity through Self-Service BI The soft-serve approach to BI helps to improve flexibility for end users, but not enough to meet the rapidly growing business demand within the Intel TME organization. Business decision makers want even greater flexibility, and they don t want to wait on lengthy centralized projects to get the information they want in the way they want it. At the same time, the TME BI team needs to be able to standardize and centralize TME data and information to ensure data quality. These competing needs place unsustainable demands on centralized IT resources. Like IT shops everywhere, the Intel TME BI team needs a way to standardize and validate organizational data, while simultaneously delivering more agile and differentiated support to end users. To address these needs, Intel TME is working to deliver full selfservice BI to data stewards and other end users. This approach allows users to access data models within the TME data mart and create their own reports using Power View. They can also download the data models into their personal sandbox areas, after which they have complete flexibility to add or remove data, restructure models, and create their own relationships, calculated columns, measures, and key performance indicators (KPIs). 2 Users can then review and refine their data models and reports in collaboration with their own business units and make the reports available to authorized users through SharePoint. When a user-generated report is mature, shown to deliver high value, and approved by the appropriate business unit, the Intel TME BI Working Group can coordinate a Technical Review Group (TRG) to create a more complete user story, perform data audits, determine data gaps, and enhance the report to ensure standardized measures, metrics, and KPIs. The new data model and report can then be deployed within the Intel TME data mart and become part of the POR. The cycle can then repeat, with users continuing to extend and adapt POR reports within their private sandboxes to address their unique needs and then sharing the results with others. This self-service approach to BI represents a paradigm shift in data and information delivery. It is already impacting the way Intel TME develops and delivers data and reports. Traditional agile processes for software development are still valuable for centralized solutions, but they are being adapted to incorporate elements of this more decentralized approach. Business unit data stewards are being integrated into the development process, and soft-serve and self-service BI is becoming an essential and integrated part of the overall offering. Soft-serve and self-service BI introduce risks as well as rewards. Without centralized control, not all data models and reports will be high quality. Some may even provide wrong or misleading information. However, it is Intel s belief that the potential value far exceeds the risk by providing an exceptionally broad base for innovation. Hundreds of users, all with different needs, experience, and insight into business processes, will be able to access and analyze data faster and more effectively. Intel TME is not the only organization within Intel that can benefit from faster access to data and information, so Intel is extending access to self-service BI tools throughout the enterprise. This broader self-service BI implementation uses the same software stack, but a different physical implementation. 3 It went live in 2011 and had over 5,000 users within one year. By mid-march 2013, there were 13,800 active users and the user base continues to grow. 9

10 SELF-SERVICE AND CENTRALIZED BI INTEGRATION Self-Service BI Create/Update Data Steward Project Status Data Steward Review PowerPoint Microsoft SharePoint Deploy Ready for TME BI? No Update Data Steward Yes TME Dept Data Steward TRG Other Data Sources Microsoft SQL Server TME Data Mart Analyst Data Steward Business User TME BI Roadmap User Stories KANBAN TME BI Application LIfecycle Management Developer Figure 7. Intel Technology Manufacturing and Engineering is moving toward full self-service business intelligence, in which data stewards and other users can access data as well as reports and adapt both in any way they choose within their personal sandbox environments. A Decentralized Approach to Training and Support Effective use of self-service BI requires that users understand the following: Relevant business processes Pertinent data sets, including how they are organized and interrelated and how to access them Tools and methods for analyzing, presenting, and sharing data It would be possible to train large user groups to use BI tools, but business processes and relevant data vary across the company. Because of this, training end users for BI will never be like training end users to use a traditional business application. A decentralized approach to BI training helps to address this issue. 10 The Intel TME BI team is educating data stewards to use the BI tools. Intel corporate IT takes a similar approach, training site owners and select users throughout the business. In both cases, those individuals then train and support people within their own organizations. This process helps to get the right information and training to the right people, by creating expanding communities of excellence tailored to the needs of each organization. Intel IT offers some additional training sessions on an ad hoc basis to help users address common challenges. Users can also attend online office hours to ask specific questions that may be beyond the expertise of their data stewards. For now, this strategy is working well, enabling a small team to train and support a very large user group. As self-serve BI continues to increase in popularity and importance at Intel, it may become necessary to deliver more formal training to supplement the current programs.

11 Moving Forward Success to Date The Intel TME soft-serve and self-service BI programs are still in a relatively early stage. The Intel TME BI team released one centralized report to production in 2011 and five more in Many more are in the development queue for One example of a successful BI deliverable is the Intel TME Forecast Progress Indicators report, which is used to help Intel TME stakeholders understand the current status of the capital supply chain. Intel TME has never before had a single view showing the status of all the tools at each supply chain stage, much less with this level of detail. The report provides a summary page showing the key steps Forecast, Order, Delivery, Impact, Transit, and Install and provides drill down alternatives to view graphs and explore details. Gaps can be identified quickly and explored to help mitigate risks and keep factory ramping schedules on track. This information is now delivered automatically to all stakeholders, so it is no longer necessary to create and run manual reports. The Intel TME Forecast Progress Indicators report and several others have reduced time-to-data to help business decision makers monitor, evaluate, and manage key processes, including the following: Supplier delivery performance Procurement status across the capital supply chain Risk factors for equipment implementation and quality Document readiness In one case, the delivered report provided approximately 400 hours per quarter in productivity savings. In general, however, quantifying value in the BI arena is challenging. Individual decisions must be tracked to determine if they were, in fact, the best decisions. The speed and quality of the decision must also be tied back to the BI environment. Because of these challenges, Intel TME is currently relying on user perception and feedback to evaluate success. Feedback has been positive across the majority of projects: In the past, we had to pull and link all this data together manually from the different systems. The process was so timeintensive, we only did it once per quarter at most. Now it takes just an hour or two to pull and manipulate the data. This tool has facilitated an in-depth analysis at the SRC line item level, allowing us to analyze point allocation and actual scores on the spot. We couldn t do this before. For years, I ve been asking how we could measure work proficiency. Now I have an answer. Great job! Thank you for your support in generating tailored data acquisition pulls and metrics for measuring continuous improvement. We ll be happy to use these indicators!! And more!!! The majority of Intel business users also report an excellent experience using Excel, PowerPivot, and Power View for accessing and creating reports and dashboards. Even very large data sets can be combined, filtered, and processed with fast application response times and building reports is relatively simple and intuitive. The ability to continue manipulating data and visualizations within existing presentations has proved valuable in creating impactful and easily customizable reports. This feedback is valuable, but more quantitative data is needed for effective planning. Efforts are underway to introduce these and other success metrics in The primary focus will be on quantifying the impact reports have on time-to-data. Once the team has a handle on these metrics, they will begin focusing on more complex issues, such as decision quality and the ability to make more decisions in less time. Future Plans Although the BI program has delivered clear benefits to date, the Intel TME BI team believes the biggest benefit is the groundwork that has been laid for future BI innovation by standardizing tools and processes for data access, analysis, and visualization. Processes are becoming more repeatable and success more predictable. The amount of high-quality data in the Intel TME data mart is also growing, which will create new opportunities and faster paths to success going forward. BI and analytics are a work in progress at Intel, as they are for every company. The Intel TME vision for BI is a world in which the following criteria are satisfied: Every employee has 24x7x365 access to the data and information they need to do their job, through a single portal that is available worldwide and configured to match their unique role in the business. Portal usage is intuitive, with self-serve data and no need for training. Barriers to data access are minimized within the constraints dictated by the need to protect Intel IP. All data accessed by decision makers comes from a single system of record to ensure data quality and a single version of the truth. To meet this need, Intel TME must be able to access all required data across the Intel Technology Manufacturing Group 4 (TMG) and the Intel TMG supplier ecosystem. This, in turn, requires that Intel TME data should be fully aligned with supplier data obtained through the next-generation Intel TMG Supplier Presence Site. BI tools are embraced by all levels of the organization, to the extent that individuals and teams update their business processes to make better use of this new information source. In time, manual sources of information should disappear completely, because they are no longer needed. 11

12 It should be emphasized that these are goals, not expectations. Existing data sets are growing and data sources are proliferating throughout the business. Fully controlling data and information will most likely never be a practical possibility. Nevertheless, a vision of an ideal BI environment helps to guide long-term plans and has helped the Intel TME BI team establish the following goals for Manage centralized BI projects as a portfolio. Advances in quantifying BI project success will help in this endeavor, providing a better foundation for prioritizing projects and allocating resources based on expected returns. Move toward trending and predictive analytics. Efforts to date have focused primarily on tracking current activities with reference to goals and expectations. The team has performed a few what if analyses to try to predict outcomes for better decision making and sees substantial value in moving toward this more advanced analytics model. Efforts will continue to evolve as the TME BI team builds a better understanding of both technical and business opportunities and hurdles. Strengthen BI alignment across Intel. Collaborative efforts are underway with other groups to define self-service BI at Intel. As one example, the TME BI team is partnering with the SharePoint Business Intelligence enterprise team, which is building an Intel-wide Community of Excellence program around SharePoint BI. Conclusion Evolving a global supply chain at the speed of Moore s Law is a complex undertaking, requiring tight coordination among hundreds of companies and thousands of individuals. Intel TME is using an integrated combination of centralized and self-service BI development to provide decision makers with simpler and faster access to the information they need to do their jobs more effectively. Microsoft BI tools provide the software foundation for this integration, with an organizational data mart built on SQL Server, a managed BI portal built on SharePoint, and end-user tools provided by Excel (with PowerPivot and Power View) all running on Intel processor-based servers and laptops. The ability to use consistent data models for both end-users and centralized development teams has been instrumental in providing flexible and effective support for all user groups. Business users can access centrally developed and validated POR reports to improve decision making for core business functions. They also have the flexibility to adapt and extend those reports with new data and alternative analyses, or to build entirely new data models and reports. As information requirements continue to grow, the Intel TME BI team believes this strategy will enable continual improvements in data usage and decision making throughout the organization. Additional Resources For more information about: The Microsoft BI solution stack, visit: Intel Server Products, including the Intel Xeon processor E7 family, the Intel Xeon processor E5 family, and the Intel Xeon processor E3 family, visit: en/processors/xeon/xeon-processor-e7-family.html 1 For more information on the Intel Xeon processor E7 family, visit the Intel web site. 2 Power View reports created in Microsoft Excel* instances currently cannot be imported directly into Microsoft SharePoint* and consumed using reporting tools within SQL Server* Reporting Services, even though the PowerPivot and tabular data models are typically the same. Technology Manufacturing and Engineering IT is currently exploring options for eliminating this gap. 3 Both the Technology Manufacturing and Engineering implementation and the broader, self-serve implementation use the Microsoft BI solution stack. However, there may be differences in product generations and version numbers. 4 The Intel Technology Manufacturing Engineering (TME) organization exists within the larger Intel Technology Manufacturing Group (TMG), which is responsible for all aspects of Intel s global manufacturing assets. INFORMATION IN THIS DOCUMENT IS PROVIDED IN CONNECTION WITH INTEL PRODUCTS. NO LICENSE, EXPRESS OR IMPLIED, BY ESTOPPEL OR OTHERWISE, TO ANY INTELLECTUAL PROPERTY RIGHTS IS GRANTED BY THIS DOCUMENT. EXCEPT AS PROVIDED IN INTEL S TERMS AND CONDITIONS OF SALE FOR SUCH PRODUCTS, INTEL ASSUMES NO LIABILITY WHATSOEVER, AND INTEL DISCLAIMS ANY EXPRESS OR IMPLIED WARRANTY, RELATING TO SALE AND/OR USE OF INTEL PRODUCTS INCLUDING LIABILITY OR WARRANTIES RELATING TO FITNESS FOR A PARTICULAR PURPOSE, MERCHANTABILITY, OR INFRINGEMENT OF ANY PATENT, COPYRIGHT OR OTHER INTELLECTUAL PROPERTY RIGHT. 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