2006 TDWI BI BENCHMARK REPORT

Transcription

1 BI Teams and Metrics OCTOBER 2006 BY WAYNE W. ECKERSON Contents 2 PURPOSE AND METHOD 2 SUMMARY PROFILE 3 BI DIRECTORS 5 COMPANIES 7 GROUPS 9 BI DEPLOYMENTS 12 BI TEAMS 13 BI BUDGETS 14 BI SUPPORT PROCESSES 15 BI ARCHITECTURES 17 CONCLUSION

2 PURPOSE AND METHOD / SUMMARY PROFILE Purpose and Method TDWI s annual BI Benchmark Report allows business intelligence (BI) teams to compare themselves to their peers on a series of organizational and performance metrics. TDWI initiated this report in 2005 in response to TDWI Member requests and will continue to enhance it with Member input. Compare your BI team on a series of organizational and performance metrics, based on a survey of BI directors The data for this year s report is based on a survey of BI directors who were invited to attend the TDWI Executive Summit held in February The survey ran from December 2005 to January More than 130 individuals responded to the survey, 120 of whom were qualified to submit responses. The small sample size makes it risky to filter the data by variables like revenues or industry, but we did make a few cuts based on BI maturity. Future surveys will expand their sample size to allow for filtering of the data by a number of variables. Summary Profile The following profile summarizes the results of this report. The profile describes the average BI director, BI team, and BI implementation. While no organization fits this profile exactly, it provides a rough snapshot of the BI industry. The later sections of this report examine the details of this profile. Teams are led by highly educated, well-compensated directors with considerable BI/DW experience. These directors oversee a central BI/DW group that serves the entire company consisting of multiple divisions and departments, and they are currently overhauling a BI/DW program that has gone through several iterations during the past five years. BI teams add two new subject areas a year, each taking three to four months to complete. They have a staff of 20 full-time employees, 25 percent of whom are contractors and 10 percent of whom are outsourced or offshored. A budget of $2.5 million is common, which is 4.2 percent of the overall IT budget; a very small ratio of help tickets to active users is typical. Most companies use a hub-and-spoke DW architecture with centralized data marts generally nine dependent data marts running against an 875 GB data warehouse that grows by 175 GB a year. BI directors are highly educated, well compensated, and very experienced Most groups serve multiple lines of business BI teams average 20 FTE; one-fourth are contractors The average BI budget is $2.5 million Most companies use a huband-spoke DW architecture with centralized data marts Organizations commonly have lots of BI tools but a small percentage of active users It s also common to have a large number of BI tools but a small percentage of active BI users. 2

3 BI DIRECTORS BI Directors Since our survey group was BI directors, we took the opportunity to create a profile of the average BI director. Most BI directors work within their organization s IT department and oversee both business intelligence and data warehousing programs (among other things). They hold substantial responsibility for the BI program s strategy, budget, and architecture. BI directors have, on average, 8 years of BI/DW experience and oversee BI/ DW teams of varying size. A majority of BI teams (65 percent) have 10 or fewer full-time staff, but 14 percent have more than 35 staff. BI teams are generally small because many projects are still getting off the ground and organizations have trimmed IT budgets and staffing in recent years. continued next page Respondents have considerable BI/DW experience and oversee small to midsize BI/DW teams. Position Consultant 5% Business sponsor 11% Level in Organization Other 3% Manager 25% BI/DW Responsibilities IT 84% Director 57% 8% CxO or unit head 8% Vice president BI and DW 85% BI/DW strategy 97% Budget 91% Architecture 91% DW only 7% BI only 7% Location Other 7% Canada 3% Europe 5% U.S. 85% BI/DW Experience (Average: 8 years) 15+ years 14% 24% 0 4 years years 28% 34% 5 9 years Team Size 36+ staff 14% staff 31% 5% 0 2 staff 23% 3 5 staff 27% 6 10 staff 3

4 BI DIRECTORS Although BI directors are one of the highest-paid groups in the IT department, most are relatively young (43 years on average) and male (74 percent). They ve reached their current position by working their way up through the ranks at their current company (6.4 years average tenure). The people who responded to this survey are a fairly elite IT group who are also pretty content with their jobs. Profile of the average BI director Individual Age 43 Gender Male (74%) Years at company 6.4 Education 56% BA 32% MA Compensation Average salary $117,260 Average bonus $20,104 Percent with options 34% Fairly compensated? 53% yes 31% no 16% not sure Outside income? 8% Job Satisfaction Very high or high 57% Looking for new job? Yes 13% Professional BI experience 8.4 years Full time on BI/DW 53% Final purchasing 21% authority Background 27% technical 27% business Certifications 1 Selected averages from the 2006 TDWI Salary, Roles, and Responsibilities Report. 4

5 COMPANIES Companies Our survey respondents generally work in large organizations with more than $100 million in annual revenues and more than 1,000 employees. Most of these organizations centralize authority and decision making to a high degree, which makes it easier to create an enterprise data warehouse that delivers a consistent view of the business. The financial services industry had the most respondents to the survey. Interestingly, most organizations manage BI/DW processes and staff as a single group, usually within corporate IT. Most respondents told us that within these centralized BI/DW groups, there are distinct DW and BI teams that function independently of each other but report to the same BI director. For example, one typical BI director runs a BI/DW group in a financial services firm that supports finance groups in all divisions. His group consists of four teams and 35 staff, five of whom reside in India. The teams are: Data warehousing team that consists of seven people (all local) who source the data from operational systems, and model, transform, and place the data in a data warehouse that supports the data marts. Data mart services group that consists of 15 people (all locally based) who are former finance people serving as business analysts (i.e., subject matter experts) who have been given some training on multidimensional modeling. They interview business people, The average BI company has thousands of employees and a centralized organizational model. Revenues Don t know 4% > $50 billion 8% $5 50 billion 19% $1 5 billion 28% Centralized Authority and Decisions Employees Top Industries Fair to low 7% Moderate 35% > 50,000 11% 5,000 50,000 29% Other 23% Higher education 5% Pharmaceutical 5% Software 6% Retail 6% Media 6% 7% < $100 million 33% $100 million 1 billion 20% Very high 37% High 21% < 1,000 39% 1,000 5,000 20% Financial services 12% Manufacturing 9% Insurance 8% Healthcare (The other category includes industries with less than 3% of respondents.) continued next page 5

6 COMPANIES synthesize requirements, identify data marts that could meet the users needs, or create dimensional models for new data marts (when required). BI tools consulting group that consists of seven people (two in India) who are tools developers. They work with internal clients to create reports using one or more BI tools. E-reporting team that consists of six people (three in India) who are all Java reporters with minimal BI experience. They create the portal through which the BI reports and dashboards are viewed. Most companies manage DW and BI functions as a single unit within corporate IT. DW and BI Organization Same group 24% BI/DW Structure Other 10% Decentralized DW 9% and BI groups Central DW, 11% decentralized BI Central BI, 11% decentralized DW Different groups 76% 59% One central BI/DW group Group Other 10% Information 8% management group Business unit IT 10% 45% Corporate IT BI/DW group 27% ONE REAL-LIFE (BUT TYPICAL) EXAMPLE OF BI/DW TEAM STRUCTURE AND ROLES WITHIN A COMPANY Within the corporate IT department, distinct BI/DW teams function independently but report to the same BI director. The group as a whole serves all divisions within the company. BI director Data warehousing team 7 local team members Data mart services group 15 local team members BI tools consulting group 7 team members (2 international) E-reporting team 6 team members (3 international) Background: technical/dw Responsibilities: source, model, transform, and load Background: business/subject matter experts; some MDM training Responsibilities: business analysis, multidimensional modeling Background: technical/bi tool developers Responsibilities: develop tools, create reports Background: technical/java, little BI experience Responsibilities: create portals to view BI reports and dashboards 6

7 GROUPS Groups Most BI/DW groups provide services to the entire company, not just a division or department, and they support a lot of users. The difference between the average (mean) and median shows that a few companies in our sample support enormous numbers of users. In fact, some leading-edge companies are using their data warehouses to deliver reports to tens of thousands of customers. BI directors draw high salaries (see page 4) partially because they oversee more than just BI/DW. Data integration, predictive analytics, financial reporting, and application development lead the pack of common non-bi/dw technologies (although you could make a case that some of these fall within the logical bounds of a BI/ DW environment). Interestingly, about a quarter of the groups handle very distinct areas like CRM, knowledge management, and ERP systems. Sometimes, a BI director who delivers substantial value is given additional responsibilities. This is known as the curse of success, or advancing one s career! Most BI groups provide a variety of services on an enterprise scale Average Users Supported: 5,186 Median Users Supported: 1,000 Scope of Support Single dept, 5% enterprisewide LOB or region 22% BI/DW Responsibilities Entire company 72% 1% Single dept within one LOB BI 99% DW 95% Data integration 75% Predictive analytics 56% Financial reporting 53% Application development 46% Compliance and audit 28% CRM 26% Content/knowledge mgmt 24% ERP or OLTP systems 17% Servers and storage 16% Supply chain mgmt 10% GIS systems 8% continued next page 7

8 GROUPS Most BI/DW groups support multiple lines of business and departments, with particular focus on serving the needs of executives, front-office functions (sales, service, marketing), and operations. This indicates that most BI/DW groups are on their way to delivering true enterprise data warehouses rather than subjectspecific data marts. Most groups support multiple lines of business (LOB) and departments. Number of LOBs Supported Not sure 8% > 21 12% % % 11% < 2 25% 3 4 Number of Departments > 21 25% 28% < % 26% 7 10 Departments Executive team 93% Finance 85% Marketing 81% Sales 72% Operations 72% Service 53% HR 39% Procurement 33% Logistics 28% Manufacturing 24% R&D 22% Design/engineering 10% Other 12% 8

9 BI DEPLOYMENTS BI Deployments Our survey respondents map nicely into TDWI s BI Maturity Model. While the majority of organizations are in BI adolescence stuck between the Gulf and the Chasm in the Child or Teenager phase of development almost one-third have fallen into the Chasm, which represents a series of obstacles to BI expansion. These include executive perceptions, user perceptions, proliferation of nonconforming data warehouses and marts, BI tools that are difficult to use, poor performance and scalability, and political and cultural problems. Most BI/DW solutions are midway through BI adolescence. Stage of BI/DW Deployment We have a mature 15% solution that delivers high business value We re doing 31% a major overhaul of the program 8% We re getting serious about it for the first time 23% We have completed our first iteration and are looking to expand 23% We ve successfully completed two or more iterations continued next page TDWI S BI MATURITY MODEL Data Marts Data Warehouses Gulf Chasm Production Reporting Spreadmarts Enterprise DW Analytic Services 1. Prenatal 2. Infant 3. Child 4. Teenager 5. Adult 6. Sage Business Value See for a Webinar on TDWI s BI Maturity Model. 9

10 BI DEPLOYMENTS An iteration is a major architectural expansion of the data warehouse, usually involving some major change to the data model, infrastructure, or delivery (e.g., reports and applications). Projects, on the other hand, usually correlate to a three- to four-month set of deliverables, often focused on sourcing new or more granular data, and developed by a team of four to six people. A surprising number of companies (46 percent) support four or more concurrent projects, which implies that these teams have at least 24 people a much higher number than our average. This may be explained by the fact that some tasks (report development, requirements gathering, and analysis) don t require full-time equivalent staff; individuals can therefore work on multiple projects simultaneously. continued next page Respondents have typically completed 2.6 major BI/DW iterations in the past 4.5 years and manage 4.1 concurrent BI/DW projects. Number of Years Deployed Number of Major Iterations 6+ 25% 29% % % 3 21% Number of Concurrent Projects Lasting 3+ Months 6+ 21% 46% 3 5 9% 0 20% 1 30% 2 9% 1 22% % 24% 3 10

11 BI DEPLOYMENTS To Deliver a Subject Area, You Must: 1. Define user requirements 2. Analyze source systems 3. Model target database 4. Develop ETL/validation code 5. Create/revise reports 6. Test, deploy, and train users The average data warehouse supports almost 10 subject areas, which means it covers a broad cross section of departments and processes. Anecdotal evidence suggests that large organizations generally have teams of five or six individuals who work for three to four months to add a new subject area to the data warehouse. These figures jibe with the data in these charts. Adding a new subject area which includes everything from defining user requirements, analyzing source systems, and modeling data, to developing ETL rules, creating, revising, and testing reports, and training users is fairly time-consuming and expensive. To accelerate this process, larger teams tend to manage multiple projects in parallel, either centrally or in distributed fashion with teams from different divisions building local applications against an enterprise architecture. Most BI/DW solutions have 9.5 subject areas, and add 2.2 subject areas a year at 2,941 man-hours each. Number of Subject Areas Average: 9.5 Don t know or N/A 9% % % % New Subject Areas Each Year 10+ 6% 10+ 6% % 3 21% Number of Man-Hours Average (mean): 2,941 Median: 2,400 21% % 5 6 Average: 2.2 a year 9% 0 20% 1 30% 2 Example: 3,000 Man-Hours Equals: 3 staff working 4 months 6 staff working 3 months 11

12 BI TEAMS BI Teams It should be no surprise that the size of a BI team is proportional to the size of the BI budget. But what may be surprising is that much of this growth in team size comes from adding third party experts (contractors, outsourced personnel, and offshore staff) to the team. Contractors comprise almost one-third of BI teams in large companies, whereas they comprise only 9 percent of BI teams in small companies. By far, the roles with the most full-time staff are ETL managers and developers, followed by BI tools development and then business analysts, support staff, and database administrators. The total staff sizes on this chart are larger than the average team sizes listed on the previous page because some roles in the chart don t necessarily report to the BI director. Why is there no correlation between staff size and BI/DW maturity? There are several potential reasons: (1) Bigger staffs get in the way of each other, so more mature teams probably figure out how to do more with less, while newbie teams may be so eager to catch up that they over-hire. (2) Mature implementations may have offloaded reporting to users and administrative tasks to another group in IT. (3) The accuracy of this data may be affected by our small survey sample. Staff size, hiring rate, and percentage of contractors grow with the size of a company. Figures based on averages. Small (<$500 million) Medium ($500 million 5 billion) Large (>$5 billion) Total FTE FTE added in Contractors 9% 23% 30% Outsourced 4% 4% 14% Offshored 3% 5% 12% Large companies have twice the staff of small and midsize companies. Figures based on averages. Small (<$500 million) Medium ($500 million 5 billion) Large (>$5 billion) ETL managers or developers BI tool managers or developers Business analysts Support staff/help desk Data analysts or data modelers Program/project managers DW administrators/dbas Business sponsors DQ analysts BI/DW architects Portal/application developers Trainers/educators TOTAL Surprisingly, there is no correlation between staff size and BI/DW maturity. Figures based on averages. Newbie (0 1 iteration) Overhauling BI/DW Mature (2+ iterations) Total FTE FTE added in Contractors 14% 26% 24% Outsourced 3% 8% 8% Offshored 5% 7% 7% 12

13 BI BUDGETS BI Budgets The BI budget represents a very small percentage of the overall IT budget. Considering that BI provides information and insights that improve decision making and planning, this is woefully inadequate. Unfortunately, we can t easily calculate the costs of poor decisions made on insufficient or inaccurate data. BI budgets are growing at a fairly fast rate across the board compared to other areas of IT. This bodes well for the growth of BI in organizations Annual Budget Average: $2.5 million Don t know 9% > $10 million 4% $5 10 million 7% $2.5 5 million 19% Fiscal Year Budget Changes + 10% or more + 5 9% + 3 4% + 1 2% Stay same 9% 8% 8% 5% 13% 17% 20% 27% 42% 32% 20% < $500,000 14% $500,000 1 million 27% $1 2.5 million 1 5% 10% or more 3% 5% 5% 6% FY04 FY05 (average change: +4.9%) FY05 FY06 (average change: +3.8%) Budgets increase with company size, with midsize companies getting the biggest increase this year. Figures based on averages. Small (<$500 million) Medium ($500 million- 5 billion) Large (>$5 billion) Average budget $820,000 $2.64 million $4.64 million FY04 FY05 budget change +5.6% +3.9% +5.4% FY05 FY06 budget change +4.0% +5.5% +3.3% BI/DW budget as percentage of IT budget 4.4% 3.9% 3.7% 13

14 BI SUPPORT PROCESSES BI Support Processes Our survey revealed a low ratio of support calls to active BI users, for three possible reasons: 1. BI tools work as advertised! This is the optimistic scenario. 2. Most support calls are handled by power users within the departments. 3. Most BI users aren t actively using the tools. (See page 16; only 39 percent of potential BI users actively use BI tools.) This is the pessimistic scenario. And surprisingly, the percentage of help tickets handled by developers increases with older projects. We would expect this to decrease as companies become more experienced with BI and separate their development teams from their support teams. The ratio of help tickets to active users is very small, and developers handle the majority of calls. Small (<$500 million) Medium ($500 million 5 billion) Large (>$5 billion) Average active users ,271 Average help tickets per month Average tickets per active user per month Percentage of tickets handled by: developers help desk other 52% 28% 17% 50% 37% 17% 47% 49% 11% New BI projects have a slightly higher ratio of help tickets to active users than older projects. Figures based on averages. Newbie (0 1 iterations) Overhauling BI/DW Mature (2+ iterations) Average active users 217 1,540 1,614 Average help tickets per month Average tickets per active user per month Percentage of tickets handled by: developers help desk other 39% 47% 19% 53% 40% 8% 55% 34% 17% 14

15 BI ARCHITECTURES BI Architectures The data on architectures hasn t changed much in years. Hub-andspoke (i.e., the Inmon approach) wins the day as the primary data warehousing architecture. However, anecdotal evidence suggests that the data mart bus (i.e., the Kimball approach) is the preferred way to design data marts. Interestingly, most data marts are logically and physically centralized. This is a far cry from the early days of data warehousing, when everyone thought they would maintain data warehouses centrally and deploy data marts on separate servers managed remotely by the departments using them. Data warehousing, it seems, thrives on a more centralized approach. Data marts are here to stay, and the most popular kind are those that are spawned from enterprise data warehouses, some of which can grow quite large. We used the median numbers here because a few companies with extremely large data warehousing environments skewed the average (mean) significantly. Nonetheless, the typical data warehouse contains a lot of data! And most companies have a lot of data warehousing structures scattered about. Most data marts and operational data stores (ODS) are not as disposable as once thought. Once built, they tend to persist and gain substantial numbers of users and data. Interestingly, the Inmon hub-and-spoke approach typically places aggregated data in data marts (often deployed as dimensional cubes), while the Kimball Hub-and-spoke architecture with centralized data marts is most common. Primary DW Architecture Independent data marts or spreadmarts 9% Data mart bus: linked data marts with no DW 10% Central DW: no data marts 17% Data Mart Architecture Database views within a DW Logically distinct tables in the same database Physically distinct databases on the same server Physically distinct databases on different local servers Physically distinct databases on different remote servers Doesn t apply or other Companies typically have 9 dependent data marts running against an 875 GB data warehouse that grows by 175 GB a year Data Mart Proliferation Median Data warehouses 1.7 Dependent data marts 9.1 Independent data marts 3.1 Operational data stores 6.0 Spreadmarts 2.6 1% Virtual: BI tools running directly against OLTP systems 63% Hub-and-spoke: central DW with dependent data marts 36% 36% 33% 22% 14% 10% Data Warehouse Average Median Total raw data 5.22 TB 875 GB Raw data added each year 1.5 TB 175 GB Most companies data marts and ODSs support hundreds of users and gigabytes of data, and are permanent fixtures. Data Warehouse Data marts ODS Active users Raw data GB GB Frequency of creation 30% quarterly 28% yearly yearly Longevity 3+ years 3+ years continued next page 15

16 BI ARCHITECTURES approach advocates putting all the detailed data into the marts. This provides added justification that most data marts adhere to the Kimball approach and contain detailed data. Companies are working hard to establish a standard set of BI tools, at least one per category listed to the right. However, a minority of companies believe that departments should purchase whatever tools they want, as long as they are leveraging the same data and adhering to common data definitions and rules. Of course, the proliferation of BI tools increases the chances that data definitions and rules will get out of sync from one department to the next. Vendors are helping on the consolidation front by acquiring each other and merging once-distinct toolsets into SOA-based BI platforms. This trend will continue, so expect the 3.2 average number of BI vendors to decline in coming years. BI user and usage percentages have almost doubled since we asked this question in a survey a year ago. We are making progress, but still have a ways to go before BI usage proliferates to all users who could benefit from it. We expect the number of reports run per day to explode in coming years as more companies push reports to users via and make reports available to customers and suppliers. External report consumption today accounts for only 15 percent of all reports generated in a company, on average. Companies have a proliferation of BI tools and vendors. Average Number of BI Vendors by Company Revenues Less than $500 million in revenues 2.3 $500 million to $5 billion in revenues 3.1 More than $5 billion in revenues 3.7 BI vendors on average: 3.2 Type of Tool Number of distinct tools, built or bought Production reporting 2.8 OLAP 2.8 End user query/reporting 2.1 Dashboards/scorecards 2.1 Data mining 1.6 Planning/modeling 1.5 TOTAL 12.9 From Enterprise BI: Strategies and Technologies for Deploying BI on an Enterprise Scale by Wayne Eckerson and Cindi Howson, TDWI research report, August BI Users and Usage Potential BI users with a BI license Licensed BI users who use the tool regularly Active BI users in an organization Penetration of BI usage is low. Report Processing Reports run per day 425 Reports pushed to users 35% Reports consumed externally 15% 39% 55% 71% 16

17 CONCLUSION Conclusion Companies are investing a lot of money and time building BI/DW environments to improve decision making, increase transparency of the business, and become more proactive in managing events. As teams and budgets get bigger, BI directors will shoulder increasing responsibility to deliver tangible business value in a short time, increasing the risks but also the rewards. Given this added responsibility, it should be no surprise that BI directors are among the top wage earners in the IT department. But most are working hard for the money: they oversee teams of 20 or more, many of whom are outsourced or offshored; manage a budget of $2.5 million; and are overhauling BI programs, adding new subject areas every three to four months. 17

18 About TDWI The Data Warehousing Institute (TDWI), a division of 1105 Media, Inc., is the premier provider of in-depth, high-quality education and research in the business intelligence and data warehousing industry. TDWI is dedicated to educating business and information technology professionals about the strategies, techniques, and tools required to successfully design, build, and maintain business intelligence and data warehousing solutions. It also fosters the advancement of business intelligence and data warehousing research and contributes to knowledge transfer and the professional development of its Members. TDWI sponsors and promotes a worldwide Membership program, quarterly educational conferences, regional educational seminars, onsite courses, solution provider partnerships, an awards program for best practices, resourceful publications, an in-depth research program, and a comprehensive Web site Monster Road SW Suite 250 Renton, WA T F info@tdwi.org The Data Warehousing Institute