How does an enterprise — especially a large, global one with multiple product lines and multiple enterprise resource planning (ERP) applications — make sense of operations, logistics, and finances? There’s just too much information for any one person to process. It’s business intelligence (BI) to the rescue! But what is BI, and how does BI differ from reporting and management information systems (MIS)? What is the business impact, and what are the costs versus the benefits? What is the appropriate strategy for implementing BI and achieving continued BI success? Our new report will give business and IT executives an understanding of the four critical phases of strategizing around BI to achieve business goals — or “everything you wanted to know but were afraid to ask” about BI. Here’s a sneak preview of the kinds of topics the report covers and the kinds of BI questions one needs to ask in order to build an effective and efficient enterprise BI environment:

1. Prepare For Your BI Program
   1. The future of BI is all about agility. IT no longer has exclusive control of BI platforms, tools, and applications; business users demand more empowerment (or make empowered changes without IT involvement), and previously unshakable pillars of the BI foundation such as relational databases are quickly being supplemented with alternative BI platforms. It’s no longer business as usual. Ask yourself:
      
      1. What are the main business and IT trends driving BI?
      2. What are the latest BI technologies that I need to know about?
      3. What’s out there beyond traditional BI?

My colleagues and I have just completed yet another engagement with a large client — one of dozens recently — who was facing a to be or not to be decision: whether to move its BI platform and applications to the cloud. It’s a very typical question that our clients are asking these days, mainly for the following two reasons:

1. In many cases, their current on-premises BI solutions are too inflexible to support the business now, much less in the future.
2. The relative success of cloud-based CRM (SFDC and others) solutions may indicate that cloud offers a better alternative.

These clients put these two statements together and make the reasonable assumption that cloud BI will solve many of the current BI challenges that cloud-based CRM solved. Reasonable? Yes. Correct? Not so fast — the only correct answer is “It depends.”

Let’s take a couple of steps back. First, let’s define applications or packaged solutions vs. platforms (because BI requires both).

Packaged solutions

• Subscribe to a solution-like CRM
• Provide standard business functions to all customers (which makes it different from “hosting;” see below)
• Difficult to tailor to specific needs
• Usually are used synonymously (but incorrectly, see below) with software-as-a-service (SaaS)

 Platforms for building solutions

• Subscribe to tools and resources to build solutions like CRM
• Provide standard technical functions to developers
• Contain limited, if any, business application functionality
• Usually labeled either as platform-as-a-service (PaaS) or infrastructure-as-a-service (IaaS).

Demands by users of business intelligence (BI) applications to "just get it done" are turning typical BI relationships, such as business/IT alignment and the roles that traditional and next-generation BI technologies play, upside down. As business users demand more control over BI applications, IT is losing its once-exclusive control over BI platforms, tools, and applications. It's no longer business as usual: For example, organizations are supplementing previously unshakable pillars of BI, such as tightly controlled relational databases, with alternative platforms. Forrester recommends that business and IT professionals responsible for BI understand and start embracing some of the latest BI trends — or risk falling behind.

Traditional BI approaches often fall short for the two following reasons (among many others):

• BI hasn't fully empowered information workers, who still largely depend on IT
• BI platforms, tools and applications aren't agile enough

This is a very smart move by Oracle. Until the Siebel and Hyperion acquisitions, Oracle was not a leader in the BI and analytics space. Those acquisitions put them squarely in the top three together with IBM and SAP. However, until this morning, Oracle played mostly in the traditional BI space: reporting, querying, and analytics based on relational databases. But these mainstream relational databases are an awkward fit for BI. You can use them, but it requires lots of tuning and customization and constant optimization — which is difficult, time-consuming, and costly. Unfortunately, row-based RDBMSes like IBM DB2, Microsoft SQL Server, Oracle, and Sybase ASE were originally designed and architected for transaction processing, not reporting and analysis. In order to tune such a RDBMS for BI usage, specifically data warehousing, architects usually:

• Denormalize data models to optimize reporting and analysis.
• Build indexes to optimize queries.
• Build aggregate tables to optimize summary queries.
• Build OLAP cubes to further optimize analytic queries.

I need your help. I am conducting research into business intelligence (BI) software prices: averages, differences between license and subscription deals, differences between small and large vendor offerings, etc. In order to help our clients look beyond just the software pricese and consider the fully loaded total cost of ownership, I also want to throw in service and hardware costs (I already have data on annual maintenance and initial training costs). I’ve been in this market long enough to understand that the only correct answer is “It depends” — on the levels of data complexity, data cleanliness, use cases, and many other factors. But, if I could pin you down to a ballpark formula for budgeting and estimation purposes, what would that be? Here are my initial thoughts — based on experience, other relevant research, etc.

• Initial hardware as a percentage of software cost = 33% to 50%
• Ongoing hardware maintenance = 20% of the initial hardware cost
• Initial design, build, implementation of services. Our rule of thumb has always been 300% to 700%, but that obviously varies by deal sizes. So here’s what I came up with:
  • Less than $100,000 in software = 100% in services
  • $100,000 to $500,000 in software = 300% in services
  • $500,000 to $2 million in software = 200% in services
  • $2 million to $10 million in software = 50% in services
  • More than $10 million in software = 25% in services
• Then 20% of the initial software cost for ongoing maintenance, enhancements, and support

Thoughts? Again, I am  not looking for “it depends” answers, but rather for some numbers and ranges based on your experience.