Business intelligence is definitely at the top of the  pyramid when it comes to mining the benefits of the new web 3.0 which is essentially the next generation of "socially aware" consumers and rich business systems becoming more popular and  affordable for small businesses. We will fully explore this in other articles but with the vast amounts of data being processed daily without the interaction of good business automation or BI tools you could be shooting in the dark and easily get left behind. Quick note; the average BI IT spend is up 49% in 2009 even in the down turn economy.

I recommend getting started with two key concepts:

1.      Make sure you all speak the same language

2.      Clearly define roles and how you interact with your technology

There is a lot of jargon out there in the CRM/CMS and Business Intelligence gathering space. One of the key parts of deploying new technology systems to capture better BI and improve the efficiency of your organization will be to make sure you all are speaking the same language and understand clearly how you each interact with the technologies you are implementing. Since the business and management folks in any given organization often speak a different language than the folks in the IT or technical departments here is a good list of jargon to review and think about what it all means to your business as you begin discussions for deployment of new technology. Another key topic should be to map out what is important to the users in different roles within your organization because often there are varied interactions with the system across your team but they all contribute to the same core data that everyone will be using to make decision upon in your business.

Perhaps if you put this out in a business meeting you could discuss it and then offer to quiz folks. If they do not run you out of town perhaps they will laugh or at least think about all of this a bit more in-depth.

Any IT specialty has its jargon, but we seem to have more than our share in business intelligence. Having a lot of terms and acronyms is usually fine, but in BI we do not always agree on the definition and, even worse, we sometimes use different terms for the same thing.

If the experts, industry analysts and pundits cannot agree then how can everyone else understand what is going on? How do people learn this field and leverage others' experiences? Well let's take this into our own hands and workshop these terms since what really matters is what they mean to you and your collaborators and stakeholders that will leverage the technologies and processes you implement.

Here is a good jargon list of terms or acronyms to get started on. Pick the ones that apply:

• Business Intelligence (BI)
• Performance Management (PM)
• Customer Relationship Management (CRM)
• Customer Relationship Business management (CRBM)
• Content Management System (CMS)
• Learning Management System (LMS)
• Operational BI
• On-Line Analytical Processing (OLAP)
• Analytical Applications
• Predictive Analytics
• "Slice & Dice" and Drill down
• Data Mining
• Data Visualization
• Dashboards, Scorecards
• Key Performance Indicators (KPIs)
• Data Shadow Systems or Spreadmarts
• DW & BI Appliances
• Data Warehouses (DW)
• Enterprise Data Warehouse (EDW)
• Data Marts (DM)
• Operational Data Stores (ODS)
• Hub & Spoke Architecture
• Data Integration
• Extract, Transform & Load (ETL)
• Enterprise Application Integration (EAI)
• Enterprise Information Integration (EII)
• Extract, Load & Transform (ELT)
• Change Data Capture (CDC)
• SOA (Service Oriented Architecture)
• Real-time Access, BI, DI or DW
• SaaS (Software-as-a-Service) or On-Demand Software versus On-Premise Software
• Cloud Computing
• E/R Modeling versus Dimensional Modeling
• Dimensions & Facts
• Star & Snowflake Schemas versus 3NF (3rd Normal Form)
• Conformed Dimensions
• Slowly Changing Dimensions (SCD)
• MDM (Master Data Management)
• CDI (Customer Data Integration)
• PIM Product Information Management)
• Open Source Software (OSS)
• Relational versus Columnar Databases
• Unstructured Data
• Enterprise Data Mashups
• Data Governance
• Metadata Management
• Enterprise Information Management (EIM)
• BICC (BI Centers of Excellence)
• ICC (Integration Centers of Excellence)
• Data quality (DQ) & data cleansing
• SMP versus MPP

Once you have gone through all of these determine which ones apply either formally or informally in your business processes and can find a consensus on a clear definition you are on your way to getting on the same page. Next we should explore the roles which you should be able to pick off of your company org chart as they relate to departments and associated leadership responsibilities.

Examples:

• Sr. Leadership
• Sales
• Marketing
• Production
• IT - Data Security
• Accounting
• Shipping and Receiving

Once you are confident you have all of the access roles established then you should map them to how they will interact with the technology and associated business processes from the jargon listed above.

I am sure you can take this a few steps further but this may give you a good place to start thinking about how to map the people with the technology in your organization. The more you can plan all of this and get a good visualization in your head the better your chances are of success.

For a good mind mapping tool to help you get a good visualization try MindJet.com

These are the types of exercises we go through informally or formally in our strategic consulting and Value Building seminars and we welcome your participation.

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