DSS

Hi all,

I am new to the forum, also new to BI. I have been working for marketing research agency for quite sometime now i am trying into BI. As i understand Market Intelligence, Business Intelligence and Competitive Intelligence are 3 major components in Decision Support System, i want to know is there real serious correlation among these components. what i am trying to understand here is how far these field contribute to DSS of any corporation. It can be evaluate better by understanding contribution by BI vs. MI and BI vs. CI and MI vs. CI.

i appreciate your help!
thanks,
zabb

Skills and Competencies

Hello,
I was just wondering if anyone had any ideas about the types of skills and competencies that are needed by staff at all levels in an organisation that is trying to effectively use information?
I'm talking about Data Steward Roles, Data Management roles etc and even if there are some basic skills that all staff who work with data and information should have. If anyone has got any info or any idea where I could start looking for ideas then I would very much appreciate it. I have got a few ideas but I could definitely do with doing a bit more research into this!
Thank You

Scorecards and Dashboards For Contact Centre

Hi, I found a interesting Article:

Scorecards and Dashboards For Contact Centre:
According to Harvard Business Review, the Balanced Scorecard concept is the most influential management idea in the past 75 years. The performance of an organization is tracked against four key perspectives such as Finance, Customers, Internal Processes and finally Learning, Innovation and Growth. These perspectives are divided into multiple sets of Key Performance Indicators ( KPIs ) and grouped against these perspectives and further broken from top level to the employee level KPIs.

Companies are globally moving towards implementing enterprise wide organizational Balanced Scorecard. Simplicity, personalization and empowerment are the keys while building Agent Dashboards. These goals are achieved through the application of Business Intelligence ( BI ) concepts. A contact center performance is an aggregation of every agent performance.

An Agent should be able to customize and get the unified view of the aggregated metrics and track them on daily basis. How much he has achieved with respect to target? How his performance benchmarked with respect to overall call center performance. Is there performance improvement over a period of time? He can drill down and see which particular KPI is bringing his overall score down and he can see how he has or has not been able to improve his performance over a period of time.

A Supervisor should be able to see how agents reporting to him are performing. His Dashboard should show an aggregated score of all his agents and simultaneously showing tabular information of comparative scores of all agents working under him. He can drill down on agent score who are not performing well. He can see individual KPIs of agents and study whether there are improvements over a period of time under the respective KPI.

A Manager would like to see dashboards of aggregated scores of supervisors on weekly basis rather than daily basis. He can drill down till agent’s individual KPI level if he desires. A manager could also drill down against different channels and see the performance of different supervisors under different channels.

A Call Center Head would like to see the aggregated performance of his senior managers and across channels and will be interested to track performance against KPIs on monthly basis. He can drill down from manager level right up to the agent level and their individual KPIs to see where the actual pains are located.

A Quality Manager would like to see how agents are performing against quality related KPIs. He would further like to analyze poor performing KPIs against type of service requests, type of channel and may be against important set of clients so that specific training programs could be designed for specific sets of agents rather than a plane blanket approach where every one is trained for everything.

In all the performance metrics could be analyzed against multiple dimensions such as channels customers, type of services, location etc. Users down the line are empowered to analyze the data and able to get operational and strategic insights. Hundreds of variants of Dashboards and Reports could be created from a simple single user friendly interactive interface

All above could be simply achieved through web browser and single user interactive interface. Every person in the organization can personalize the dashboard or reports from this single user interface. The power of analysis is coupled into the reporting and dashboard. It is this Business Intelligence capability that creates the unique customer experience in getting the insights of business.

Best Analytics Practices

Hi,
Just read an interesting article by Babson-Professor Thomas H. Davenport in the Harvard BR of January 06 about how companies compete on analytics.
What I liked most was a handy top-10 of Best Analytics Practices, thought I'd quickly share it with you guys:

1. Apply sophisticated information systems and rigorous analysis to both your core capability and other functions.
2. Executive team recognizes and focuses on the importance of analytics capabilities.
3. Treat fact-based decision-making as a part of the company culture.
4. Hire the very best analytical people.
5. Manage analytics at the enterprise level.
6. Apply proprietary metrics for key business processes.
7. Share data and analysis with customers and suppliers.
8. Generate information whenever possible and create a "test and learn" culture.
9. Has been building analytics capabilities for several years now.
10. Make your quantitative capabilities part of your corporate reputation.

Has anyone worked in BI?

Hi All,

I would like to know whether any person in this forum has actual experience with BI. I would like to know how BI has influenced the decision making process in your experience. Thanks for your replies.

Venkat

30 ways to use OLAP in business

An interesting article by Contour Components discloses 30 ways on where OLAP or multidimensional data analysis is applicable. OLAP is a specific way of financial and statistical data representation for executives, specialists and analysts. It is designed to aid in decision making and better information understanding. The main idea is to answer the user’s questions, arising at the work time, on-the-fly.

An OLAP system allows user to get into details and generalize, filter, sort and regroup data at the time of analysis. Intermediate and final totals are recalculated instantly.

The main data viewing and manipulation tool is the dynamic electronic worksheet. Its elements – columns and rows – are the manipulation controls. Moving rows and columns or clicking them user makes the system perform calculations and show data in different aspects.

Thus, user can produce lots of reports out of a single dataset on his own, without any interference with IT-specialists. This saves IT departments from continuous hard-coding of various kinds of reports and gives additional degree of freedom to executives and specialists for getting the essential information.

OLAP breaks data into two groups: facts (numbers, also called measures) and dimensions (descriptions). Facts are aggregated in a given slice by some algorithm while the user defines grouping and aggregation depth.

Also, an electronic worksheet can display data with a regular structure. OLAP is suitable everywhere, where a task of multifactor data analysis takes place. Generally, having a table filled with data, given that it contains at least one descriptive column and one or more data columns, OLAP can become an effective and convenient tool for analyzing such table and producing reports.

Read 30 ideas of using OLAP

Bestselling books on data warehousing and decision-making

Simulation in BI

Imagine yourself running through your own simulated B., trying to take intelligent decisions and maneuvering through increasingly competitive landscapes, in a way like a DOOM or QUAKE or a racing game. If you take poor decisions you will see the way your company suffers; if you invent and implement the right strategies you'll get a promotion, your company's shareholder value will increase and of course your difficulty level will be increased.

If this sounds like too far-fetched for you, you might be wrong. A survey conducted by Chief Learning Officer showed 55% of respondents are already using simulations in their corporation for workforce education. Over 80% of respondents have either acquired or developed simulations.

Looking at these figures, you might be wondering if BI simulations have already become mainstream? Well, less than a third of those surveyed said simulations had impacted their organizational learning processes to a significant degree so the answer to this question is NO.
Why? The reasons for B. Simulation still being a Brave New World field include:

• the high cost of creating simulations
• lack of organizational infrastructure
• scarcity of quality products and services
• deficiency of management-level comprehension on B. simulation

Despite of these obstacles, no less then 83 percent of the respondents currently using simulations expect an increase in the use of these tools in the next two years.

Like any major innovation in the past, the adoption of BI simulation probably will take longer than expected, but its impact will also most likely be much bigger than anticipated. Making sure your company is amongst the early adopters would seem advisable.

What is BI really? Multiple Versions of the Truth

What is BI really? Here are some 'versions of the truth':
- According to a website BI is a broad category of Management Information Systems, applications and technologies for gathering, storing, analyzing, and providing access to data to help enterprise users make better B. decisions.
An article by Peter Bochner and Jack Vaughan mentions a few more definitions:
- The process firms go through to gather, store and analyze data.
- A critical activity that helps companies to make faster, smarter decisions, as well as increase revenue, build customer loyalty, streamline operations, improve risk management and even enable previously impossible B. processes.
- A constantly evolving strategy, vision and architecture that continuously seeks to align an organization’s operations and direction with its strategic B. goals.
- The theory that the more you know about your customers and the B. problem you’re trying to solve, the better you’re able to solve it.
- According to Danny Siegel from Pfizer Inc an effective BI system provides corporations with “one version of the truth”.

Ain't it funny that there is no single version of the truth about what BI is? Perhaps one of you has an even better definition to share with us?

Strategic decisions still taken based on 'gut feel'

A new research study conducted by B. Week Research Services and B. Objects shows that more than half of the critical B. decisions made in organizations are based on 'gut feel' and experience, rather than sound and verifiable information. The study, titled “The Fact Gap: The Disconnect Between Data and Decisions” of 675 executives assesses the state of information access and decision making within organizations throughout the United States and Europe.

The majority of survey participants - 77 percent - indicated that they were aware of bad B. decisions made within their organization because of insufficient information. In addition, nearly all recognize that inefficient information access significantly impacts the overall productivity of their organization. The survey also shows that businesses are buried by a glut of incompatible applications and databases, and organizations are struggling to make the various systems work together.

More Key findings from the research include:

• Two-thirds of executives identified that more than half of their important B. decisions are based on 'gut feel' and experience, rather than on sound and verifiable information;
• 77 percent of respondents are aware of bad decisions that managers have made within their organizations because they did not have access to accurate information;
• A chasm exists between low-level tactical decisions and high-value decision making, with a majority of time spent on routine, day-to-day tactical decisions, rather than on strategic decisions with the greatest impact on B. success;
• There are more critical B. decisions that need to be made compared to two years ago, and it is becoming more challenging to make important B. decisions
  Data retrieval is not just an annoyance, but has a material impact on overall productivity of the B.

It seems BI for now remains a conceptual paradise of decision software suppliers.