Data mart approach and Evidenced-based management approaches have striking similarities as follows;
data mart approach’s focus on a particular subject or department to help management make strategic decision about their business is similar to Evidenced based Management’s approach’s defining the objective and information needs, based on that collecting data and analyzing and turning that data into insights and presenting that into insights.
Instead of focusing on collecting everything that is easily measured and counted, organization’s need to be more systematic and selective about the information they are gathering.[1]
Source:
1- Moving from data to insights by Bernard Marr - Management by Certified Management Accounting Canada -June/July 2009.
Business intelligence should be driven by decision maker’s information needs. Business intelligence should answered there business questions such as;
What fact, figures, statistics, and so forth do they need for effective decision making?
How should this information be sliced and diced for analysis? (dimensions)
What additional information can aid in finding exactly what is needed? (attributes)[1]
Source:
1- Delivering Business Intelligence with Sql Server 2008 by Brian Larson
In continuation to our previous post on evidence-based intelligence, we are writing more on the step 1 of defining aims and information needs.
In this step the focus should be on manger’s information needs identification and objective of these. In other words organization’s information needs to be highly selective.
Identify strategic objectives/information needs – here we link the data we collect to most important drivers of value and performance. This insures that analytics we generate (a) are relevant to organization’s competitive positioning, (b) support its greatest information needs, and are not (c) wasted on irrelevant information. [1]
Identify who has the information needs
Here it is important to target audience (information customers)
Information customers can be groups of people such as the board of directors, senior managers, the HR and marketing departments, or a single person.[1]
Clarify what questions they want answered
The aim is to ensure that analytics provide the knowledge that will enable the recipients to make most appropriate and focused business decision.
Clarify what decision needs to be taken
We need to clearly identify any important decisions the data support.
Our point of view: the above steps are true for business intelligence and data mart development.
Source:
1 - Intelligence required - moving from data to insights by Bernard Marr - Management by CMA
Layout-led discovery
When we know the questions we want answered and have a good idea where that answer is going to be found, we can use the printed reports to deliver our business intelligence.
This is the most common form of business intelligence. [1]
For example we want to know employee productivity for bonus calculations we know where to find the information and we can design the report in Crystal reports or Sql Reporting services, to retrieve the information, and reports are effective business intelligence tools. This is an example of layout-led discovery.
With layout-led discovery, we learn answers to our questions for example we will find some employees have to high productivity and some have low productivity. If there is not enough information, for example for the reasons of high and low productivity in employees we may not have sufficient details. We may need to know nature of work / profitability analyses on task assigned to various employees. We need supporting details for informed decision making.
Data led discovery
This often occurs when the information we initially received changes the questions slightly.[1]
In our previous example we find an information anomaly, a significant difference in employee productivity. This may cause us to look at data differently and we want to follow the data that catches our attention.
This may called a data led discovery. To implement data-led discovery we need some interactive mechanism for drill down and viewing the report in different perspectives. It can be implemented through interactive reports in Crystal reports / Sql Server reporting services.
Source:
1- Delivering Business Intelligence with Microsoft Sql Server 2008 by Brian Larson
This post is about if then else statement examples using PUBS database.
Examples
A. Use one IF…ELSE block
This example shows an IF condition with a statement block. If the average price of the title is not less than $15, it prints the text: Average title price is more than $15.
USE pubs
IF (SELECT AVG(price) FROM titles WHERE type = ‘mod_cook’) < $15
BEGIN
PRINT 'The following titles are excellent mod_cook books:'
PRINT ' '
SELECT SUBSTRING(title, 1, 35) AS Title
FROM titles
WHERE type = 'mod_cook'
END
ELSE
PRINT 'Average title price is more than $15.'
Here is the result set:
The following titles are excellent mod_cook books:
Title
-----------------------------------
Silicon Valley Gastronomic Treats
The Gourmet Microwave
(2 row(s) affected)
B. Use more than one IF...ELSE block
This example uses two IF blocks. If the average price of the title is not less than $15, it prints the text: Average title price is more than $15. If the average price of modern cookbooks is more than $15, the statement that the modern cookbooks are expensive is printed.
USE pubs
IF (SELECT AVG(price) FROM titles WHERE type = 'mod_cook') < $15
BEGIN
PRINT 'The following titles are excellent mod_cook books:'
PRINT ' '
SELECT SUBSTRING(title, 1, 35) AS Title
FROM titles
WHERE type = 'mod_cook'
END
ELSE
IF (SELECT AVG(price) FROM titles WHERE type = 'mod_cook') > $15
BEGIN
PRINT ‘The following titles are expensive mod_cook books:’
PRINT ‘ ‘
SELECT SUBSTRING(title, 1, 35) AS Title
FROM titles
WHERE type = ‘mod_cook’
END
This post is about Evidence-Based Management published under article “Intelligence required Moving from data to insight” by Bernard Marr - CMA Management magazine, June/July 2009 .
Through Evidence-Based management, organizations explicitly use evidence (the best and most appropriate information) to guide the decision-making process to extract maximum value and competitive advantage from their data and information. According to Stanford University Professor Robert Sutton EBM is simple idea: It just means finding the best evidence that you can, facing those facts, and acting on those facts – rather than doing what everyone else does, what you have always done, or what you thought was true. We like this statement.
Five steps towards evidence-based management (EBM)
Step 1: Defining objective and information needs.
Step2: Based on step 1 collecting data.
Step 3: Analyzing data – focus on turning data into relevant insights.
Step 4: Presenting information – focusing on communicating the information and insights to business decision makers - extracted in step 3.
Step 5: Making evidence based decision concerned with Turing information into knowledge and decisions.
Role of information technology in EBM
IT and Business intelligence (BI) plays an important role in Evidence-Based management. Right steps should be taken and most important is common sense and something we do intuitively, instead of believing that state-of-the art Business Intelligence infrastructure will resolve all the problems.
Our point of view: we strongly agree with the evidence-based management techniques presented above, especially Professor Robert Sutton’s statement that finding the best evidence, facing those facts, and acting on those facts.
This post is to analyze the point of view by Oracle’s vice-president for Enterprise Performance Management; Mark Wilkinson, published in Computer weekly under article “Companies fail to get the most out of business data” by Cliff Saran in Mar 2009.
Oracle’s vice-president for Enterprise Performance Management, Mark Wilkinson, said, “The research shows that companies are good at visualizing historical data, but not so good at forecasting and scenario planning.”
He suggested that the use of desktop business intelligence tools was hindering companies because data was distributed on PCs rather than centralized.
Our point of view: It is understood that centralized data warehouse / Data mart for data analyses / business intelligence is the right approach. However in our experience we need the centralized data imported into our variety of desktop business intelligence software’s for in-depth analyses by the business users. For example pivot tables in Excel, Crystal Reports and Microsoft SQL Reporting Services.
We believe that desktop business intelligence software’s are critical for analyzing historical data, forecasting and making informed decision making. The most important is to have the right data in centralized data warehouse or data marts for informed decision making the business users. The data warehouses / Data mart must be transparent to business decision makers.
Read this article
Organization’s data is critical for the success and Data governance is strategically important.
Read more about this article
Data governance is a set of processes that ensures that important data assets are formally managed throughout the enterprise. Data governance ensures that data can be trusted and that people can be made accountable for any adverse event that happens because of poor data quality.
It is about putting people in charge of fixing and preventing issues with data so that the enterprise can become more efficient. Data governance also describes an evolutionary process for a company, altering the company’s way of thinking and setting up the processes to handle information so that it may be utilized by the entire organization.
It’s about using technology when necessary in many forms to help aid the process. When companies desire, or are required, to gain control of their data, they empower their people, set up processes and get help from technology to do it. [1]
Source
1- Sarsfield, Steve (2009). “The Data Governance Imperative”, IT Governance
Right Master Data management (MDM) provides single version of the truth, MDM is critical to impact business positively. With proper (MDM), you will know exactly what products your customers have, what items you buy from selected vendors and business relations with your customers. Customer’s can be contacted with confidence.
Staff must agree on exactly what constitutes a “customer” or a “partner,” and how to resolve any disagreements across business units. Departments and divisions need to agree on hierarchies of customers and products and how to resolve duplicate records across sources.[1]
Source:
1- Demystifying Master Data Management by CIO.com