We strive to achieve
Highest quality and Reliability
in all our Data collection activities
While maintaining perfect
Communication with our Clients

Vision

To be THE BEST
Strategic Decision Support Partner
In
Healthcare Industry

We have well defined quality assurance and data validation processes. Strict quality checks and measures are put in place for online and offline projects separately. Quality assurance and Data validation (Online) Once we are through with processing of data and are ready to deliver, the data undergoes quality test by our analysts, to see if the data matches the client’s requirements. Quality check starts at the DP resource level, where they perform one layer of Quality check. The quality analyst performs the next and final layer of QA. The quality check involves the following procedures: Follow the readme.txt file, naming conventions, and standards Update questionnaire and understanding of questionnaire Verify if data is according to the approved layout Verify if all questions are in Marginal/Frequency Verify if the last column of the CE layout is same as in Marginal/Frequency script last column Check bases in Marginal/Frequency Verify if the respondent ID is unique Sort the data in CE file and OE file on the basis of Respid and verify if it is the same Remove junk data from the OE data

In depth Quality check includes the following procedure:

1. Single Punch/Grid Question --- The Quality Analyst checks the range codes for single punch questions and verifies if they have valid range codes. The forward and reverse filter conditions are checked. 
2. Multi Punch Questions --- The Quality Analyst checks the range codes for multi punch questions and verifies if they have valid codes. The forward and reverse filter conditions are checked. Also, if there is a none/valid exclusive code, other range codes are not selected. It is also verified that at least one respondent answers the question.
3. Straight lining Checked--- Quality Analyst performs this check on grid questions to find out if the respondent has punched same range code for all grid options.
4. SPSS Data Check----- Quality Analyst has a different set of guidelines to check SPSS data.

      The following checks are performed ------

1. Unique meaningful name to the variable
2. Number respondents and respids should be same as CE ASCII and OE Excel
3. Frequency of SPSS data is checked with frequency of clean data.

5.   Tabulation output checks:

1. Check for question title
2. Check for base sample or title
3. Check for stubs and their spelling
4. Match the values from the SPSS frequency
5. Check the means of the tables
6. Check the banner points as per the banner plan
7. Also check the table titles
8. Formatting of the tables and banner requires extra care
Quality assurance and Data validation (Off line)
1. Our QC process starts from the time the study is in the briefing stage. We run and check the questionnaires or DI guide for logical, arithmetical and administrative compliance, depending on the methodology. We implement and execute different QC procedures as mentioned below:

F2F / IDI Interviews: We start a study by conducting three mock interviews to finalise the right way to administer the questionnaire. Executives do a random 5% back check to start with, and then Independent Quality Controllers (QC) back check 30% of the questionnaires with respondents according to the contact details obtained during recruitment. A back-check questionnaire is designed including the basic information of the respondents as well as some key questions. QC back checks with the respondents over telephone. If the respondent is not reachable over telephone, QC visits the respondent's premises to conduct back check. Any flaws or discrepancies discovered during the validation are reported to the Project Managers. If the questionnaire has errors, it is conducted afresh.

• For Telephonic Interviews - Our team of QC are directly involved in the Telephonic Interviews and accompany at least 10% of SS with each interviewer and independently perform 20% of the SS telephonic back check with random question checks. Any flaws or discrepancies found during the back check are reported to the Project Managers. If the audio file has errors, it is taken out and conducted afresh.