Application of the principles of quality management in the translation industry: Evidence-based decision making

Application of the principles of quality management in the translation industry: Evidence-based decision making

BURG Translations has been certified in the ISO 9001 process since 2009. This article is part 3 of a series of articles documenting our application of the ISO 9001 to our translation company.

Evidence-based decision making entails:

  • Ensuring the accessibility of accurate and reliable data
  • Using appropriate methods to analyze the data
  • Making decisions based on the analyses
  • Balancing the analyses with practical experience

Today, well organized companies have more access to data than ever before. This data should contribute to making business decisions in order to justify sound actions, and help produce predictable outcomes.

Ensuring the accessibility of accurate and reliable data

As meticulous documentation is a core component of the ISO 9001 process, meticulous data collection is an extension of it. Certain pieces of data, such as number of non-conformances, are a requirement. The better practice is to make well-structured analyzable data a core part of the corporate culture. As the old management saying goes, “if you can’t measure, you can’t manage it”.

At BURG, data validation is a largely automated process that is checked daily as a team. Daily performance metrics, including percent of missing data, are reviewed together as team and are addressed. Our data is categorized in the following ways:

  • Proposals
  • Projects
  • Accounts
  • Contacts
  • Invoices

Each category includes a series of data points that are required, such as proposal amount and time, project value, account sales, a contact’s relationship to their content, and who to contact for open invoices. As a result, the team seems daily the quality of our service, the health of our clients, and the health of our business.

Some questions that our data collection allows us to ask are:

  • Is the value of the proposal unusual for our client?
  • Is the project on time and on budget?
  • Is the account behaving normally?
  • Are our clients happy?
  • Is enough documentation collected to easily facilitate payment?

Using appropriate methods to analyze the data

General analysis of business data is rather straightforward. For example, one key metric used is “response time”, which is the time it takes for our team to reply to an email from a client. The analysis of “how many minutes does it take to reply to a client”, is to determine if the number of minutes is less than or equal to 60. Further analysis is to take the average and learn, on average, how long it takes to reply to a client.

Another example is non-conformance reports (NCRs), which is the number of times a final product does not conform to specification (whether or not the client is happy with the deliverable of a project), is measured along with the:

  • project number
  • name of the client involved
  • name of the Client Manager involved
  • exact claim made by the client
  • impact
  • immediate corrective action
  • long-term preventative action
  • date the client accepted our response
  • date Production Manager confirmed the success of the implementation of the preventative action

In this case, a trend analysis can be used to answer questions like:

  • is the number of NCRs increasing, staying the same, or decreasing over time?
  • Is there a particular client or Client Manager associated with NCRs?
  • How long does it take to implement a long-term preventative action?

In general, these types of analyses are very straight-forward to do in Excel. This general level of analysis can be applied to nearly any metric and provide Leadership with enough of an indication of the health of a department.

Making decisions based on the analyses

The results of an analysis alone are not enough to make decisions. Interpretation is what converts results of analyses into decisions. These interpretations are based on benchmarks like expectations or goals. For example, if we notice that a particular Client Manager has consistently lower response time than the rest of the team, it can be interpreted as a “faster Client Manager”. This might need validation from the Client Manager’s point of view. Do they have less work to do? Are they using a tool that allows them to respond faster? Or do they simply check their inbox more frequently? This type of probing is what leads to proper interpretation, good decision-making, and in this example, “best practices”, which are methods or ways of doing things that we feel are the “best way” to do something.

Each week we share challenges and solutions from around the team and pool our collective experiences to update our training documentation. Our documentation, driven by data analysis, is one of our more valuable company assets. It is the culmination of iterative decisions made to optimize methodologies and keep the company efficient and effective.

Balancing the analyses with practical experience

Not all data collected is measured exactly and not all data collected measures exactly what you want to measure. Furthermore, the results do not include realities of life, such as the human limits of a team or available resources.

To best apply results from an analysis, share the results with others, discuss the interpretation and collective conclude on a way forward. To minimize the number of meetings required, take advantage of the meetings already in place to include an agenda item. At BURG, we have training meetings specifically to discuss challenges the team are having, and to collective decide how we will move forward given the data and resources that we have.


One of the principles of quality management is evidence-based decision making. Evidence-based decision making depends on having good evidence, in the form of properly analyzed data that has been correctly interpreted. Collecting data in the first place is critical to any well-organized company and is central to the ISO 9001. For translation companies, collecting data on service quality, client satisfaction and business processes is essential to keeping costs low for clients while keeping the quality high. Companies that have embraced good documentation and data collection practices will always have a more stable track record of good decision making and happy clients. The ISO 9001 allows companies, like BURG Translations, to provide the highest level of performance at every stage of every project for every client.

This article is part 3 of a series of articles documenting our application of the ISO 9001 to our translation company. You can read the previous articles here:

Application of the Principles of Quality Management to the Translation Industry: Client Focus
Application of the principles of quality management in the translation industry: Engagement of People

If you’d like to learn more about how BURG Translations can help you improve your translation process and quality and reduce costs, please contact us today.

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