What is the future for QA Analysts in Canada?

I wanted to generate some thought on how the QA role is changing in Canada.

The largest fix costs associated with QA by far is that of labour. Let’s look at some average QA analyst salaries using Salary.com Canadian median numbers to avoid debate.

Finding the right balance and mix of staff, seniority, skill set, to work load is a difficult endeavour. Do you set aside individuals to do client vs. server, performance vs. functionality, regression vs. pre-production etc.

For simplicity let’s say Acme Inc has 10 QA staff all level 2 QA Analysts and one QA director.  Their application has 4 releases a year.  The calculation for wages expense would be 10 employees x C$61,839 wage = C$618,390 + C$107,355 for the director = C$725,745 excluding additional costs associated with an employee like office, equipment, management overhead etc. That’s C$181,436.25 a release. It’s not surprising that management focus is often on ways to reduce this amount.  Attempts at cutting the costs of labour, usually comes in the a few forms

1)      End User QA Approach

The end user approach usually starts with an attempt to reduce the number of QA staff. If all things remain the same, this translates into less time spent testing and less completed test cases. Reducing the amount of QA done in each release can show short term cost savings. Perhaps it’s dropping the number of test cases; perhaps it’s not doing performance, integration, security, identity or some other aspect of testing, or perhaps its ignoring regression testing or some maintenance. Something must be cut out of the QA process due to lower number of available QA hours.

So for example Acme cuts the number of QA staff down from 10 to 7 and reduces the director to a Manager. The new costs can be calculated as; 7 QA staff x C$61,839 wages = C$432873+ C$93,642 manager = C$526,515 or a saving of C$199,230

If reducing staff results in additional software quality in production, the costs savings won’t last long. Once in production, it’s usually a malicious exploit, data integrity issues or end user that brings attention to them.  Since they failed in their prime purpose to identifying these software quality issues before production, this can tarnish QA reputation and the Acme’s. The cost associated with maliciously exploited or data integrity issues, or loss of brand aside, management will focus back on QA, often erases the savings when they hire back up to 10 QA staff.

This leaves the previously untested software backlog and the need for a “clean up” program to retest and trace bugs and patches. “Cleaning up” can require higher QA Analyst skill levels and extensive experience in understanding the impacts of repairing something added 3 releases ago. Let’s say 2 people at QA level 3 and a manager for an additional annual cost of C$244,812. Increasing total QA staffing costs to $970,557 a year.

2)      The Lowest Wage Approach

The lowest wage approach is when there is an attempt to reduce the average hourly wage spent on QA staff. This usually takes the form of underpaying QA staff or reducing the skill level.

Say Acme keeps 10 staff and a director, but pays them 10% less than market rates, and hires only level 1 QA analysts.  The new costs can be calculated as ; Level 1 QA Analyst less 10% = C$48,117 + C$96,619 for a director = C$577,789. A saving of $147,956 a year. The equivalent of reducing the number of level 2 QA analysts from 10 to 8 in the example above.

Underpaying QA staff results in high staff turnover, lower skilled employees, lower morale and lower productivity in general.  Each new employee can take months to become familiar with the business requirements, test environments, application, processes, tools, and people. Low morale, can introduce lower quality in your quality testing. Additional training and support costs can also factor in.

The real question is if a QA analyst level 1 paid below market average 80% or more as productive as a QA analyst Level 2 paid on average. Is the increase in experience and hopefully ability of a higher paid QA consultant worth it? If productivity drops, the result is either the need to hiring more QA staff erasing the savings or similar issues as outlined in 1 above

3)      The Offshore Approach

According to Payscale.com the average QA Analyst in India earns Rs431,142 a year. (Range of 184,437 – Rs 824,054). What if Acme could hire 8 QA staff in India, 2 and the director locally? The new costs can be calculated as Rs431,142 /year conversion C$7,330 /year x 8 QA = C$58,640 + 2 x C$61,839 Canadian QA = C$182,318 + C$107,355 for the Director = C$289,673 / year. All things being the same, that’s a savings of $436,072 / year!

The reality is it will be somewhat less. Acme needs an office India which will have overhead costs. Alternately, they could use a 3^rd party outsource company, but pay a much higher hourly rate per developer, as the company would need to cover its overhead and make a profit. There is much written on outsourcing QA to countries like Brazil, India, Ukraine etc, covering the challenges and benefits and I won’t try cover it here. The maths in the example above is clearly not true, yet clearly serves to indicate the scale of the wages gap.

4)      Best Practices Approach

Here the focus is about finding more effective ways to approach QA in order to gain larger efficiencies out of the largest cost – labour.  It’s about decreasing inefficiencies of staff, identifying quality issues earlier and faster, defining staff roles, sourcing and training the right people, using the right tools and developing the right business process.  The best place starts reviewing the SDLC business process in your organization. Once QA’s role is defined, it can drill down into the QA Process, Testing and KPI.

Best practices business case is slightly different. The new costs can be calculated as: 10 QA workers, work 52 weeks, less say 4 weeks’ vacation and 1 week health related.  That’s 52-5 = 47 weeks.  10 QA testers x 47 weeks x 40 hour = 18, 800 hours of labour. We all know management is overhead and does not work so 725,745 (current labour costs) /18,800 (effect hours) gives Acme QA team a blended rate of C$38.60 /hour Let’s say, through best practices and Automation, Acme manages to maintain the same level of testing, but only require 3,500 hours per release. The savings can be calculated as  3,500 x 4 releases = 14,000 x blended rate C$38.60 = $540,400 or a saving of $185,345. Enough pay for 2 more QA staff, training and some additional tools.

So what are some things could Acme do to save that number of hours while still cover the same amount of testing?

• Reduction in code drops. Say development to production averaged 7 code drops  and hence testing cycles, including pre-production. After better defining entrance points, the average drops to 6 code drops saving nearly 8% of QA test cycles.
• If installing the lab after hours saved 3 hours of QA downtime = 4 releases/year x 7 (now 6) code drops x 3 hours x 10 QA x  C$38.60 rate= C$32,424 savings.
• Functional testing script maintenance reduced by 15 minutes per test case. 40 test cases per QA x .25 /hours x 7 drops x 4 releases x  10 QA  x  C$38.60 /hour =  C$108,080
• Performance Test Script time reduction, regression testing, splitting client and services testing, giving development subset to test before accepting delivery etc. 
  

Conclusion

In the rapidly changing world of the Data economy, QA testing needs to change to keep pace. Finding a better approach, providing training and identifying economies, may have being management areas in the past.  As a QA professional in Canada however, your role will remain at risk of being outsourced to far cheaper economies, unless you increase YOUR Personal value.

The answer I see is QA professionals in Canada need to develop their role into that QA thought leadership. Developing and proving expertise that justify the higher cost of their employment. Constantly revising best practices, updating their skills and reviewing alternates approaches. Join organizations like TASSQ, VANQ, or OSQA etc and network with other like minded QA professionals , sharing successes / failures,  learn new things. Honing their skills in an effort to reduce manual labour intensive testing resources.

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