Whether you are a medical device vendor or non-regulated SVP, most of your resources should be spent on your research and development department. For this reason your RISK Management assessments process, based on FMEA, should consider development RISKs. You need to create Key Performance Indicators (KPI), which are based on your organizational context. You will need to define methodology which measures the value created by R&D activities, which will essentially allow you to:
- Capture not only merely economic value, but intangible assets;
- Measure the efficiency and effectiveness of ongoing projects in the R&D portfolio, focusing on the most relevant;
- Assure transparent and traceable estimates, based on actual data;
- Assess regularly the coherence between feature development and defect sensitivity;
- Support the evaluation of different kinds of projects and results: Incremental vs. breakthrough, core business technologies vs. emerging ones;
- Evaluate results, at least once a year, perform post postmortems;
- Support the planning and leadership role of Corporate in the R&D activities.
So as the development team leader or R&D manager, you are responsible for examining your defect history log, and identifying those areas in the product that are the most difficult to fix. Such a survey is beneficial in predicting or mitigating the recurrence of such events.
How Do I Create Historical Measurement On Defects In QPack?
In QPack View Designer, there are many options that enable you to check the current state of work items. However, should you need to create a view that is multidimensional, then it is beneficial to apply the User Defined Criteria, which will allow you to review historical data in Orcanos ALM. So essentially, your initial investigation will uncover defects within your population, while your second inquiry will be on the historical values of said population. There you can place an additional WHERE clause
id in (select obj_id
where tablechanged=’DEFECTS’ and fieldname=’status’
group by obj_id, cast(NewValue as nvarchar(max))
having count(*)>1 and cast(NewValue as nvarchar(max))=‘REOPEN’)
The SQL statement checks changes in the defect history and returns those who were REOPENED more thanonce. You may want to do the same for those that were REOPENED more than twice. Here are the results you can expect
More Advanced Investigation In Orcanos ALM
Now that we have conducted that analysis we are able to do more in-depth research and determine what aspects of our products suffer the most from REOPEN events. Additionally, we can use the double reopen research to refine those areas and find the most critical areas of functions in our project. Should you create a second chart view of that data where you have placed your feature list that those defects are associated with, you may get interesting results.
From the first REOPEN, it is clear which areas, in general, are more difficult to resolve doing it First Time Right. From the second report, you may find which areas require extra effort to solve using those second REOPEN, which highlight the low efficiency areas in problem resolution. If some methodology of Root Cause Analysis is being used in your R&D activity, you will have not just a view of your problem, but a view of your solution and mitigation of such events.