Outside of Scope: Agency staff and partners are already reporting required data and have a variety of different reports from multiple data systems to track existing compliance metrics. Newly proposed job quality metrics go beyond the scope of current funder requirements.
Emphasize that the agency has established a new strategy centered around job quality. Informed decision-making--not data--is the goal; informed decision-making is. Measuring job quality can help drive better decision-making and focus throughout the initiative.
Also, take the opportunity to reduce or remove data collection that isn’t required and doesn’t serve your new strategy. This demonstrates an understanding of the human limitations (in terms of the burden to both those served and the case manager) on how much can be collected.
Impatience for Results:
Internal and external stakeholders are impatient or lose interest in the job quality initiative because progress on key performance indicators is not immediate.
Express shared frustration with the pace of progress, while noting that making measurable impacts in a life, program or community takes time. While “big” outcomes—such as worker advancement or worker satisfaction—are ultimately what a job quality initiative is trying to achieve, it is important to demonstrate progress in the short-term indicators that contribute to larger outcomes.
Data Quality Issues:
An initial assessment reveals that the agency has incomplete and/or inaccessible datasets that may have errors, calling the quality of all data into question.
Data don't need to be perfect to get started. While investment is often needed to establish a robust set of data for monitoring progress, even some data are better than none when it comes to decision-making.
Being a data-driven organization means thinking practically, using what’s available and deciding what is “good enough” to inform decisions. That said, as gaps or problems are identified in data, we will create a plan to address them. This may include re-training staff, clarifying written guidance, addressing system issues or even removing unnecessary data collection requirements.
Too Expensive:
Budget limitations make investing in additional data infrastructure and resources challenging.
Using data to monitor performance and make adjustments reduces time and resources wasted on efforts that aren’t producing results. Investing in the talent and expertise needed to implement this measurement system is a strategic priority, as well as an allowable and reasonable expense, and will advance our ability to attract additional funds (both public and philanthropic) by better demonstrating impact.