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Keeping “Data Decay” at Bay: How to Improve Your Staffing Firm’s Data Quality

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Data is the lifeblood of any organization.

Managing that data properly helps get the correct information to the right place or person, at the right time, and in the proper format. Ongoing data management ensures healthy staffing operations to identify opportunities and risks, provide a high quality of service, and make intelligent marketing and sales decisions.

Today we will look at the “right information” piece of the data management equation, and more specifically, the data quality.

When we use the word “quality” here, we’re referring to data that is:

  1. Fresh (up to date)
  2. Relevant (applicable to the intended purpose)
  3. Accurate (reflects reality)
  4. Complete (can provide insights for decision-making)
  5. Reliable (went through quality checks)
  6. Traceable (has an audit trail)

Over time, every organization grows its data set. But if not properly maintained, that data decays. Employees come and go. Documents are moved and changed. Metrics that were once relevant are no longer critical.

Without proper intervention, poor data quality can lead to poor decision-making, missed opportunities, taking on unseen risk, and lost revenues.

How can you keep “data decay” at bay?

Here are the first steps you should take if you question – or want to improve – your staffing agency’s data quality.

Audit your data

Start by assessing the current health, or quality, of your data. Then, review it for freshness, relevancy, accuracy, completeness, reliability, and traceability.

Your company data must serve a business purpose. This means you must understand what data each team and team member needs to perform their duties and responsibilities optimally. Some questions to ask are:

  • Can they access and retrieve what they need?
  • Is the data they have access to enough to provide insights?
  • Does the team have sufficient data skills to understand and use the data?
  • Are data management roles and responsibilities clearly understood? Everyone has them.
  • What workarounds are currently in place masking gaps and deficiencies in current tools, structures, processes, and policies

Clean your data

    Once you have a good picture of your situation, it is time to prune. This includes steps to:

    • Update or remove incomplete or erroneous records
    • Remove duplicates
    • Remove irrelevant data
    • Remove or archive old or decayed data
    • Note missing data necessary to produce insights

    Prevent Data Decay (in real-time)

    Over time your data gets old, loses relevancy, picks up errors, and loses trustworthiness. A few ways to combat this entropy are to:

    Centralize your data (reasonably)

    When data is scattered across the organization, it is challenging to organize, update, dedupe, track errors, provide access to and secure.

    What is the “reasonably” for?

    It is almost impossible to find a tool that can manage all data across an entire organization well. Many teams in the organization require specific processes or standards and have their jargon and KPIs. A central data management approach can, in some cases, harm productivity if it requires conformity to a standard expectation. Instead, consolidate your tech stack where it makes sense and integrates where it does not.

    Standardize processes and formats

    Control where data comes into your company, as well as what is captured. It would help if you only ingested what your teams need and have a good reason for anything above and beyond this.

    To this end, you can predefine what data is required, validate the data at the input or ingestion point, set rules to flag or prevent bad or incomplete data, and restrict unique data entries. The latter will go a long way in reducing duplicate entries.

    Critical to this is…

    Integrate your tech stack

    The less manual data manipulation, the better. Integrating your (hopefully) consolidated tech stack will minimize these occurrences, time is taken to retrieve complete data, and increase overall data reliability. Integration should be set up between a database and each of its data entry points (website application form and Applicant Tracking System), databases or teams (sales and marketing), internal and external systems (Applicant Tracking System and social media).

    Utilize automation

    This goes hand-in-hand with integrating your tech stack and critical to keep data fresh, compliant with company processes and standards, and elevating issues or wins. Have data quality/validation checks at your data input/ingestions, integration, storage, and retrieval points. This will minimize bad, old, and incomplete data from creeping in. Set up notifications for signs of data decay but also to celebrate team and company wins.

    Update your tech

    Technology advances quickly, and malicious actors do so as well. This has accelerated with more happening in the cloud and fewer physical devices. Secure and actively protect against malware by regularly updating your systems.

    Enrich your data

    Do not rely solely on directly generated data. For instance, integrate data from official databases to flesh out contact records or standardize addresses.

    Stay compliant

    Keep ahead of relevant regulations and ensure your data capture, storage, and usage is compliant. A consolidated and integrated tech stack will allow your company and teams to pivot quickly with new rules.

    Your staffing firm deserves data that is trustworthy. Better data quality means better insights for prompt and accurate decision-making.


    How can Haley Marketing help?

    High-quality data is critical to successful marketing; best guesses and hunches don’t work. That’s why we’ve developed robust tools that deliver timely, relevant data to understand – and improve – the ROI of your marketing investment with us. Whether you’re looking to drive sales or enhance recruiting, our experts can help. Let’s talk!

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