This is the second of a three part data series from Roger Serrette, Ricoh Customer Experience Center Director, Commercial Printing Business. Don’t miss the first part of his series: How to Intentionally Use Your Data.

Wait, I know I need to conduct a workflow assessment, and I have data, but unbiased data?

It is no surprise that business leaders use in-house data to support the decision process. By nature, we want to justify action with accurate and predictable analytics, but very few teams start with a non-biased data collection. Instead, they work unconsciously to find data that supports their business decisions.

The problem here is that sampling or response bias leads us to cognitively collecting data in such a way that it leads to a predetermined outcome. So, creating a questioning environment to collect neutral data is critical in alleviating the pitfalls of cognitive bias especially related to workflow.

Why is unbiased data collection critical in a workflow assessment?

Often, the bias that exists is toward protecting the existing system. Be it out of loyalty to the existing workforce on the floor, the platforms or investments made many years ago, or the simple normal resistance to change, managers within operations sometimes see the operation as qualified and successful or see the solutions to problems as more problematic than just dealing with them. That hurdle at the beginning of the process clouds the collection and leads to predetermined results.

The good news is that despite unconscious bias, every production shop has unbiased data everywhere. It hangs out on shared department manager’s spreadsheets, lingers in perpetuity on white boards, ages on sheets taped to presses, and is archived in ticket sheets. It even gets broken down into fractured visuals in email and slides documenting current challenges. You have data, and in those collected forms it paints an unbiased view that can be used to assess your workflow.

Steps Towards an Unbiased Viewpoint

To assemble that unbiased view, begin with a physical mapping diagram that shows your workflow and job parameters required for a job submission. Then using a series of questions, you can begin to collect the data in plain sight to assess your workflow.

  1. What constitutes the volume in the production environment?
  2. What is the myriad of submission or onboarding processes for customer jobs, including the percentages of those submissions that require touch points such as a customer service representative (CSR) calls, change requests, file correction or manipulation, tracking, etc.?
  3. What is captured about every job or file and is that consistent across the onboarding process?
  4. Is there a process in onboarding to capture missing or to correct file/job elements?
  5. What are the breakdowns of those jobs and how are they tied back to each customer by service level agreement (SLA), application, and market segment, and does the system automatically or manually stake out the required resources?
  6. Which jobs consistently have margins, which are noted loss leaders, and which ones were promissory or pipeline leaders that have not materialized?
  7. What jobs require outside partnership assistance to achieve its completion to sort, use specific applications, mail optimization, etc.
  8. In your environment, given each potential path that a job can take from submission to shipping, what languages and processes exist between departments and workflow steps (manual vs automated)?
  9. How are reprints, damages, overage, and rejections all handled?

From this list of questions, you can now create a system chart that captures the complicated journey of every job type through your production or manufacturing process.

Now, assess if that data and flow indicates if there are gaps or hurdles hindering the effectiveness of your workflow. Unbiased collection across the workflow will lead to a more accurate and stable view of the system and be able to lead you into the correct next steps in addressing your uncovered workflow challenges.

Want to learn more? Be sure to reach connect and reach out to Roger.

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Barb Willans

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Barb Willans


Business Management
Data-Driven Decision Making
Print Production

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