5 Ways Manually Recording Data Can Harm Your Production Environment
Many corporations hold back on automating data processing due to costs, perceived complexity, and lack of cultural readiness for a more data centric approach to work. This in turn results in continued cost burden and inefficiencies of manually entering production data on paper and in spreadsheet software programs such as MS Excel. Assembly status, inventory levels, test and quality results continue to be prone to errors due to missentered, lost or missing data.
Lack of visibility into actual operations is a direct result, and entrenches silos of tribal knowledge, leading to increased operating costs and market risks.
On the contrary, automating operations data capture and storage, to deliver real-time actionable information, is very cost effective and highly profitable today.
Companies that undertake this transformation are capturing market share at rates faster than ever, due to their ability to quickly identify operational inefficiencies, in order to reduce labor and material costs, improve quality, and deliver faster to market.
The power of this competitive advantage, against anachronistic incumbents, cannot be overstated.
Here are 5 ways manually recording factory data is harming your operations.
Loss of Valuable Operator and Engineering Time
When utilizing a manual system for data entry, the cost of labor needs to be factored in. To have an effective manual data entry system, engineering staff needs to be properly trained, understand the importance of accuracy when entering production information, and follow consistent formatting rules for each field (example: dates, quantity, operator names/signatures, measured data such as voltage, amps, Cu plating thickness, etc.)
Unlike an automated system that only needs to learn your processes once, a manual system requires constant training to ensure all current and onboarding staff are following the same procedure. And this adds further costs to the already costly loss of productivity due to manual entry requirements.
Increased Security Risks
Let’s say onboarding data entry personnel is not within your organizational roadmap or budget. An option would be outsourcing this work or training engineers to now also manually track data, on top of their existing responsibilities. Both have drawbacks.
Outsourcing can take a significant amount of time finding the right provider, agreeing on terms, and onboarding. But there are major security risks that come along with outsourcing a data entry service. If your data contains any sensitive information, using a third-party service provider could prompt data leaks, and limits your actual control over how the data is processed/managed.
Training current staff how to manually record data may be a short-term solution to keeping your data secure, however, operators and engineers will forget protocol for entries, record illegible information, etc., unless reinforced regularly through training updates. As mentioned above, this also dramatically reduces time from actual production. Even with the use of engineering notes through each process, these can be incomplete or simply inaccurate.
And the fact of the matter is that operators and engineers generally don’t read ‘pass down’ notes and comments. So critical information transfer will fail you at the most inopportune time.
Time is Valuable
Manual data entry takes too much time in comparison to automated systems. Going from multiple keystrokes to just one click will save 1,000s of operating hours that can be allocated towards getting products to market faster. Including the time it takes to track, record and correct inevitable mistakes made while performing manual data entry. Take a moment to ask yourself how much time specific roles are taking to fulfill manual entry and tracking requirements, per day. Now add the hourly labor cost to this, and factor in hours further taken to recover from issues due to lack of traceability. This marginal cost will be alarming.
Ample Room for Error
One of the biggest downfalls of a manual data entry system is the higher error rate. We are all human and even the most careful employees make mistakes and with a manual system, increased speed usually relays to decreased accuracy.
As should be abundantly clear from previously discussed points, it’s impossible to achieve 99.99% accuracy with a manual system. Any errors will cause inconsistencies that can impact the accuracy of your reporting, and the searchability of your data, undermining your ability to make good decisions quickly. To counteract this, corporations may choose to invest in a review or quality check process to ensure accuracy and benchmark error rates. This takes even more time and increases corporate costs and resourcing complexity.
Automating your data collection processes in order to digitize operations will save you time, money and give you full visibility into your current processes, thus helping you stay ahead of the competition while making data-driven decisions .
The costs and complexity to automate data collection and reporting are extremely low today, and result in immediate benefits across your operations.
The only true barrier is a cultural readiness to be more for a more data centric. Once this is overcome, your digital transformation initiatives will start delivering immediate, measurable results:
- Reduced labor and material costs
- Improved quality
- Faster time-to- market
The power of this competitive advantage cannot be overstated.
If you are currently seeking solutions to help accurately track and manage your manufacturing operations data, contact us. We can help guide you to find the best solution for your current and future operational needs.