Author: Paul Henriques in: Management
When you are investing in your firm or planning your next big move, choosing how to best spend your time and money can be stressful. To decrease that stress, the best option is to do your research and increase your knowledge. Find the best product based on mountains of data, condensed down to what is most important to you.
But how can you trust that the data you based your decision on is correct?
Recent studies by Gartner found that poor data quality has companies losing up to $10 million a year, with IBM calculating that in the US alone, the lost revenue due to data errors total over $3.1 trillion. These costs come in many forms:
You may still be wondering how these figures could be possible. This is because an error in one record can impact your entire production chain. As a matter of fact, research from the Harvard Business Review states that only 3% of company data meet basic quality standards.
Data scientists have a name for this ongoing production of errors: the hidden data factory. The hidden data factory can lead to an eroding sense of trust in your data.
For more information on Lean and Downtime, see our white paper on Cutting Waste with LEAN Thinking.
While it isn’t easy to decrease the root cause of the waste, applying a lean methodology to data entry and processing will improve your data quality.
Bad data comes from communication errors, which can be summed up as:
Once you discern where the problem areas are you now have to map what is being affected by those errors and how to resolve them.
Receipt and input errors can be resolved by adding confirmation to the data, or you can bypass the possibility of human errors by looking to implement direct electronic communication, or EDI, between you and your customers, vendors, and banks.
The third problem area often requires 3rd party plug-ins, or other services to ensure the applications can communicate with one another.
A better solution to all three areas is to implement a single point data system, like OnRamp, where all the data is contained within one program and one database that quickly and efficiently allows communication between all your business units and supports EDI.
With the process mapped and implemented, you now have to ensure your staff are using the new flow.
This will generate less waste, just by having better data available.
With errors decreasing, you will see your costs go down, meaning you can pass some of those savings onto your customers. Implementing a single point system allows your customers to create requests that are automatically viewed by your planning team, thus shortening the amount of time you require to get your goods to the customer.
With one problem solved and your flow and pull running well, you can run the process again on the same data set or a new one to keep improving your processes and removing waste.
The above process has been found to help you close hidden data factories, leading to more productivity, and most importantly, more informed decisions.
As you know, there are multiple data points for you and your team to work through. For example: Customers, Vendors, Employees, Parts, Work Centers, and Maintenance.
For most firms, it is impossible to clean all this up in one go. Instead, focus on your small data initiatives by trying to implement the following practices:
The next steps are:
Bad data creates non-value-add expenses in the form of hidden data factories that decrease your competitiveness and decision making. While there is money and business lost because of bad data in every modern industry, that can be mitigated with better systems, more automation, and smarter people management. A single point, single database ERP system, such as OnRamp, helps you better manage your data, decrease data waste, and helps you better manage your workers in all departments.
Staying ahead of your bad data ensures your firm is nimble and ready to capture more market share and make you a leader in your field.