The principles, techniques and methodologies of Lean Manufacturing focus on removing waste from production processes and keeping just those elements that add value–always with a continuous-improvement approach. The Lean concepts have been used with great results in a wide range of domains: Lean accounting, Lean IT, Lean HR, etc.
But why should we apply them to data management? Just as the latest trend? So we can feel like hipsters in data management? Unfortunately not.
We must apply Lean techniques to our data management to stay competitive. We have already talked in previous posts about the importance of the master data and how they make up the data foundation of the enterprise. Our ERP data provide the base of our operations, which in turn provide the base for our decisions.
Yet Gartner estimates that more than 25% of the critical data within large companies is somehow inaccurate or incomplete. These errors in the base of the pyramid are spreading up to our operations, adding costs and inefficiencies that affect our decisions, with an impact in millions of dollars.
But this current situation is not the real reason that we should start using Lean techniques in our data management. The real problem is in the future, as that data grows.
- Companies are estimated to duplicate their data volume each 2-3 years, and a lot of all these data-generation processes are inefficient and manual, leading to a high percentage of errors.
- A lot of our employees spend 1 to 3 hours daily filling data screens in SAP, instead of dedicating that time to value-added tasks.
- A lot of companies are still using email-based processes (even paper forms) to compile all the info required in our ERP system. Those processes cannot be measured–and if you cannot measure them, you cannot really improve them.
Let’s call it the “Data Management Tax.” All this time our employees are dedicating to data-related tasks–entry, compilation or verification–is a tax that companies with ERP systems are paying just to run their business, and they are paying it with hours and hours of their employees.
The main problem with this Data Management Tax is that it grows at the same rate as our data, ergo—exponentially! We will need more and more hours from our employees. All this translates into a direct cost, with more time and resources for data-management tasks, as well as all the risks associated to the bad quality of them (delays, errors, etc.).
The only way to avoid this exponential growth is by doing more with the same resources, even more with less than our current resources. This is the objective of the Lean philosophy. By applying Lean techniques with iterative continuous improvement, we will standardize and improve our data-management processes in an agile and rapid way.
We must change our inefficient manual processes with standardised processes that can be continuously improved with short cycles, allowing a real implementation of the Lean philosophy in our company. Where we had cost increases and risks with delays or errors, now we will have continuously improved standardised processes with speed and accuracy in our data.
All these mean an increase of your company’s competitiveness, thanks to the implementation of Lean Data Management.
Questions or comments about this article?
Tweet @IsraelRosJ to continue the conversation!