Big data is the buzz term of the moment – including big data and spare parts inventory management.
For the un-initiated ‘big data’ refers to the collection of huge amounts of data, held in large and complex databases.
The buzz around big data is that it is said to enable companies to gain new and important insights into the subject of the data and from that take better and more targeted actions.
While big data is used extensively in science, research, and government, the real buzz is around the use in the private sector – think Amazon, Wal-Mart, and Facebook.
It is the combination of increases in computing power and low cost access to that power via ‘the cloud’ that has enabled big data for most private sector organizations.
So what does this mean in the world of big data and spare parts inventory management?
In a word, optimization.
Data driven optimization has been around for a long time and many companies can provide software to help with this.
The promise of big data however goes beyond optimization at your site, it encompasses the entire spare parts inventory management supply chain – that is, planning, procurement, supply, usage, and disposal.
Sounds great but there are three major problems with the application of big data in this area.
- A mis-match between IT capability and operational capability. If your IT capability exceeds your operational capability then it doesn’t matter what data you have, you are unlikely to be able to implement successfully. You should always work on improving your operational capability before collecting more data.
- Data analysis requires assumptions about the nature of interactions. Harvard Business Review coined a term I like – big data needs ‘big judgment’. Modeling the behaviors that drive interactions is likely to empirically based – not everything has a clear and consistent cause and effect – so big data may not be driven by the data at all but by the underlying assumptions of your analysis.
- Data quality. Few companies have spare parts inventory data of sufficient quality to make use of the existing tools, let alone the analysis of big data. Data quality is a major problem in the area of spare parts inventory management. These quality issues are created by human behaviors such as not recording transactions, removing more than required, delays in returns to the storeroom and, perhaps the worst of all, squirrel stores.
Don’t get me wrong, big data can be very powerful.
However, it is not a solution for all problems.
In the world of spare parts inventory management most companies would be better served with focusing on improving their operational capability, rather than more analysis of their spare parts inventory interactions and transactions.
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Author: Phillip Slater