How to prevent a computerized product data mess?

How to prevent a computerized product data mess?

Data is taking a central stage in everything that businesses do these days. You can hear about digital strategies and digital transformation every day today. So, let’s bring computers and solve the problem of data mess. Not so fast. For most companies, bringing computers actually ends up with not solving a problem, but creating a computerized mess. How to prevent it and what indicators will tell you that you’re moving from data mess to computerized data mess? I’m continuously hearing top managers, engineers, procurement, and other departments of manufacturing companies speaking with growing concerns about the data and their ability to perform their work. According to many people, I’m talking continuously, here are 5 concerns they have about the data.

5 Indicators of Product Data Mess1– One Crucial Spreadsheet. There is one important spreadsheet that collects a very important set of information that is critical for many people and represents centralized storage of data about products. This data is managed by multiple people and departments. The data can be outdated quickly if it is not updated. At the same time, updating this data manually requires too much time and effort. You hope this Excel will be secured with the top priority.

2- Data Traceability Mess. Each project is represented by an Excel file that includes components, assemblies, and corresponding data such as quantity, suppliers, cost, and other information. The person who created it is your data mastermind (or Chief Excel Officer), but there is no easy way to trace data relationships back to the original – design data, additional materials, type of information cost, suppliers. You hope the questions about traceability won’t be asked every, because they are hard to answer.

3- Parts, components, materials are listed multiple times differently in multiple Excels. The data identification is a mess. You might have multiple projects Excels with the same components named differently. The data was entered by different people at different times. Each Excel by itself is important because it represents a critical piece of product data, suppliers data, cost, and other information. However, the task of consolidating these multiple Excels together is overwhelming, so you continue to go into this vicious cycle again and again.

4- There are no measurable KPIs to quantify product design, cost, suppliers, procurement. It is easy for companies to quantify sales numbers. Most companies’ sales numbers are known. However, to connect this information to product, design, suppliers, cost of materials and other information is not. What was the actual cost of the equipment produced and sold? Such a question can put in a freeze mode an average operational manager in a medium-size manufacturing company with next to impossible probability to get these numbers and connect the cost of actual inventory used to build a product to sales cost.

5- IT reports are always late and irrelevant when delivered. Company effort to collect information from multiple places is hugely underestimated. It is very common to take multiple weeks to produce an actual project cost report, monthly analytics takes 30 days to produce and the impact of lead time change on supplied materials takes longer than lead time itself.

Where is THE button?

When companies are coming to me with such a level of problems, I ask them about what is the plan to make a change? Unfortunately, for many companies, this is quickly becoming the hardest moment. They don’t know. Companies live in such a mess, but they use TLAs way of silo thinking about finding a solution. Unfortunately, many of the companies are thinking about how to import all Excel data in some magical system that will solve all problems and also looking for a button that is supposed to be called – “Make all work”.  Unfortunately, both methods are not very helpful.

Data Strategy and How to Make a Change?

The change is hard and when it comes to the data mess, it is even harder. There is no other way than to make your hands “dirty” with the data and start cleaning your data records and eliminate the mess. But, things should not look too gloomy if you apply a structured process that can help you separate tasks and make changes by stages. Here are 3 important steps to make:

1- Think about data identification first. For many companies, it starts from Part Numbers. Once you know how you identify what you use, life will be much easier for you, because ABC-123, will mean only one thing.

2- Focus on a centralized catalog (Item database) of every material, component, assemblies, part you use and how you collect information about each item and establish the process of new item creations and re-use. New Part Numbers are expensive, especially when they apply to already existing items.

3- Prioritize data sharing and re-use. To have updated information trumps everything else. Knowing that you work “on the same BOM” can solve thousands of problems you will have otherwise.

What is my conclusion?

Don’t bring computers in your messy data? You will end up in a bigger mess. Spreadsheets are quick to create but terrible to share, update and manage. Bringing all your data into a spreadsheet can give you a false sense of ownership, structure, and protection, but will not solve the fundamental problem – data identification. reuse and sharing. Focus on these three priorities and build a roadmap to get out of the data mess. Just my thoughts…

Best, Oleg

Beyond PLM

Disclaimer: I am the author at PLM ECOSYSTEM, focusing on developing digital-thread platforms with capabilities across CAD, CAM, CAE, PLM, ERP, and IT systems to manage the product data lifecycle and connect various industry networks. My opinions may be biased. Articles and thoughts on PLMES represent solely the author's views and not necessarily those of the company. Reviews and mentions do not imply endorsement or recommendations for purchase.

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