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Your digital transformation report
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Digitalizing your data
These processes make your data theoretically available, but not really an asset. For example, if you have a scanned drawing, that’s a digital file, sure. But it just sits in some folder somewhere as an image file. You have to remember what it was labeled as, where it was saved, and when you should go to look at it. In tight timelines, or when newer employees come on board, or many other situations, you might as well not have the image at all.
True digital transformation makes it easy and intuitive to make use of this data. With our scanned drawing example, making it into a true digitalized asset involves using optical character recognition to make the text on the drawing searchable, using machine vision to analyze the drawing to recognize components, and properly indexing it with this contextual information.
Jumping from static data scattered across many systems (or filing cabinets) to maximally useful digital assets won’t happen overnight. Here’s a process to help you get there:
A data lake is a central repository for all types of data from lots of different systems. It allows you to sort, filter, and search through all your data at once, highlighting trends and other insights. Rather than a static spreadsheet where you have to know exactly what you’re looking for, data lakes allow for more intuitive searching.
Another relevant advantage of a digital transformation is making revisions and collaborations easier and more consistent. The average automotive drawing goes through at least five revisions, with some industries requiring dozens more. Without a good process and technology to support it, it’s very difficult to track these changes.
Inevitably, there will be some information that gets missed in this process. Keep track of whenever you have to:
- Make a search that required some memorized knowledge
- Search in places outside of your data lake
- Contact someone to find out where something was stored
- Take a long time to find the data you needed, for any reason
- Teach a new person where to find something
As you’ve indicated that you still have substantial data contained on paper records, you should prioritize getting these scanned and digitalized as soon as possible. It will likely be a time-consuming process, but it will pay for itself quickly in time savings.
As you’ve indicated that your data mostly lives in spreadsheets, you’re on your way to true digitalization. However, spreadsheets are insufficient – people generally have to “know what they’re looking for” to find things in them, requiring memorizing specific labels, ID numbers, or other fields. More intuitive search capabilities will make your data a better asset.
Your searches are currently taking too long. When you think about the number of
Building collaborative infrastructure
The first necessary step is ensuring every potential collaborator has the infrastructure to contribute. This means they need to access the relevant discussion, leave their thoughts and changes, and have those changes tracked so that subsequent collaborators can continue moving forward.
As you’ve indicated that you still have some comments made on physical drawings, you’ve already got a good system for ensuring all subsequent collaborators see changes. However, working on physical paper is very insufficient in terms of accessibility. Uploading your data to a cloud-accessible database will speed up collaboration.
Once you have universal access to data among collaborators who need it, you can enhance it with analysis and comparison tools. For example, highlighting the differences between two drawings or documents, rather than having to compare them manually. This makes it easier to understand what changes are being made and why.
The final aspect of good collaboration that a digital transformation should enable is access to contextual data. Each collaborator may have different information that they need to see in order to make their decisions. It’s important to make that information easy and quick to find. Otherwise, decisions are slowed or made sub-optimally.
Imagine a group of people collaborating to revise a design. One person may want to know the cost of different component parts, requiring past order data. Another person might want to know the quality data of previous similar designs in production. Yet another might want to know what materials had been used for similar designs in the past. And yet another may want to know an estimate of the total cost of the design.
Each person finding the data they need could take an exorbitant amount of time if not optimized with a digital transformation. Ideally, you should be able to surface all of this information simultaneously using only the drawing. This saves time and energy, allowing for more informed, strategic, and efficient decision-making.
Building an insightful data lake
Another major benefit of a digital transformation is unlocking new strategic insights. Beyond just finding answers to questions you have during collaboration, you can find opportunities that you hadn’t even considered looking for.
These opportunities can be extremely valuable and impactful. Here are some of the decisions you could be empowered to make:
- Consolidating suppliers to negotiate better rates
- Diversifying suppliers to remove supply chain fragility
- Finding redundant parts and products in your database
- Uncovering commonalities in defective parts, enabling higher-quality designs
- Discovering trends between design features and time spent in production
The data you need to notice these opportunities would typically require many manual searches and cross-references. For example, to find times to consolidate suppliers, you’d have to look up procurement data for each previous order, sort them by supplier, then categorize them by different part qualities until you notice patterns.
For example, after many searches and comparisons, you may be able to determine that Supplier A consistently has the lowest prices with acceptable defect rates for aluminum pipe fittings, and thereby negotiate that they’ll handle all of your aluminum pipe fittings going forward at a lower bulk rate.
However, with a modern digital transformation solution, all of this data can be surfaced and sorted automatically from your data lake. Instead of manually parsing each order to determine what aspects are relevant, this modern system can automatically highlight useful commonalities.
With our previous example, instead of having to examine each order to see if it fits into the aluminum pipe fitting categories, this system could automatically make that categorization and provide supplier, quality, price, and material information alongside it.
Spearheading your digital transformation with CADDi
This investment can be enhanced by adopting a digital system to automate and simplify your digital transformation. CADDi’s features include searching by drawing, design revision infrastructure, and surfacing relevant data. Each of these makes your decision-making process faster and more strategic.
Sign up for a demo to see it all in action.
