Why Product Data is the Key to Profitability

Education / Why Product Data is the Key to Profitability
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Summary: Product data is dispersed throughout organizations which makes it hard to find and access. Centralizing this information improves efficiency and maximizes profitability.


If your organization is involved in making things, it’s imperative to make the most out of your data.

Particularly when it comes to product data.

Today we’re going to look at:

  • Where product data goes wrong
  • How product data impacts your bottom line
  • Why product data needs to be organized
  • The best way to organize your product data.

So let’s get started.

The problem with product data

Product data is a really valuable resource.

Except when you can’t access it.

And this is, unfortunately, the reality most product teams face.

There’s plenty of product data out there, but very few, if any, people have access to all of it.

Things get even trickier when you consider where this data is located.

Any given data point could be stored in an email thread, slack, channel, shared drive or even exclusively on someone’s hard drive.

For instance, say you make electric can openers, and you’re about to release the Can-O-Matic 10,000.

You have to send your latest CAD design to the manufacturing floor to make sure they can make what you have in mind.

But then you get an email back with an attached PDF that’s marked up by the manufacturing manager.

That email thread is the only place that data point is stored.

And this makes product data time-consuming to find and difficult (or impossible) to access and use. A problem that at least half of product design teams face.

Half of product design teams report that accessing data from another location in their company as a problem.

And it’s not just inefficient. There are real business consequences to disorgnized product data.

The cost of disorganized product data

Disorganized product data is detrimental to profitability.

Here’s why.

1. It slows down product development

Lots of departments other than engineering need to touch product data throughout a product’s lifecycle.

But since this data is hard to find and access, product development gets slowed down.

Instead of teams working on tasks that add value to a product, they spend hours looking for the data needed to do so.

In fact, manufacturers report that 15% of company time is spent on non-value adding tasks like data retrieval.

Long story short, organizations pay for expensive labor — labor that then spends 15% of its time doing very low-value tasks.

As a result, products take longer to release and generate less revenue when they do hit the market.

2. Duplicate work occurs

When teams can’t access product data, it gets hard to know what’s been done and what hasn’t.

It becomes unclear whether a job is incomplete or if it’s just hidden away in a file somewhere.

This is particularly a problem during the design phase, as 42% of teams see their ability to avoid designing a part twice as so-so at best.

The business impact of this: designers spend 80% of their time on design work that’s already been done — which hurts profitability big time.

And with the average industrial designer making around $65,000 a year, that means companies are paying a whopping $52,000 a year per industrial designer for work that’s already been completed.

With design teams having multiple industrial designers, disorganized product data reduces profitability by hundreds of thousands a year.

Disorganized product data reduces profitability by hundreds of thousands a year.

3. Production errors happen

When data is all over the place, it’s hard to make sure that your product design includes all the specs it needs to.

Which results in incorrect designs being sent to production.

And this causes a lot of money to go out the window.

With the minimum for production runs in the 5,000 range, products with design errors face two fates:

1) Rework

When extra resources are dedicated to getting the product up to the right specs.

2) Scrap

In this situation, it’s cheaper to start from scratch than it is to rework the product.

Either way, both solutions negatively impact your bottom line.

In the words of Cleanslate UV Co-founder Oleg Baranov:

It’s cheaper to design right the first time than to engineer the fix in later

And organized product data is how you do that.

4. Deadlines are missed

The effects of disorganized product data ripple across organizations and eventually culminate into missed deadlines.

With each missed deadline resulting in a 12% drop in company shares, disorganized product data impacts profitability in a big way.

On average, missed deadlines cause a 12% drop in share price.

Disorganized product data is expensive.

It causes all sorts of problems and makes it hard to deliver high-quality products to market quickly and effectively.

So what’s to be done?

The path to organized product data

The solution is to make product data accessible.

Product data needs to be available when you need it, from where you need it from.

And the best way to do this is with a software that automates the process.

Automation is key when it comes to organizing data because human error is unavoidable.

When data is manually organized, mistakes happen.

People forget to move every file to your centralized drive or don’t update the file once it’s there.

Staff turnover can also result in files being excluded from the database.

Regardless the reason, manual data organization leads to your repository being incomplete.

To optimize product data and profitability, you need software to pull and push data from across repositories to create a shared version of the truth.

This way product data can be easily accessed by everyone in the product stakeholder network.

Recap

Here’s what you get with organized product data:

  1. Accelerated product development. When teams can find the information they need, processes are smoother and products are launched sooner.
  2. Increased efficiency. When product designs are up to date, teams don’t waste their time doing work that’s already been completed.
  3. Simplified production. Organized product data mitigates the risk of something going wrong during production.
  4. Conquered targets. When processes from development to production are streamlined, managing the product lifecycle is easier than ever.

The trick when it comes to product data — make it accessible wherever and whenever people need it.


Image Credit: George Becker via Pexels

Wondering how cloud PLM can help when it comes to product data? Find out now.

2018-12-12T13:56:26+00:00