Tech-Clarity Perspective:
Best Practices forManaging Design Data

How Effective DataManagement Fundamentals
Enable World-Class ProductDevelopment© Tech-Clarity, Inc. 2012

Table of Contents
Executive Overview ....................................................................... 3	
  Importance of Effective Data Management ................................... 4	  Data Management Challenges Impact Time and Quality .............. 5	
  Complexity, more than Size, Creates Issues ................................. 6	
  Wasting Time on Nonproductive Data Management ..................... 7	
  Identifying the Top Business Performers ....................................... 9	
  Best Data Management Practices of World Class Companies .... 10	
  Enabling World Class Data Management (and results) ............... 11	
  Conclusion ................................................................................... 13	  Recommendations ....................................................................... 14	
  About the Author .......................................................................... 15	
  About the Research ..................................................................... 15	
  2© Tech-Clarity, Inc. 2012

Executive Overview
Effectively managing design data is critical to remain agile in today’s complex productdevelopment environment. Tech-Clarity research shows that effective data management
helps companies design innovative, high-quality products quickly and efficiently. This
report analyzes how best practices relate to business performance based on over 2,000
responses to a web-based data management survey.

Companies with world-class performance are more likely to havevery effective data management capabilities.
The survey allowed participants to report their company performance related to quality,
innovation, product development speed, and efficiency. Respondents of all company
sizes from various manufacturing industries across the globe shared their experiences.
Survey analysis correlated companies with the highest aggregate performance in theirimportant product development metrics with their data management approaches. The datashows that companies with world-class performance are more likely to have very
effective data management capabilities. World-class manufacturers:••

Are more able to find the data they need, share it with others, manage their design
projects, and provide the correct data to manufacturing
Spend 25% less time on nonproductive data management tasks

The results indicate that effective data management is an important enabler for designingand developing profitable products. Better data management also helps companies
streamline data management efforts. This is critical given that one-quarter of thecompanies surveyed indicate their technical personnel spend the equivalent of one day
per week (20%) on non-value-added data management activities.

World-class manufacturers are more likely to use structured,
collaborative design data management technology.
Leading companies take a different approach. Survey analysis indicates that world-classmanufacturers are more likely to use structured, collaborative design data management
technology. World-class companies are 30% more likely to use PDM or PLM solutions
and are more likely to use other collaborative data management tools like Microsoft
SharePoint to manage their design data. Managing design data and enabling collaboration– the basic fundamentals behind any PDM or PLM solution – provide important businessvalue. As one participant from the industrial hygiene industry says, “Quite simply when
you have good data management it protects the bottom line and project time.” This report
helps manufacturers learn from the approaches of top-performing companies to help themstreamline design data management and improve business performance.
3© Tech-Clarity, Inc. 2012

Importance of Effective Data Management
The importance of effective data management is probably no surprise to those that face
the daily challenges of today’s complex product development environment. TechClarity’s The Five Dimensions of Product Complexity describes five areas where productdevelopment has grown more complex in recent years, including mechanical complexity,
mechatronics, global markets, global design and manufacturing, and lifecycle
profitability. The report concludes that “manufacturers must address these challenges orsuffer from poor quality products, delayed time to market, and high lifecycle costs.”“To be caught in the quagmire of lost or irretrievable information, design
documentation, or company historical data can paralyze a company.”
Hydro-Electric Equipment Company
Data management is critical to product development success. As one hydro-electric
equipment company explains “Without a clear and precise method of managing design
data and other documentation, a company can become stagnated by not being able tofind, control, or retrieve important data. To be caught in the quagmire of lost or
irretrievable information, design documentation, or company historical data canparalyze a company.”
With this in mind, how can better data management improve business? Survey
respondents were asked to identify up to three areas of improvement that would have asignificant impact on their business (Figure 1). The top improvement opportunities
identified relate to the basic fundamentals of design data management, including control
and retrieval of information. These are consistent with findings in Tech-Clarity’s The
Business Value of Product Data Management which indicate the reasons manufacturers
turn to PDM solutions, including:•••Controlling and securing product-related data
Improving the ability to quickly find and reuse information
Sharing product knowledge with other departments“The advantages of streamlined design data management are clear:
less time is wasted and fewer misunderstandings occur.”Specialty Packaging Company
Survey respondents indicate a wide variety of opportunities for improvement. In addition
to better data management, respondents indicate they would benefit from extending data
management to automate product-related processes, specifically design release andengineering change. They also indicate that better ability to share data, including

4© Tech-Clarity, Inc. 2012

visualization, would have a positive impact on their business. From the results, it is clearthat companies see the benefits available from improving data management
fundamentals. As a specialty packaging manufacturer explains, “When multiple people
are working on the same project, the advantages of streamlined design data management
are clear: less time is wasted and fewer misunderstandings occur.”

Figure 1: Areas for Improvement with Biggest Impact on Business Performance

Data Management Challenges Impact Time and Quality
Why do companies see so much value from improving data management? The reason lies
behind the data management challenges they face. Respondents indicate a number ofproblems, with most companies reporting a combination of these issues (Figure 2). These
are real challenges with significant business impacts including inefficiency and issues
that can lead to mistakes. “Getting the right information to the right person in the rightformat is critical,” offered an industrial equipment participant. “Without this you will
struggle getting parts made correctly and getting them on time.”“Lost data has caused days of time spent re-creating the data.”
Automotive Company.
The most prominent theme companies expressed is wasting time. Forty percent (40%) of
respondents indicate searching for data is a problem. But that is not the only negative
impact on design time, two out of the top three issues reported relate to everyday tasks
that are too time consuming. One could argue the other issues related to tracking
engineering changes and release processes also contribute to wasted time and delayed
time to market. “It is difficult to find the data you are looking for in a timely fashion,” one
representative expressed, “There are multiple servers, locations and sites to look for thedata and there are multiple log-ins needed.” Another issue is lost or misplaced data,
which makes reuse impossible and further wastes precious design time. “Lost data has
5© Tech-Clarity, Inc. 2012

caused days of time spent re-creating the data,” recalls one automotive company. “Lostor difficult to find information affects production and profitability,” explains a consumer
products company.

Figure 2: Severity of Design Data Management Challenges

Another common theme relates to preventing costly errors. Managing engineering change
and release to manufacturing are critical to ensuring that what is designed actually gets
produced. “Data management is crucial for all areas of a business, and vital forengineers and designers who rely very heavily on the engineering data to solve
problems,” explains an industrial equipment manufacturer, “Lack of or incorrect data
could be catastrophic in the worst case scenario and in the best case it still takes awayfrom productivity and causes delays.” Poor data can result in significant quality and cost
impacts. One company described the potential business impact, saying “A huge amounts
of profit can be lost in releasing out of date design models which cause late toolingchanges and loss of time. This is a big competitive issue.” Another company reports thatobsolete data has been sent out to suppliers to be manufactured, resulting in “a huge
waste of time and money.”“Lack of or incorrect data could be catastrophic in the worst case scenario andin the best case it still takes away from productivity and causes delays.”
Industrial Equipment Manufacturer

Complexity, more than Size, Creates Issues
The negative impacts of poor data management are significant. Management in somesmaller companies might believe they are immune to these issues, assuming that data
management challenges are correlated to company size. The data, however, doesn’t
support this belief. The survey shows similar frequencies of challenges from companies
6© Tech-Clarity, Inc. 2012

of all sizes. Even some of the smallest companies face significant challenges. Whilelarger companies do have marginally larger challenges, smaller organizations reportsimilar difficulties. Prior research confirms that smaller companies have many of thesame challenges as larger organizations, but they have fewer resources to solve theproblems.

Product complexity is a larger driver of data management issues
than company size.

Figure 3: Data Management Challenges by BOM Size (Representing Product Complexity)

So what drives data management challenges? The short answer is product complexity.
BOM (bill of material) size was used in the study as a way to gauge complexity of
respondents’ products. Survey analysis (Figure 3) shows a clear correlation between
reported challenges and a greater number of items in BOMs. This leads to the conclusionthat product complexity is a larger driver of data management issues than company size.

Wasting Time on Nonproductive Data Management
Poor data management results in inefficiency and wasted time. Part of the lost time is due
to rework, reduced ability to reuse existing designs, and generally reinventing the wheel.
But part of the inefficiency is related to wasting unnecessary time on data management
7© Tech-Clarity, Inc. 2012

tasks themselves. Inefficient data management puts a burden on the precious innovation
resources of a company. This leads to a perception that design data management is goodfor the business but is a burden on individual engineers, or as something that it is done todesigners and engineers and not for them. This should not be the case, as effective data
management can reduce non-value added time searching for designs in addition to
helping enable the rest of the organization.

“Inefficient data management puts a burden
on the precious innovation resources of a company.”
Unfortunately, the survey respondents indicate that, on average, 15% of their technicalstaff’s time is wasted on non-product data management tasks (Figure 4). About onequarter of companies (26%) report wasting more than 20% of their technical time on
nonproductive data management tasks. That is more than one full day of work per week!
Later we will see that this doesn’t have to be the case.

Figure 4: Percent of Time Spent on Non-Productive Data Management Tasks

About one-quarter of companies (26%) report wasting more than 20%of their technical time on nonproductive data management tasks.
That is more than one full day of work per week!
8© Tech-Clarity, Inc. 2012

There is clear opportunity to increase efficiency and give time back to designers toincrease innovation and throughput. According to one correspondent effective data
management allows him to “spend more time creating and refining products instead of
wasting time managing data.” People across the business have to be able to access data
efficiently to do their jobs, and if it is too difficult they are more likely to guess and cause
quality issues, or reinvent the wheel and reduce efficiency even further. But enablingothers to leverage design work should not hamper the productivity of individual
designers. Ideally, companies should achieve benefits on both sides such as this industrial
equipment manufacturer serving the food industry, “Data management is important to us
because it affects our business economically and makes it easier on the end users to
perform their jobs well.” Clearly a win-win.

Identifying the Top Business Performers
Which companies are doing better at designing their products? And more importantly,
what are they doing differently so others can learn from them to improve their own
performance? To find out, we analyzed four design and product development metrics toidentify world-class performers. The survey requested that each participant evaluate theircompany’s performance (Figure 5), on their ability to:••••

Design high quality products
Develop new products quickly
Develop innovative products
Develop products efficiently

Figure 5: Self-Assessment of Product Development Performance

These metrics were chosen because they have a significant impact on product success andprofitability. The evaluations were aggregated across the multiple metrics andrespondents were classified into one of five performance bands. The top 20% of theaggregated scores were defined to be “world-class performers.” Although these self
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© Tech-Clarity, Inc. 2012evaluations may be inflated, as the fact that the vast majority report themselves as either
average or above average, selecting the top 20% across multiple design and development
disciplines is very useful for our purposes. The organization, processes, and software
enablers in place at the manufacturers in this world-class performance band wereanalyzed to determine which approaches were more common to these leaders in order tomake recommendations to others.

Best Data Management Practices of World Class Companies
When the performance bands were evaluated, the analysis uncovered a high correlation
between effective data management and world-class product development performance.
On first blush this may seem trivial, but it is in fact a very profound finding. It provides astrong indication that effective design data management supports higher levels of
business performance. “Without proper data management we will be always behind thecompetition,” explained one participant. How was this determined? The survey asked
participants to evaluate their ability to:
•
•
•
•
•

Find the data they need
Share data with others
Complete tasks efficiently
Manage design projects
Provide the correct data to manufacturing

The analysis uncovered a high correlation between effective data management
and world-class product development performance.
Survey results indicate that world-class companies are much more likely to be highly
effective across all of the operational data management capabilities reviewed.
Specifically, world-class companies are:
•
•
•
•
•

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2.7 times as likely to be "very effective" at finding the data they need (50%compared to 19%).
2.7 times as likely to be "very effective" at sharing data with others (49%compared to 18%)
Over 3 times as likely to be "very effective" at completing data management tasks
efficiently (51% compared to 16%)
Over 3 times as likely to be "very effective" at managing their design projects(49% compared to 14%)Over 2.5 times as likely to be "very effective" at providing the correct data to
manufacturing (60% compared to 22%)

© Tech-Clarity, Inc. 2012

The results clearly show that companies performing at world-class product developmentlevels have developed much better design data management capabilities. “Design data
management leads to better productivity, product quality, service, and change
management,” an aerospace company participant explains, “It also leads to significant
reduction in cycle times and overall production and support costs.” Perhaps counterintuitively, these world-class companies are not spending more time on data management
to achieve their higher levels of performance. In fact, the poorer performing companies
spend, on average, 34% more time on nonproductive data management tasks than worldclass companies. This indicates that the leaders’ investment in better data management
not only improves performance but also pays dividends in terms of efficiency.

Poorer performing companies spend, on average, 34% more time
on nonproductive data management tasks than world-class companies.

Enabling World Class Data Management (and results)
One reason that companies suffer from poor data management performance is thesystems they use. “The wasted data management time and lack of communication of ourcurrent system is the greatest challenge we face,” explains one industrial equipment
respondent. Although network or shared drives are the most common systems used to
manage design data, they appear to lead to little differentiation in company performance.
In fact, world-class companies report less reliance on unstructured tools for design data
management such as using local computers and shared files (Figure 6).

Top performing companies are more likely to use structured, collaborative data
management solutions like PDM, PLM, or Microsoft SharePoint.
On the other hand, the top performing companies are more likely to use structured,
collaborative data management solutions like PDM, PLM, or Microsoft SharePoint.
Specifically, world-class companies are 30% more likely to use PDM or PLM to manage
design data. The findings lead to a clear conclusion that structured data management
approaches like PDM/PLM help enable better product design and development
performance. Although the overall percentage of companies using Microsoft SharePointis small (about 5% overall), world-class companies are almost two times as likely to use
SharePoint to support their design processes. The SharePoint findings, coupled with thefact that world-class companies are less likely to use generic document management
systems, leads to another interesting conclusion. World-class manufacturers tend to use
more collaborative solutions such as SharePoint, PDM, or PLM.

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© Tech-Clarity, Inc. 2012

Figure 6: Primary Systems to Manage Design Data by Product Development Performance

As discovered in previous Tech-Clarity research, the fundamentals of design data
management include sharing information in addition to controlling it. The data shows thatworld-class companies are sharing more data (Figure 7). For example, leading
manufactures are 1.5 times as likely to be sharing data with suppliers using their data
management system. Of course sharing information is only valuable when theinformation is available and accurate, so it not surprising that world-class companies arealso 19% more likely to be controlling access to files (protecting IP) with their data
management systems, and 20% more likely to control versions / revisions this way.

Leading manufacturers are 1.5 times as likely to be sharing data with suppliers
using their data management system.
Beyond the basics of data management, some extended capabilities were also morecommonly found in world-class companies. For example, they are more likely toautomate product-related business processes. In fact, world-class companies are about
one-third more likely to use data management systems for managing design release andengineering change in addition to managing data. These capabilities, to some, mightdelineate the boundary between PDM and PLM systems. Regardless of definitions, thefundamentals provide value on their own and set up a foundation on which even broader
capabilities can be implemented to gain greater business value.

12© Tech-Clarity, Inc. 2012

Figure 7: Use of Design Data Management System by Product Development Performance

World-class companies are about one-third more likely
to use data management systems for managing design releaseand engineering change in addition to managing data.

Conclusion
Effective design data management fundamentals enable better product development
performance. The data shows, however, that companies face significant challenges inmanaging their critical design data due to product complexity. The challenges can lead toquality problems and inefficiency, and prevent companies from taking advantage ofstrategic opportunities such as design reuse. Addressing these challenges with effective
design data management practices and technology leads to significant businessadvantages, including improved efficiency, quality, and time to market. “If we don't
control our data properly we put revenue at risk,” explains an electronics manufacturer.
“Also, reuse of parts saves us hundreds of thousands of dollars each year.”“If we don't control our data properly we put revenue at risk.
Also, reuse of parts saves us hundreds of thousands of dollars each year.”Electronics Manufacturer
World-class companies are more effective in the area of design data management, yetalso spend less time on non-productive data management tasks. Other companies canlearn from them to improve data management without adding additional cost. “Data13© Tech-Clarity, Inc. 2012

management is very important,” explains one participant from an industrial equipment
manufacturer. “It has allowed our business growth to outpace the need to add moreengineering staff. We are doing much more with less effort.”“Data management is very important. It has allowed
our business growth to outpace the need to add more engineering staff. We aredoing much more with less effort.”
Industrial Equipment Manufacturer
World-class companies also take a more collaborative approach to design data
management. For example, they are more likely to use their data management systems toshare data internally. “Like most manufacturing / engineering companies the design data
is used in all areas of the company,” explains a consumer electronics manufacturer. “Thismeans that maximum efficiency is attained by keeping this data accurate and easily
accessible by all that need to see and use it.”To enable this more collaborative, efficient data management, world-class companies are
more likely to use structured, collaborative data management solutions such as PDM,
PLM or SharePoint. “Design data management is key, because in todays fast-paced
market people expect a better design in less time,” explains an industrial equipment
manufacturer. “From my experience the time and/or money lost by incorrect or
conflicting designs can be greatly reduced by refining the design process to include arobust data management system.” The fundamentals of design data management,
supported by an effective data management solution, provide significant business value
and provide a foundation that can be expanded on for future benefits.

Recommendations
Based on industry experience and research for this report, Tech-Clarity offers thefollowing recommendations:
•
•
•
•
•

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Ensure that your business has the basic fundamentals of data management in place
Improve design data management effectiveness to improve business performancein product design and development
Identify innefficiencies in data management tasks and reduce non-productive
time, freeing up time for innovation and greater design throughput
Explore the use of structured, collaborative tools including PDM, PLM, andSharePoint to improve data management and product development performance
Leverage design data management solutions beyond data to automate processes
and enhance collaboration© Tech-Clarity, Inc. 2012

About the Author
Jim Brown is the President of Tech-Clarity, an independent research and consulting firmthat specializes in analyzing the true business value of software technology and services.
Jim has over 20 years of experience in software for the manufacturing industries, with abroad background including roles in industry, management consulting, the software
industry, and research. His experience spans enterprise applications including PLM, ERP,
quality management, service, manufacturing, and others. Jim is passionate about
improving product innovation, product development, and engineering performancethrough the use of software technology and social computing techniques.
Jim is an experienced researcher, author, and public speaker and enjoys the opportunity
to speak at conferences or anywhere that he can engage with people that are passionate
about improving business performance through software technology.
Jim can be reached at jim.brown@tech-clarity.com. You can follow Jim on Twitter at@jim_techclarity, you can read his blog at www.tech-clarity.com/clarityonplm, or you
can find Tech-Clarity on Facebook.

About the Research
Tech-Clarity gathered and analyzed over 2,400 responses to a web-based survey on
managing design data. Responses were gathered by direct e-mail, social media outreach,and online postings by Tech-Clarity, Siemens PLM, Cadalyst, and 3DST. The responses
were filtered to identify manufacturers to get the perspective of people that manage
design data as a part of their business, resulting in 2,325 responses.
The respondents comprised design engineers (40%), design managers (10%), andengineering managers (9%), draftsmen (8%), and CAD managers (8%) with additional
representation from across the enterprise.
The respondents represented a mix of company sizes, including large companies withover 500 employees (38%), medium-sized companies with between 101-and 500
employees (29%), and smaller companies with less than 100 employees (33%).
The responding companies represent diverse manufacturing industries, including
Industrial Equipment (37%), Automotive (28%), Consumer Products (18%), Electronics& High Tech (17%), Aerospace and Defense (16%), Medical Devices (10%), and others.
The respondents reported doing business globally. The majority of companies design andmanufacture products in the North America (56%), about one-half design andmanufacture in China (51%), Asia/Pacific Rim (19%), Western Europe (18%), Latin
America (13%), Eastern Europe (9%), and India (8%) among others.
15© Tech-Clarity, Inc. 2012