Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    image fx (67)
    Improving LinkedIn Ad Strategies with Data Analytics
    9 Min Read
    big data and remote work
    Data Helps Speech-Language Pathologists Deliver Better Results
    6 Min Read
    data driven insights
    How Data-Driven Insights Are Addressing Gaps in Patient Communication and Equity
    8 Min Read
    pexels pavel danilyuk 8112119
    Data Analytics Is Revolutionizing Medical Credentialing
    8 Min Read
    data and seo
    Maximize SEO Success with Powerful Data Analytics Insights
    8 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: The Technology Adoption Life Cycle
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Uncategorized > The Technology Adoption Life Cycle
Uncategorized

The Technology Adoption Life Cycle

PhilSimon
PhilSimon
6 Min Read
SHARE


I have spent time this week working on new piece for Cutter on emerging technologies such as cloud computing and MDM. Interestingly, I returned to a tried and true concept: Technology Adoption Life Cycle (TALC). For those of you unfamiliar with TALC, Wikipedia defines it as a model that

Contents
Which type of organization is most likely to be on the left side of TALC?Which type of organization is most likely to be on the left side of TALC?

…describes the adoption or acceptance of a new product or innovation, according to the demographic and psychological characteristics of defined adopter groups. The process of adoption over time is typically illustrated as a classical normal distribution or “bell curve.” The model indicates that the first group of people to use a new product is called “innovators,” followed by “early adopters.” Next come the early and late majority, and the last group to eventually adopt a product are called “laggards.”

While enterprise technologies have certainly changed in my fifteen years of working with them, one question continues continues to intrigue me:

Which type of organization is most likely to be on the left side of TALC?

To simplify matters, I’ll place all organizations into three categories:

More Read

2009 Retrospective
NRC Report: Data Mining won’t find the Terrorists
Slouching Toward Creepiness: Analyzing Human-Computer Interaction
Wolfram Talks About Wolfram Alpha
Google Wave or just a Blip?
  • The Struggling Organization
  • The Self-Sufficient Organization
  • The …


I have spent time this week working on a new piece for Cutter on emerging technologies such as cloud computing and MDM. Interestingly, I returned to a tried and true concept: Technology Adoption Life Cycle (TALC). For those of you unfamiliar with TALC, Wikipedia defines it as a model that

…describes the adoption or acceptance of a new product or innovation, according to the demographic and psychological characteristics of defined adopter groups. The process of adoption over time is typically illustrated as a classical normal distribution or “bell curve.” The model indicates that the first group of people to use a new product is called “innovators,” followed by “early adopters.” Next come the early and late majority, and the last group to eventually adopt a product are called “laggards.”

While enterprise technologies have certainly changed in my fifteen years of working with them, one question continues continues to intrigue me:

Which type of organization is most likely to be on the left side of TALC?

To simplify matters, I’ll place all organizations into three categories:

  • The Struggling Organization
  • The Self-Sufficient Organization
  • The Adventurous Organization

Note that economic conditions mean that all bets are off. Many successful organizations these days lack the funds for many desirable or even necessary technological improvements.

The Struggling Organization

Over the course of my career, I’ve had many discussions with people about the challenges that their organizations face implementing new systems and why so many projects failed to hit their marks. While by no means a definitive list, consider the following:

  • the difficulty of gathering comprehensive system requirements during the discovery phase
  • the dynamic nature of requirements
  • the inevitable scope creep and resultant problems during IT projects

Issues like these have plagued both organizations for years. What’s more, they continue to manifest themselves during many (if not most) major IT projects. As a result, organizations that have historically struggled with enterprise systems will rarely—if ever—be on the left of TALC. If anything, they are the very definition of laggards.

The Self-Sufficient Organization

Often I’ll assist organizations begrudgingly upgrading systems. In these cases, the motivation is clearly the stick, not the carrot. For these organizations, previous implementation issues and future enhancements to their apps just don’t matter now (as well as in the short- and mid-terms). These types of organizations are going live in a few weeks and the focus is very much on what needs to happen to continue paying employees, running financial reports, and the like. Only well after the dust settles will “future enhancements” be broached.

In terms of TALC, organizations “getting by” are usually reluctant to take the lead on a new but largely untested technology. You’ll most likely find them in the early to late majority of TALC.

The Adventurous Organization

Then there are organizations that want to be on the leading edge–or perhaps need to be, based on some business reason. They have the following:

  • sufficient financial resources
  • sufficient human resources
  • a “risk-tolerant” culture
  • a compelling business need

These organizations are more likely to implement a largely untested technology and be on the left side of TALC. As an added incentive, at times, software vendors are willing to work with “beta clients” by providing free or heavily discounted resources. In exchange, the vendor will be able to promote the product’s implementation as a successful case study.

Conclusion

Organizations that have had problems implementing and maintaining their systems tend not to be early adopters. In other words, financial, cultural, and political reasons place the vast majority of organizations squarely in the middle of the curve. When walking is a challenge, it’s hard to imagine running.

Feedback

What do you think? Are there are other reasons that organizations often take a “wait and see” approach?

Photo from Wikipedia.

The Technology Adoption Life Cycle is a post from: Phil Simon

TAGGED:enterprise technologyit projectstechnology adoption life cycle (talc)
Share This Article
Facebook Pinterest LinkedIn
Share
ByPhilSimon
Phil Simon is a recognized technology authority. He is the award-winning author of eight management books, most recentlyAnalytics: The Agile Way. He <consults organizations on matters related to communications, strategy, data, and technology. His contributions have been featured on The Harvard Business Review, CNN, The New York Times, Fox News, and many other sites. In the fall of 2016, he joined the faculty at Arizona State University’s W. P. Carey School of Business.

Follow us on Facebook

Latest News

image fx (2)
Monitoring Data Without Turning into Big Brother
Big Data Exclusive
image fx (71)
The Power of AI for Personalization in Email
Artificial Intelligence Exclusive Marketing
image fx (67)
Improving LinkedIn Ad Strategies with Data Analytics
Analytics Big Data Exclusive Software
big data and remote work
Data Helps Speech-Language Pathologists Deliver Better Results
Analytics Big Data Exclusive

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

The Chopping Block: Three Questions to Ask When Considering Cutting Features from an IT Project

7 Min Read

Is Twitter Dying?

4 Min Read

Business Sponsorship

8 Min Read

Overcoming the Barriers to IM Success: Learn from the Past.

4 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

ai in ecommerce
Artificial Intelligence for eCommerce: A Closer Look
Artificial Intelligence
ai chatbot
The Art of Conversation: Enhancing Chatbots with Advanced AI Prompts
Chatbots

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-25 SmartData Collective. All Rights Reserved.
Go to mobile version
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?