We use cookies, including third-party cookies from Google to serve personalized ads through AdSense, to operate this site and understand how it is used. By continuing to browse, you accept this use. See our Privacy Policy and Terms of Use for details, including how to opt out of personalized advertising.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    What Kind of Problem-Solving Distinguishes Data Analysts From Software Engineers -- AI-generated illustration
    What Kind of Problem-Solving Distinguishes Data Analysts From Software Engineers
    7 Min Read
    chatgpt image jul 21, 2026, 04 34 30 pm
    4 Core Benefits of Predictive Maintenance after Vibration Analysis
    10 Min Read
    How Does Data Mining Boost Customer Satisfaction in Logistics? Harnessing Analytics for Results -- AI-generated illustration
    How Does Data Mining Boost Customer Satisfaction in Logistics? Harnessing Analytics for Results
    11 Min Read
    chatgpt image jul 13, 2026, 04 23 45 pm
    How Data Analytics Helps Companies Improve User Engagement
    19 Min Read
    chatgpt image jul 13, 2026, 03 59 46 pm
    How Data Analytics Improves Multi-Location Search Strategies
    10 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Designed to be used
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Business Intelligence > Designed to be used
Business Intelligence

Designed to be used

JuiceAnalytics
JuiceAnalytics
4 Min Read
Designed to be used
Photo by wal_172619_II on Pixabay (https://pixabay.com/photos/building-facade-architecture-glass-7879891/)
SHARE

I have become curiously interested in this post that talks about how it’s difficult to correctly write an application for the iPhone. The assertion is that writing software for the iPhone is harder than for a desktop, not because of the technology, but because:

“everything counts so much — every design choice, every line of code, everything left in and everything left out.”

Very eloquently and precisely put. If you’ve ever used any sort of mobile computing platform, not just the iPhone, you know how much proper design can make an application really useful – or totally useless.

But then again, isn’t this the case with any application? Aren’t the best ones those in which the designer applied Brent’s assertion for iPhone software? Some applications seem to have their genesis in the charter “build an application that allows the user to perform all these actions” while others are built on the charge “build an application that helps the user solve this problem” — it’s the battle of functionality versus purpose.

Take a look at ChartChooser based on Andrew Abela’s “smart charting” guidelines. It doesn’t help users figure out how to pick a bar chart or pie chart. What it does is to help them answer the “what’s the right way to show this information” question. There’s not a lot buttons or features, it just does one thing well. There are certainly other good (better?) examples out there as well (FlipVideo, Evernote, Tivo, to name a few). The better the software, the less the user will think about it when using it to get their job done.

More Read

How Technology Has Shaped Organizational Change Management
How Technology Has Shaped Organizational Change Management
Business Intelligence and Why You Need It
New Technology Is Not an Easy Button for Big Data
Social Dynamx, Scaling Social Customer Support
Target variables matter but so do decisions.

In line with this thinking, we put together a short list of some design principles that we use to keep the user productive:

  • Solve a problem – Make sure the end product provides a specific solution to a specific problem so the user can easily understand how it helps them.

  • Enable casual use – Minimize the “barrier to entry” for new users by avoiding feature overload, minimizing clicks for each task, and by not letting polish become bling.

  • Tell a story – Relate the data to the key questions, answering them in a logical order and revealing layers of detail as users express interest in knowing more, not before.

  • Lead to action – Empower the user to finish their task quickly (btw, the “task” is not “using software”).

  • Encourage exploration – Use the experienced guide approach to give the user enough context to understand the problem and then point them in the right direction to learn about new factors that will expand their insight.

 

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

Flat editorial illustration: The article's core relationship is workload-by-workload decision-making for cloud migration, where s
Which Workloads Should Move to the Cloud?
Cloud Computing Exclusive IT
Flat editorial illustration: The article positions data governance as a strategic board-level concern rather than a purely techni
Why Data Governance Is Becoming a Board-Level Business Priority
Big Data Exclusive Policy and Governance
Flat editorial illustration: The article argues that data annotation quality should be measured by inspectable gold sets, written
The Top Data Annotation Companies Are Separated by Proof of Quality, Not Headcount
Big Data Exclusive
Flat editorial illustration: The article's core relationship is the gap between raw bank-feed records and reliable subscription i
Subscription Trackers Have a Transaction Data Problem
Big Data Exclusive

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

AI Artificial intelligence infrastructure
Artificial Intelligence

Will the Integration of Accounting & Artificial intelligence Fruitful?

5 Min Read
agenic ai
Artificial IntelligenceExclusive

How Businesses Are Using AI to Make Smarter, Faster Decisions

Decision Management’s 'Epsom Salt' Problem
Decision Management

Decision Management’s ‘Epsom Salt’ Problem

3 Min Read
Patient-Centered Data-Driven Care: Carolina Advanced Health
AnalyticsCollaborative DataData MiningData WarehousingDecision ManagementPolicy and GovernanceRisk Management

Patient-Centered Data-Driven Care: Carolina Advanced Health

0 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 chatbot
How AI Website Chatbots Improve Customer Support and Lead Generation
Chatbots Exclusive
Artificial Intelligence for eCommerce: A Closer Look
Artificial Intelligence for eCommerce: A Closer Look
Artificial Intelligence

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-26 SmartData Collective. All Rights Reserved.
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?