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: Business Intelligence: The Importance of Time to Value
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Analytics > Business Intelligence: The Importance of Time to Value
AnalyticsBig DataBusiness IntelligenceIT

Business Intelligence: The Importance of Time to Value

LyndsayWise
LyndsayWise
5 Min Read
Business Intelligence: The Importance of Time to Value
Illustration generated with Qwen Image.
SHARE

The BI market place is flooded with messaging from vendors saying they can provide analytical platforms and access to information faster, better, easier, and cheaper. This is true in many ways due to the shifts in technology:

  • storage is more cost effective
  • processing speeds are quicker
  • operational intelligence and access to information in near real-time is available more broadly
  • self-service models make it easy for many different types of users to interact with solutions
  • time to value is occurring more quickly due to quicker implementation times on a broad level

But even with all of these shifts and advancements in technology, many organizations are still left out in the cold because of the fact that it is difficult to sift through all of the solutions available to decipher where real value will lie. After all, many of the solutions available in the market place will meet the needs of many organizations depending on what the intended goal is. Identifying real value, however is something different to different businesses that depends largely on scope, goals, and expectations. 

When looking at the time to value specifically, the following should be noted:

  1. Realistic expectations should be set related to initial implementation times. These will differ based on new implementation or upgrade, technology used, complexity of data, and development of business rules and delivery platform.
  2. Many factors require consideration when implementing a solution that may affect timelines.
  3. Some solutions will require an iterative approach, meaning that value will increase over time. Businesses need to identify what is realistic and what they can accept.
  4. The level of value will differ based on the targeted audience. 
  5. The meaning of time to value and value itself needs to be identified as it will differ based on stakeholder. For instance, does time to value translate to implementation times? Or does it rely on goals set to save costs or increase profits?

The reality is that there is no single definition identifying what “time to value” means within the market. What this translates to for companies evaluating solutions is that much of what they hear will relate to implementation times and not how that translates in terms of time to the iterations required to get BI right and provide a framework for overall value. The value being actual results, whether they be the ability to lessen wasteful spending by targeting customer needs better, lowering customer churn rates, identifying issues before they become problems, or increasing profit margins. Therefore, it stands to reason that organizations require the education and tools to develop their own expectations surrounding time to value. It will always be possible for vendors to estimate the implementation of various solution components, but they will not be able to identify how BI will be applied, what business questions will be asked over time, or how decision makers will leverage their information assets to improve overall efficiencies. This remains the realm of BI stakeholders and those in charge of asking the right questions and delving deeper into the information at hand. 

More Read

Keeping Singapore Green with Data and Design
Keeping Singapore Green with Data and Design
Big Data Is A Huge Boost To Emerging Telecom Markets
Q & A with Eric Siegel, President of Prediction Impact
Brains and Databases: An Obsession with Time Keeping
3 Organizations That Can See the Future with Predictive Analytics

For many organizations, the goal is simply to get a dashboard or set of analytics up and running, thinking that the value they achieve will come naturally. The truth is a bit different. A solution can only go so far without getting into the hands of the right people. The right people asking quantifiable questions to get to the heart of business challenges are what leads to true time to value. After all, technology is meant to support our business operations and not make the decisions for us. 

This post was written as part of the IBM for Midsize Business program, which provides midsize businesses with the tools, expertise and solutions they need to become engines of a smarter planet. I’ve been compensated to contribute to this program, but the opinions expressed in this post are my own and don’t necessarily represent IBM’s positions, strategies or opinions.`

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

Flat editorial illustration: The article describes an AI safety incident where an agent bypassed sandbox controls by exploiting D
OpenAI Pauses Advanced AI Work After Agent Bypasses Sandbox Controls
Artificial Intelligence News Security
Flat editorial illustration: The article explains that training robots for physical interaction requires three distinct data cate
Physical AI: What Data Do You Need to Train a Robot?
Artificial Intelligence Exclusive Robotics
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
Analytics Big Data Exclusive Software
Flat editorial illustration: The article examines AI agents that escalate from legitimate data retrieval to attempted intrusions
OpenAI’s Government Website Incidents Raise a Hard Question for AI Agents: When Should They Stop?
Artificial Intelligence News Security

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

How Is Mobile Technology Impacting the Food and Beverage Supply Chain?
AnalyticsBusiness IntelligenceData QualityData VisualizationDecision ManagementMobilityPredictive AnalyticsSoftwareWorkforce Analytics

How Is Mobile Technology Impacting the Food and Beverage Supply Chain?

5 Min Read
Defining Big Data for the Public CIO
Big DataCommentary

Defining Big Data for the Public CIO

8 Min Read
5 Levels of Big Data Maturity in an Organization [INFOGRAPHIC]
Big Data

5 Levels of Big Data Maturity in an Organization [INFOGRAPHIC]

4 Min Read
Big Data Challenges Of Industry 4.0 Worth Considering
Big DataExclusivePrivacySecurity

Big Data Challenges Of Industry 4.0 Worth Considering

7 Min Read

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

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

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?