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
    car expense data analytics
    Data Analytics for Smarter Vehicle Expense Management
    10 Min Read
    image fx (60)
    Data Analytics Driving the Modern E-commerce Warehouse
    13 Min Read
    big data analytics in transporation
    Turning Data Into Decisions: How Analytics Improves Transportation Strategy
    3 Min Read
    sales and data analytics
    How Data Analytics Improves Lead Management and Sales Results
    9 Min Read
    data analytics and truck accident claims
    How Data Analytics Reduces Truck Accidents and Speeds Up Claims
    7 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
Shutterstock Licensed Photo - By Gunnar Pippel
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

Why Big Data is a Big Deal for Sales: New Infographic
3 Organizations That Can See the Future with Predictive Analytics
Dresner: Mobile Business Intelligence to Transform BI Industry
Domain Management Concepts: Thinking Strategically About DNS
5 Technologies Massively Disrupting Hotel Customer Service in the Age of Big Data

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

warehousing in the age of big data
Top Challenges Of Product Warehousing In The Age Of Big Data
Big Data Exclusive
car expense data analytics
Data Analytics for Smarter Vehicle Expense Management
Analytics Exclusive
using accrual data to improve financial forecasts
Using Accrual Data to Improve Financial Forecasts
Big Data Exclusive
image fx (60)
How Finance & BI Teams Choose Accounting Software
Big Data Business Intelligence Exclusive

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

programming concepts for data scientists
Big DataData ScienceExclusiveProgramming

Crucial Programming Concepts For Data Scientists

6 Min Read

Here’s Why Natural Language Processing is the Future of BI

8 Min Read

Know Your S#*!: Maximize Web Conversion with A/B Testing

8 Min Read
Restaurant Industry
Cloud ComputingIT

3 Impacts of the Cloud Revolution on the Restaurant Industry

6 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 and chatbots
Chatbots and SEO: How Can Chatbots Improve Your SEO Ranking?
Artificial Intelligence Chatbots Exclusive
ai in ecommerce
Artificial Intelligence for eCommerce: A Closer Look
Artificial Intelligence

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?