Skip to main content
Mobile
  • Finance, Accounting & Economics
  • Global Business Management
  • Management, Leadership & Organisation
  • Marketing & Sales
  • Strategy
  • Technology & Operations
HS Talks HS Talks
Subjects  
Search
  • Notifications
    Notifications

    No current notifications.

  • User
    Welcome Guest
    You have Limited Access The Business & Management Collection
    Login
    Get Assistance
    Login
    Forgot your password?
    Login via your organisation
    Login via Organisation
    Get Assistance
Finance, Accounting & Economics
Global Business Management
Management, Leadership & Organisation
Marketing & Sales
Strategy
Technology & Operations
Practice paper

Thesis and antithesis — Innovation and predictive analytics: Σ (Past + Present) Data ≠ Future Success

Ted William Gross
Applied Marketing Analytics: The Peer-Reviewed Journal, 6 (3), 230-243 (2021)
https://doi.org/10.69554/MWXJ1645

Abstract

Predictive analytics (PA) is a tool routinely used by companies to help chart a future product path. It makes extensive use of algorithms and data mining to sort out market desires and trends. It also combines a robust host of artificial intelligence tools, including machine learning, pattern recognition, natural language processing, sentiment analysis and emotion recognition, among others, to achieve more precise results. PA, though, is imperfect, as it is often subject to the whims of the marketplace. Analysing past and present data does not, in any manner, guarantee positive results. Indeed, when it comes to innovation, particularly ‘disruptive innovation’, relying on PA can lead a company down a disastrous path. Data analytics requires a method that validates innovation and uses PA as something other than an infallible crystal ball. But does the possibility of innovation automatically disavow any insights into future market trends that PA may supply? This paper attempts to place both innovation and PA into proper perspective. It considers when, where, how and why PA and innovation are paramount, but reiterates the importance of instinct, originality and creativity. To illustrate its argument, the paper draws on the history of the Sony Walkman and Apple iPod.

Keywords: innovation; predictive analytics; disruptive innovation; disruption; market analytics; data analytics; artificial intelligence (AI)

The full article is available to subscribers to the journal.

Already a subscriber? Login or review other options.

Author's Biography

Ted William Gross has worked in the high-tech industry for over 30 years as a chief technology officer, vice president of research and development, team leader and programmer. His current study, seminars and lectures concentrate on the application of the principles of chaos theory to data analysis and artificial intelligence components, including machine learning, sentiment analysis, pattern recognition and disruptive innovation. Ted’s work on technology has been published on Medium and LinkedIn, as well as in a variety of professional journals.

Citation

Gross, Ted William (2021, January 1). Thesis and antithesis — Innovation and predictive analytics: Σ (Past + Present) Data ≠ Future Success. In the Applied Marketing Analytics: The Peer-Reviewed Journal, Volume 6, Issue 3. https://doi.org/10.69554/MWXJ1645.

Options

  • Download PDF
  • Share this page
    Share This Article
    Messaging
    • Outlook
    • Gmail
    • Yahoo!
    • WhatsApp
    Social
    • Facebook
    • X
    • LinkedIn
    • VKontakte
    Permalink
cover image, Applied Marketing Analytics: The Peer-Reviewed Journal
Applied Marketing Analytics: The Peer-Reviewed Journal
Volume 6 / Issue 3
© Henry Stewart
Publications LLP

The Business & Management Collection

  • ISSN: 2059-7177
  • Contact Us
  • Request Free Trial
  • Recommend to Your Librarian
  • Subscription Information
  • Match Content
  • Share This Collection
  • Embed Options
  • View Quick Start Guide
  • Accessibility

Categories

  • Finance, Accounting & Economics
  • Global Business Management
  • Management, Leadership & Organisation
  • Marketing & Sales
  • Strategy
  • Technology & Operations

Librarian Information

  • General Information
  • MARC Records
  • Discovery Services
  • Onsite & Offsite Access
  • Federated (Shibboleth) Access
  • Usage Statistics
  • Promotional Materials
  • Testimonials

About Us

  • About HSTalks
  • Editors
  • Contact Information
  • About the Journals

HSTalks Home

Follow Us On:

HS Talks
  • Site Requirements
  • Copyright & Permissions
  • Terms
  • Privacy
  • Sitemap
© Copyright Henry Stewart Talks Ltd

Personal Account Required

To use this function, you need to be signed in with a personal account.

If you already have a personal account, please login here.

Otherwise you may sign up now for a personal account.

HS Talks

Cookies and Privacy

We use cookies, and similar tools, to improve the way this site functions, to track browsing patterns and enable marketing. For more information read our cookie policy and privacy policy.

Cookie Settings

How Cookies Are Used

Cookies are of the following types:

  • Essential to make the site function.
  • Used to analyse and improve visitor experience.

For more information see our Cookie Policy.

Some types of cookies can be disabled by you but doing so may adversely affect functionality. Please see below:

(always on)

If you block these cookies or set alerts in your browser parts of the website will not work.

Cookies that provide enhanced functionality and personalisation. If not allowed functionality may be impaired.

Cookies that count and track visits and on website activity enabling us to organise the website to optimise the experience of users. They may be blocked without immediate adverse effect.