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
    stock investing and data analytics
    How Data Analytics Supports Smarter Stock Trading Strategies
    4 Min Read
    predictive analytics risk management
    How Predictive Analytics Is Redefining Risk Management Across Industries
    7 Min Read
    data analytics and gold trading
    Data Analytics and the New Era of Gold Trading
    9 Min Read
    composable analytics
    How Composable Analytics Unlocks Modular Agility for Data Teams
    9 Min Read
    data mining to find the right poly bag makers
    Using Data Analytics to Choose the Best Poly Mailer Bags
    12 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Embracing the Unexpected
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Data Management > Culture/Leadership > Embracing the Unexpected
Business IntelligenceCommentaryCulture/LeadershipKnowledge ManagementPredictive Analytics

Embracing the Unexpected

MIKE20
MIKE20
5 Min Read
SHARE

The nineteen century belonged to the engineers.  Western society had been invigorated and changed beyond recognition by the industrial revolution through its early years and by its close the railroads were synonymous with the building of wealth.

The nineteen century belonged to the engineers.  Western society had been invigorated and changed beyond recognition by the industrial revolution through its early years and by its close the railroads were synonymous with the building of wealth.

The nineteen century was the era that saw the building of modern business with the foundation being established for many of the great companies that we know today.  The management thinkers who defined the discipline cluster around the first part of the twentieth century and it should be no surprise that they were heavily influenced by the engineers.

More Read

CRM business intelligence
Convergence 2013: CMOs Ain’t Rich, MSDynCRM is Getting There
AI Can Improve Financing Access and Equitability to Disadvantaged Socioeconomic Groups
Tom Davenport’s Culture of Analytics
10 Ways How Artificial Intelligence Is Changing the Content Writing Landscape
What To Know About Using Artificial Intelligence For Big Data Analysis

Business was built around the idea of engineered processes with defined inputs and outputs.  I’ve written before about the shift from process-driven to information-driven business.  In this post, though, I am really focusing on another consequence of the engineering approach to the running of businesses, the expectation of achieving planned outcomes.

There is a lot to be said for achieving a plan.  Investors dream of certainty in their returns.  Complex businesses like to be able to align production schedules.  Staff like knowing that they have a long-term job.

When you’re building a bridge or a railroad, there is certainty in the desired outcome.  Success is measured in terms of a completed project against time and budget.

When your business has a goal of providing products or services into a market, the definition of success is much harder to nail down.  You want your product or service to be profitable, but you are usually flexible on its exact definition.  However, internal structures tend not to have this flexibility built in.  Large businesses operate by ensuring each part of the organisation delivers their component of a new project as specified by the overall design.

This sounds fine until you look at these components in more detail.  Many are fiendishly complex.  In particular the IT can often involve many existing and new systems which have to be interfaced in ways that were never intended when they were originally created.  Staff trained to achieve a single outcome in the market keep on testing customers until they gain (or even bludgeon) acceptance for the product or service design.

Because of the scale of these projects, failure is not an option.  The business engineering philosophy that I’ve described will push the launch through regardless of the obstacles.  However, there is a growing trend in business to try and use “big data” to run experiments and confirm that the design of a new product or service is correct before this effort is undertaken.

There is also another trend in business.  Agile.  Agile methods are characterised by an evolutionary approach to achieving system outcomes.

Individually these trends make sense.  Taken together they may actually be starting to indicate a deeper change.  In a future world we may treat business as an experiment in its own right.  We know what the outcome is that we expect, but we will push our teams to embrace issues and look for systemic obstacles to guide us in new, and potentially more profitable, directions.

When customers don’t react positively to our initial designs, rather than adjust the design to their aesthetic, business should ask whether the product is appropriate at all and consider making a radical shift even at the last minute.

When IT finds that a system change is harder than they expected, they can legitimately ask whether there is a compromise that will deliver a different answer that might be equally acceptable, or sometimes even more useful.

One of the major differences between scientists and engineers is that the former look for the unexpected in their experiments and try to focus on the underlying knowledge they can get from things not going as planned.  Perhaps twenty-first century business needs less people thinking like engineers trying to railroad new products and services into the market and more who are willing to don the lab coat of a scientist who is willing to allow the complexity of modern business to flourish and support their innovation.

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

stock investing and data analytics
How Data Analytics Supports Smarter Stock Trading Strategies
Analytics Exclusive
qr codes for data-driven marketing
Role of QR Codes in Data-Driven Marketing
Big Data Exclusive
microsoft 365 data migration
Why Data-Driven Businesses Consider Microsoft 365 Migration
Big Data Exclusive
real time data activation
How to Choose a CDP for Real-Time Data Activation
Big Data Exclusive

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

Affiliate Summit West

2 Min Read
HR Analytics
Data MiningData VisualizationDecision ManagementKnowledge ManagementRisk ManagementWorkforce AnalyticsWorkforce Data

Workforce Planning and HR Analytics

5 Min Read
big data
AnalyticsBig DataBusiness IntelligenceDecision ManagementStatisticsUnstructured DataWorkforce Data

Analytics at Google: Great Example of Data-Driven Decision-Making

8 Min Read
Image
Business IntelligenceModeling

How Nike is Using Data to Help Save the Planet

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 chatbot
The Art of Conversation: Enhancing Chatbots with Advanced AI Prompts
Chatbots
AI chatbots
AI Chatbots Can Help Retailers Convert Live Broadcast Viewers into Sales!
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?