By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    AI analytics
    AI-Based Analytics Are Changing the Future of Credit Cards
    6 Min Read
    data overload showing data analytics
    How Does Next-Gen SIEM Prevent Data Overload For Security Analysts?
    8 Min Read
    hire a marketing agency with a background in data analytics
    5 Reasons to Hire a Marketing Agency that Knows Data Analytics
    7 Min Read
    predictive analytics for amazon pricing
    Using Predictive Analytics to Get the Best Deals on Amazon
    8 Min Read
    data science anayst
    Growing Demand for Data Science & Data Analyst Roles
    6 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-23 SmartData Collective. All Rights Reserved.
Reading: 3 Pitfalls to Avoid When Using Data to Make Decisions
Share
Notification Show More
Aa
SmartData CollectiveSmartData Collective
Aa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Business Intelligence > Decision Management > 3 Pitfalls to Avoid When Using Data to Make Decisions
Big DataBusiness IntelligenceDecision Management

3 Pitfalls to Avoid When Using Data to Make Decisions

Seb Whitehead
Last updated: 2017/07/06 at 12:36 PM
Seb Whitehead
4 Min Read
Using Data
SHARE

Data is not just a buzzword thrown around in the marketing sphere. Data is collected and analysed effectively in order to realise what a business is doing well, what a business is doing less well, and how a business can improve. Without taking the data on board and using it to facilitate change, there would be little point in collecting it. However, there are issues when it comes to interpreting and using data to make decisions in business. It’s not as straightforward as it seems, and there are certainly pitfalls to avoid.

Contents
Anchoring and AdjustmentOverconfidence in DataCausation vs Correlation

Anchoring and Adjustment

Anchoring and adjustment refer to the idea of dropping an anchor – or investing heavily in a piece of information – and then adjusting around that anchor. Often, the anchor works as a good starting point, but data may indicate that new avenues should be explored in order to create better success. Often, data can be collected and analysed within the realm of the anchor – neglecting the fact that the anchor itself may be the reason the business isn’t doing as well as it should be. Experts, including Value Walk reinforce this when discussing how investors react to fluctuations in the stock market indices and how behavioural finance can help inform their decisions. Investors often want to be proven right, so are mired in their initial assessments, not taking into account new information that progresses with the market. This reasoning of course extends to other applications too, including running a business or implementing a strategy.

Overconfidence in Data

Overconfidence can be a pitfall when it comes to actionable plans resulting from the collected data. Familiarity with a business decision, the abundance of information data causes, and the mere fact we have already taken action by analysing the data can all combine to create a scenario of overconfidence. And this scenario will likely result in failure. The more familiar we are with a decision, the more confident we feel about it. So if the data results in a brand new targeting campaign, which we haven’t implemented before, we would feel that we could handle it, even if it was a more difficult option. But that would be wrong to merely assume. Data gives the impression we have a lot of information available to us, yet it isn’t always meaningful enough to create the results we need. And by analysing the data, we feel we have made progress. Data should result in new ideas outside of what we already know – otherwise, we may be suffering from overconfidence.

Causation vs Correlation

Probably the most important pitfall not to succumb to in data collection and analysis is not taking into account the difference between causation and correlation. Causation states that X occurs because of Y, while correlation merely points at a relationship between X and Y. There may be a correlation between high revenue and social media engagement, but that doesn’t necessarily mean that the social media engagement is the cause of the high revenue. By ascertaining which is which and not making decisions on false causations, the correct decisions and recommendations can be made based on the data.

More Read

residential proxies

How Residential Proxies Help Improve Data Gathering

Four Strategies For Effective Database Compliance
5 Big Data Storage Solutions
Discover the Power of Analytical Insights in Your Business Data
How To Keep Your Data Security Knowledge Up To Date?

Data is collected for a reason – and can only be properly utilised if the analysis is done accurately. By taking into account issues that could potentially skew the results – and therefore skew the recommendations collate from the data, businesses can ensure they are moving in the right direction.

TAGGED: business decisions, data collection, data management
Seb Whitehead July 5, 2017
Share This Article
Facebook Twitter Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

Data Ethics: Safeguarding Privacy and Ensuring Responsible Data Practices
Data Ethics: Safeguarding Privacy and Ensuring Responsible Data Practices
Best Practices Big Data Data Collection Data Management Privacy
data protection for SMEs
8 Crucial Tips to Help SMEs Guard Against Data Breaches
Data Management
How AI is Boosting the Customer Support Game
How AI is Boosting the Customer Support Game
Artificial Intelligence
AI analytics
AI-Based Analytics Are Changing the Future of Credit Cards
Analytics Artificial Intelligence Exclusive

Stay Connected

1.2k Followers Like
33.7k Followers Follow
222 Followers Pin

You Might also Like

residential proxies
Big Data

How Residential Proxies Help Improve Data Gathering

7 Min Read
database compliance guide
Data Management

Four Strategies For Effective Database Compliance

8 Min Read
Data Management

5 Big Data Storage Solutions

6 Min Read
analytical insights for business data
Analytics

Discover the Power of Analytical Insights in Your Business Data

5 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 is improving the safety of cars
From Bolts to Bots: How AI Is Fortifying the Automotive Industry
Artificial Intelligence

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
Go to mobile version
Welcome Back!

Sign in to your account

Lost your password?