Why Decisions, not data, should drive analytics and businesses
Decisions are the core of every business. Every day, organizations make numerous decisions ranging from what products to produce, which markets to target, which employees to hire, and which suppliers to partner with. With the abundance of data in today’s world, decision-making has become more complex, and organizations need to rely on analytics to make informed decisions.
Data analytics has been widely adopted by businesses as a means of making better decisions. However, it is not enough to rely solely on data analytics. Decision analytics is a better approach that combines data analytics with decision intelligence.
What is Decision Analytics?
Decision analytics is the process of using data analytics to support and optimize decision-making. It involves collecting, analysing, and interpreting data to identify trends, patterns, and insights that inform decision-making. Decision analytics uses a wide range of techniques, including statistical analysis, machine learning, data mining, and predictive modelling.
Decision analytics is not just about collecting and analysing data. It is about using the insights gained from the data to inform and improve decision-making. This requires a combination of data analytics, decision intelligence, and human judgment.
What is Decision Intelligence?
Decision intelligence is the ability to make good decisions in complex and uncertain situations. It involves understanding the decision-making process, identifying potential biases, and using a range of tools and techniques to improve decision-making. Check Decision Intelligence, except this time it’s not complicated to understand it better!
In summary, Decision intelligence is not just about making good decisions. It is about making better decisions than your competitors. It involves using data analytics to gain a competitive advantage and make decisions that drive business value.
Let’s say here, for it to be less confusing with all these termionologies, that Decision Analytics is the Decision Intelligence approach, while Data Analytics is the traditional BI view of problems.
Decision Analytics vs. Data Analytics
Data analytics is the process of collecting, analysing, and interpreting data to identify trends and insights. It involves using statistical analysis, machine learning, and other techniques to uncover patterns in the data.
Decision analytics goes beyond data analytics by incorporating decision intelligence into the decision-making process. It uses the insights gained from data analytics to inform and optimize decision-making. This requires an understanding of the decision-making process, potential biases, and how to use data to inform and improve decision-making.
In summary, data analytics provides the insights, and decision analytics uses those insights to inform and improve decision-making.
Why Decision Intelligence is Better than Normal Data Analytics
While data analytics provides insights into what has happened in the past, decision analytics provides insights into what will happen in the future. Decision analytics uses predictive modelling and other techniques to forecast future trends and identify potential opportunities and risks.
Decision analytics also takes into account the human factor in decision-making. It recognizes that decision-making is not just about data and analytics. It involves a range of factors, including intuition, experience, and human judgment.
By combining data analytics with decision intelligence, decision analytics provides a more comprehensive and accurate picture of the decision-making process. This results in better decision-making that drives business value and gives organizations a competitive advantage.
Real-World Examples of Decision Intelligence
An industry that has adopted decision intelligence at its best is the technology sector. Tech companies are always looking for ways to improve their products and services to meet the changing needs of customers. They need to make informed decisions quickly to stay ahead of the competition.
Netflix is an example of a tech company that has adopted decision intelligence to drive its business strategy. Netflix uses data analytics to track viewer behaviour and preferences. Then, it uses this data to recommend content to users and create its own original programming.
Netflix’s decision analytics approach has been successful in driving customer engagement and growth. By analysing viewer data, they were able to identify a gap in the market for original programming and launched its own shows, such as House of Cards and Orange is the New Black. These shows were huge hits, leading to increased subscriber growth and revenue for the company.
Another example is Google. Apart from having Cassie Kozyrkov, one of the founders of Decision Intelligence, as a Director, Google uses decision analytics to optimize its search algorithms and provide users with the most relevant search results. Google collects data on user behaviour, such as search queries and click-through rates, to identify trends and make improvements to its algorithms.
By using decision analytics, the algorithm has improved its search results to provide a better user experience, helping them to maintain their dominance in the search engine market.
Why does this matter to you?
The abundance of data in today’s world has made decision-making more complex for organizations, requiring the use of analytics to make informed decisions. While data analytics has been widely adopted, decision intelligence offers a better approach by combining analytics with decision factors to inform and optimize decision-making.
Decision intelligence involves understanding the decision-making process, identifying potential biases, and using a range of tools and techniques to improve decision-making.
It provides a more comprehensive and accurate picture of the decision-making process, resulting in better decisions and driving business value, which gives organizations a competitive advantage, as in the examples we discussed.
To adopt decision intelligence, businesses should invest in advanced analytics to integrate data insights with human judgment and biases. They should prioritize data quality and ensure decision-making is transparent and accountable. Overall, in my opinion, decision intelligence empowers businesses to make better decisions and gain a competitive advantage in their industry, while normal analytics is just reassuring what you probably already know.
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I’m a Senior Data Analyst and when people ask me what do I work with, I always say “I work with Decision Intelligence” because I try not to limit myself to data! It’s like they say, you have to be clever as a fox… 🦊
