Data-driven decision making: How data is driving business decisions for the future

Data-driven decision making: How data is driving business decisions for the future

Data-driven decision making (DDDM) is becoming a more prevalent strategy for business decisions in 2019 and beyond. It involves making decisions that are supported by data analytics and modelling, rather than choices solely based on intuition or observation. 

Data is now an integral part of management decision making. Analytics provide accurate insights and the basis for decisions made across a multitude of industries, such as medicine, transportation and equipment manufacturing.

This article explores what DDDM is, and how it can be implemented to help achieve better business outcomes. Using the example of Amazon, explore how a major corporation uses DDDM to increase their ROI.

DDDM: the combination of data and human decision-making

Also described as data-driven decision management, DDDM extrapolates data to illustrate projections and forecasting, which can be combined with the human aspects of decision making. Rather than going with ‘gut feeling’, machine learning and artificial intelligence (AI) are readily used to inform businesses of issues and solutions.

Data scientist roles are becoming more important in a business’ success. They work closely with managers to translate data into key business insights. Data scientists and managers can use DDDM to procure unbiased opinions from the data, rather than decisions and data acted on from an emotional perspective.

It’s important to know that DDDM doesn’t replace human decision making. They both work in tandem and are best utilised by combining the two. This is where the relationship between data scientists and managers is key, as they work together to analyse data and use it to formulate insights that impact management decisions and future initiatives.

Data can inform leadership decisions

With the incorporation of DDDM, it’s essential to have a plan of action – not just a focus on collecting as much data as possible. In carrying out DDDM, you need to:

1. Plan a strategy with your data team to understand what you’re looking for and what you’re trying to achieve
2. Identify what questions you need to ask
3. Identify the data you may need to answer those questions
4. Understand the costs to see if the effort is justified
5. Collect the data
6. Analyse the data
7. Present and distribute the information in business terms and tell a story with the data
8. Incorporate these data insights into your business.

By carrying out this plan, you will be fully prepared to incorporate DDDM into your managerial style, working with data scientists to innovate your business now and in the future. This more democratic style of decision-making uses collaboration to turn data into competitive advantages.

Case study: How does Amazon incorporate DDDM into their business?

Amazon is a prime example of a major corporation using the DDDM method in a variety of ways for business growth.

Recommendation engines

Using collaborative filtering engines (CFE) to look at previous purchases, wish list, shopping cart, reviews and history, Amazon then recommends products with data from other customers’ similar purchases. This strategy generates 35% of the company’s annual sales.

Anticipatory shipping models

Predictive analysis helps to send potential bought items to your local distribution center. This allows for quicker delivery and reduced overall expenses for Amazon. DDDM also informs the company to select vendors that are closest to you when ordering a product. Better delivery schedules and routes help to reduce shipping costs.

Optimised prices

By collating competitor pricing, order histories and expected profit margins, Amazon changes prices every 10 minutes to offer the best deals for customers and to keep them coming back for more discounted prices.

This is just one example of a large corporation using DDDM to make more informed business decisions. The specific tactics Amazon use are only some of the ways data can be used to better inform your own decision making for future business growth.

If you want to learn more about making informed decisions with data, James Cook University offers Data Analysis and Decision Modelling for online study. You can upskill your decision making – while still maintaining your position in your current employment – over a seven-week study period. If you’re interested in using data to make you the best manager possible, become an expert in data analysis and decision modelling in less than eight weeks at James Cook University. A global MBA will ensure that you stay competitive in any international market.