Gaining a competitive advantage in business is no longer just about accepting the status quo or relying on traditional approaches. Data-driven decision making (DDDM) involves making decisions that are based on data analytics and modelling, rather than on intuition or observation. It can provide accurate insights across a wide range of industries; however, DDDM doesn’t replace human decision-making. 

A combination of data and human intelligence can allow business leaders to obtain a deeper knowledge of customer patterns, trends and behaviours. If managers and data experts work together, they can use this data to make real-time decisions that are increasingly complex and informed. And long-term, it enables organisations to maximise management decisions, capitalise on emerging opportunities and achieve better business outcomes. 

Ultimately, Australian businesses can benefit from the power of data-driven decision-making if they understand their imperatives, invest in the right tools and technologies, and commit to a mindset that embraces collaboration, innovation and change. 

Developed with subject matter provided by the International Institute for Analytics, our new Data-driven Decision Making course is ideal for anyone who works with data – in small businesses through to multi-nationals. And if you’re keen to kick-start your career in the data science or data analytics sector, here’s an incentive for you – the industry is expected to be worth around $103B by 2023. So now is the ideal time to make data your (virtual) best friend! 

Learning Outcomes

• Gain insights into effective data-driven decision making
• Learn how to document an opportunity
• Understand your desired business outcomes
• Study how to focus your resources on the right analysis
• Learn how to frame a problem
• Discover how to ask the right questions
• Explore the steps for testing and validating assumptions
• Learn how to create an initial problem statement
• Study how to refine and finalise your problem statements
• Understand how to distinguish between common data categories
• Learn how to identify, scope and validate data
• Gain insights into identifying critical data needs
• Find out how data sets can be obtained from different data locations
• Learn about what considerations you need to make with data standards 
• Study how to select the appropriate analysis methods
• Understand what makes for effective data-driven decision making
• Learn how to solve your identified problems
• Study how to distinguish between reporting and analysis
• Explore the four common analytics categories
• Uncover the four business intelligence classes
• Learn how to determine an appropriate analysis type
• Study how to evaluate and refine analyses 
• Gain insights into testing analyses results
• Learn how to persuade and enable company leadership
• Understand how to make smart, informed and intentional decisions
• Uncover the elements of an empathy map
• Gain insights into the components of a compelling story
• Learn how to motivate action among key stakeholders
• Study how to evaluate your presentations for effectiveness
• Learn about the different output types of impactful presentations
• Discover how to present various levels of detail
• Uncover valuable elements you should include in your presentations
• Learn about effective labelling in presentations
• Study the repetition types used in presentations
• Understand how to present relatable material
• Learn how to deliver a concise, clear and compelling message
• Discover how to ensure you have all the facts when presenting
• Study how to focus your presentation for effective delivery
• Learn how to adapt a presentation to suit a variety of target audiences
• Understand the three key roles needed to position your analytic efforts for success
• Study how to present compelling analysis stories that enable a call to action

Insights into DDDM in Australia 

According to a survey conducted by professional services network, PricewaterhouseCoopers, 39 per cent of global organisations rate their decision-making as ‘highly data-driven’ with Australia lagging at 27 per cent. 

In fact, 61 per cent of Australian organisations admitted their decision-making process is only ‘somewhat’ guided by data, only 20 per cent of them use analytics to detect emerging opportunities, and only 5 per cent of those took action on data-driven insights.  

Other ‘Takeaways’ From the Survey Suggest: 

• Across all industries, Australian businesses are more likely to use analytics to diagnose a problem after the event rather than using it to make decisions to navigate the way forward.
• In terms of how Australian business leaders make decisions, they still prioritise experience and ‘gut feel’ over data-driven decisions.
• A variety of factors including budget constraints and the courage to ‘do something different’ hinder the way Australian business leaders approach decision-making.
• Many organisations are focused more on defending existing market share than they are on creating new revenue streams that will drive their future growth.

Case Study: Amazon

E-commerce sites typically use data to drive sales and profits. And if you’ve ever shopped on Amazon and received a product recommendation on their website, you’ve had a first-hand experience of a data-driven business decision! Other ways they use DDDM include: 

Recommendation engines

Amazon consistently uses collaborative filtering engines (CFE) to look at customers’ wish lists, previous purchases, history, reviews and virtual shopping carts. They then recommend products based on data from other customers’ similar purchases, with 35 per cent of their annual sales resulting from this strategy! 

Engagement Metrics 

Amazon also uses key engagement metrics like click-through, open and opt-out rates to further decide what recommendations to push to which customers. By integrating recommendations into nearly every aspect of their purchasing process – from browsing to check out – product recommendations have become one of their most successful methods of driving sales and increasing their bottom line.

Anticipatory Shipping Models

Analysing predictive data also allows the company to send potentially bought items to their local distribution centres – before they’ve even been purchased! This will enable them to reduce their expenses and offer a quicker (and more cost-effective) delivery service to their customers.

Optimised Prices

By analysing order histories, competitor pricing and expected profit margins, they can continually revise pricing to offer their customers the best possible deals – which keeps them coming back for more! It’s a win-win! 

 

Keen to make data part of your decision-making strategies? Learn how to harness both mind and machine with our Data-driven Decision Making course!