Session 4: Strategic Benefits of DDDM

Companies that rely on data expect a better financial performance. | Harvard Business Study Review

DDDM can move an organisation toward an evidence-based culture that is focused on the future. It promotes decisions based on data, analysis, experimentation, evaluation and evidence rather than opinions, intuition, or indicators that are less than predictive or reliable. The organisation becomes proactive rather than reactive.

Data can certainly help organisations improve record keeping and compliance. But rather than simply report data for compliance reasons after the event (reactive), the organisation can use data to drive decisions that improve programs, activities, or strategies before the event (predictive). An organisation embracing DDDM places real value on decisions supporting problem solving, innovation, and improvement processes that can be supported by verifiable data.

The Q Score

Across all industries, data decision making has an impact, even in ones you might not suspect. Take the entertainment industry: The Q Score is a qualitative measure of programs and celebrities, alongside a standard for measuring consumer appeal of performers, brand ambassadors, influencers, characters and licensed properties and brands.

Based upon this data, television networks, steaming services, social platforms, advertisers, digital marketers and other related industries are able to track who and what brand has the most consumer appeal.

The Q Score has been tracking celebrity appeal since 1964 and long before automated data decision making algorithms. In the 1980s, for instance, the actor Ted Danson from the popular television series Cheers, had the highest Q Score rating. Danson was a valuable asset for advertisers because his ratings were based on likeability and trust and therefore a perfect celebrity to promote their products.

The Q Score index now includes popular YouTube entertainers. PewDiePie, for instance, has the highest Q Score among 6-to-12-year- olds (40) and 9-to-14-year-olds (38). But that score falls to 15 in the 13-to-24-year-old demographic, where Jenna Marbles and Grace Helbig rank highest. Among total viewers over age six, Higa, Smosh, and Helbig all tie for first, at 23.

Q Scores | 4:44 mins

Amazon Case Study

Have you ever left a review on Amazon? This company relies on an algorithm called ‘item-to-item collaborative filtering’ that customises the browsing experience for returning customers. Amazon analyses the users key engagement metrics such as click-through rates, open rates and opt-out rates to further decide what recommendations to push to their target customer. By integrating recommendations into nearly every aspect of Amazon’s purchasing process, from product browsing to checkout, the company has found that product recommendations drive sales.

Leaving a positive review on Amazon raises the customer experience because the recommendation helps consumers find a product they may like, without wading through page after page of items, and while simultaneously triggering a reaction that makes them feel Amazon actually knows them. This is why Amazon spends so much time personalising the experience, to make you feel valued, just like an exchange with a friendly salesperson.

As tracking our movements becomes more ingrained, and the use of AI incorporating facial recognition, length of time you pause on an item by tracing eye and finger movements alongside subtle body language cues, the more relevant data will be targeted to your personal taste.


Bernard Marr (2020), Why every business needs a data and analytics strategy, Blog.

Advantages of DDDM can include:

1. Improvements to transparency and accountability as to how a problem was solved or actions were prioritised.

2. Greater efficiency as continuous improvement streamlines the processes supporting decision making and problem solving. This includes being able to track improvements over time and critically examining where improvements need to be made in the DDDM process.

3. Real-time access to insights that inform choices and accelerate responses. Through use of real-time data, examination of trends or historical data patterns, the decision-making process becomes fast, more reliable, and secures greater confidence from all the parties involved.

4. Greater competitive advantage occurs as tools and technologies improve to support data collection and analysis, and the people involved acquire the capability necessary to sustainably implement data-driven decisions.

5. Greater responsiveness and line-of-sight on the customer experience. Simply stated, data allows organisations to identify customers, their demographics, their needs, how they want to engage in a customer journey, and if they are satisfied with the customer experience.

6. Promotion of agility through a virtuous circle of data feedback whereby data-driven decisions trigger data and feedback that help the organisation develop new and improved products, services, and ways to raise the customer experience.


Robyn Collinge (April 2020). How to gather and use customer insights to improve experience, Blog, HubSpot.


How do you create a data strategy | 9:38 mins

  • Can you identify a problem that could usefully be moved through a systematic DDDM process?
  • How could data collection and processing be better aligned to decisions or problem-solving priorities in your operational area or organisation?
  • What are some of the most obvious risks to your organisation of not being able to access data required to make decisions at speed and with greater accuracy?


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