Powering strategic development with AI and machine learning

By DataIQ | 12 December 2019 Email

The world is changing at an incredible pace and consumer preferences are more complex than they were 10 years ago. The next generation of consumers are far more fickle, experimental and granular than those that went before. This makes it harder for all businesses, and retailers in particular, to understand and predict their needs.

Until very recently, the tools available to deal with this explosion in data simply were not able to keep up. This is now at a tipping point - FMCG retailers and manufacturers are on track to invest over $20 billion in big data over the next three to five years. Last year, Walmart was third in technology spending, behind only Amazon and Alphabet.

Big data alone is not the answer

While the volume of data that is available now is greater than ever - and doubling every 14 to 18 months - it’s dealing with this in an effective way that is the challenge. To move faster and predict more accurately, businesses need to embrace new innovations in data analytics like artificial intelligence (AI) and machine learning (ML) which have the potential to revolutionise the industry.

By automating standard processes, it makes it possible for retailers and manufacturers to make smarter decisions faster and more effectively. In order to do this, AI needs to work on a data integration and management system, like the IRI Liquid Data® technology platform which makes it possible to integrate complex, multi-source data.

AI and ML systems can scour analytical databases at a speed and prowess that humans just can not match. The systems can point us in new and different directions while insights are generated in real-time.

The changing role of strategists

In 2016, Accenture released research which predicted that the impact of AI technologies would be to increase productivity by 40%. The way that this will be achieved is that the technology will take over a lot of the repetitive and predictable elements of people’s roles allowing them to work more efficiently or creatively.

Whereas the role of the strategist used to be about combing the data to find patterns, facts and uncover new truths, their role now is to ask the right question of the machine. AI and ML can significantly remove the churn part of the role, but they still need guiding.

Organisations now need to reinvent themselves in order to win at AI. This is perhaps the biggest challenge as cultural change is in many ways harder to achieve than technological. Strategists will need to have strategic business understanding as well as the science in order to unlock the truths which will enable their company to grow.

By embracing AI and ML, it makes it possible to democratise data - the systems do the technical element and make it possible to provide the actionable insight to the individual doing the job. In an FMCG business, for example, this could mean that the systems identify trends which could lead to an out-of-stock problem in specific stores and automatically send the alert to the account managers.

The account managers, without having to sift through reams of data, have the information they need to adjust stock volumes and so key sales opportunities are exploited rather than missed. These sorts of monitoring and alert processes can apply to any part of the business including crucial sales levers such as promotions and pricing.

The most successful companies in the future will be those which are able to develop a data-driven culture whereby data is a core part of the mindset and workflows of all employees. This will enable everyone to make better, faster decisions. AI and ML are applicable to every area of business and every department within it.

How AI and ML enable strategic development

Companies need to have a deep understanding of the consumer to guide their strategy and future direction. AI and ML are part of the toolkit for the strategist to achieve this, they elevate the strategic development process to an entirely different level. Their ability to search through a virtually unlimited number of digital sources makes them totally unique. Through ML, the system will continually fine tune itself so that it can evolve and create ever more focused and relevant results.

There are three high-priority areas that AI and ML can be used for which support strategic development among FMCG businesses:

  • Future scoping - looking at consumer behaviour, trend spotting, identifying innovation opportunities;
  • Operational - revenue management (for example, pricing and promotion), retailer collaboration, assortment and media;
  • Monitoring - automating insights, identifying out-of-stock and price gap issues, alerting to fast-moving items at a competitor.

AI and ML unlock opportunities that aren’t normally identified, and they anchor them in consumer and economic value. AI has the capacity to process the volume of conscious and non-conscious data that already exists.

People reveal important information about themselves every time they blog, tweet or search. Combining this with their non-conscious data, such as music and film preferences and other elements can help to predict future trends. This means that the innovation process can be completely reimagined and will move much more quickly than it could in the past.

AI and ML offer the opportunity to automate the most labour-intensive parts of data analysis. They have the power to transform data into useful information that enables better business decisions. While they are game-changers, the key point to remember is that they are tools - they serve us, not the other way around. Understanding how to get the best out of them is the challenge that all businesses now face.

Andrew Appel is president and chief executive officer, IRI. One of the original innovators in big data, IRI integrates the world’s largest set of otherwise disconnected purchase, media, social, causal and loyalty data to help CPG, retail, over-the-counter health care and media companies grow their businesses.

 

https://www.iriworldwide.com/en-SA/News/News

 

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