The new and improved FMCG sector – now with the power of AI
Technology has for long been playing a key role in delivering a competitive edge for FMCG companies. Many companies are already reaping the benefits of digital transformation initiatives, some nascent and others comprehensive. In that light, it’s interesting to see how Artificial Intelligence is unlocking huge benefits for FMCG companies by bringing in more efficiency as well as effectiveness in several business functions. It’s also clear that the Global FMCG/CPG ecosystem is also fast awakening to the growing AI opportunity.
AI can help FMCG companies get predictive insights into customer behaviour, deliver a better consumer experience, and facilitate superior engagement. AI also enables a great deal of automation in business processes that can help reduce costs and save time. An IBM survey found that retail and brand executives expect intelligent automation capabilities to help reduce operating costs by an average of up to 7%.
Acknowledged benefits of applying AI
- Fewer errors, more accuracy
AI works on past data to suggest recommended paths of action. It identifies duplication of efforts, reduces errors, and helps to fix them to arrive at better-directed actions.
- Round the clock support
Using AI technology, companies can program a virtual assistant or a chatbot that can help address customer queries round the clock. Conversational AI is in demand because it also elevates the customer experience.
- Automation of mundane tasks
AI can be greatly leveraged to automate manual repetitive tasks that can be simplified with the help of technology. This provides teams with more time to focus on other important issues.
- Improved decision-making
With deep learning AI tools, companies can get meaningful insights into various business parameters. This enables them to make better decisions based on factual data.
How AI can transform the FMCG sector?
FMCG companies stand to benefit greatly by embracing the advancements in data-driven technologies like AI, ML, and deep learning. By adopting such cutting-edge technology in the fast-moving consumer goods industry, companies can make the supply chain more efficient, have better inventory management, and achieve more accurate demand forecasting.
Let’s look at them one by one:
Supply Chain Optimization
For FMCG companies an efficient supply chain is extremely crucial to ensure accurate demand fulfilment, healthy profits, and business growth. With AI technology companies can get better visibility into their supply chain operations identifying areas where they can cut costs, improve efficiency, and enhance service levels. By mining insights from data with machine learning algorithms, companies can identify operational inefficiencies and optimize operations further. AI can help in arresting inefficiencies in the production schedule, manage delivery ETAs, as well as pinpoint frauds in the system. All of this can have a great impact on business profitability.
Demand Forecasting and Inventory Management
Having a pulse on customer demographics unleashes a world of opportunity for companies. AI helps in collating and analyzing all the critical customer data points. Interpreting the rich customer data sets with the help of machine learning and deep learning algorithms helps companies in their demand forecasting strategies. Companies can then act suitably to meet customer demand in the best way possible. For example, this could mean how to arrive at best ways to cater to the demand coming in from the rural areas and creating communications and messaging strategies aligned to those changing realities. This also enables companies in maintaining the desired inventory based on demand-gap analytics. Inventory management for FMCG companies can become a massive optimization challenge. With the help of AI technology, this can be streamlined to a great extent.
Personalized Consumer Experiences
Companies can use AI to transform their customer experience and make it extraordinary. How? By changing it from being reactive to proactive to even predictive. This is the new paradigm of customer service opening up for FMCG companies. Companies can utilize customer data and insights to curate proactive customer experiences. This means providing customers with all the help and guidance they need on their purchase decisions, even before they ask for it. Having access to vast pools of customer data helps in identifying demand patterns, which in turn helps in cross-selling or up-selling with the help of personalized recommendations. Using AI tools, intelligent customer engagement can be achieved in real-time. When driven by insights that help the customer address real needs better, this adds tremendous value to the brand appeal.
IBM provides a solution that allows operations, supply-chain, sales, product, manufacturing and finance teams to collaborate to create plans in minutes instead of days and get the best product mix and production quantities for the right location at the right time.
This solution also allows data scientists to work together in an integrated development environment to quickly build optimization and forecast models using their method of choice, test and evaluate multiple scenarios to assess impact before production, and quickly deploy models so business users can access models directly from the planning tool and get immediate results.
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In Conclusion
There are a lot of correlations and patterns hidden in the way consumer demand fluctuates. For FMCG companies, this is a goldmine of valuable information that needs to be processed to reveal strategies that can deliver a competitive edge to their business. How to place their product, which products to push or stock, which workflows to change or optimize, how to segment marketing spend, how to price, or when to launch offers, there is so much to plan and streamline in the FMCG landscape. All of this can be done effectively by utilizing advanced tools and algorithms. It’s in that context that more and more FMCG companies are leveraging AI-led automation to redefine their consumer experience and brand engagement.
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