AI Enabled Decisions for Consumer Goods Companies
Since time immemorial, businesses have learnt from past experiences – be it from mistakes or successes as both are equally important to learn from. Equally important is to keep ears and eyes open on what is happening around you and how it may impact your business as well as your consumers. What if companies have intelligent systems (AI systems) in place that keep a close watch on real time happenings, socioeconomic environment, and top of all that, learn from past behavior and automate business decisions that are more accurate and timely? If that happens your computer network will mean more to you than your most trusted business partner.
Why companies should invest in these intelligent systems?
Businesses are undergoing a lot of challenges due to rapid changes in consumer dynamics as well as increased competition. To survive in an excessively dynamic and competitive environment, companies should continuously learn and respond to current market trends, consumer behavior in real time. AI systems gather a deep understanding of a subject by mining enormous past and present data with cognitive intelligence, thereby helping companies making impactful decisions. There is no doubt that AI enabled decisions have the potential to make businesses more competitive, more profitable, more efficient and so on. Companies should prioritize areas to implement these capabilities in different parts of their organizations to maximize value of these investments.
Typically, businesses have 3 types of external (Outside-In perspective) stakeholders and AI can impact all 3 areas. Here’s how:
1. End consumers (B2B2C) – Consumer Goods companies can now anticipate their needs and suggest products/ services at a time the consumer is most likely to buy
2. Buyers (B2B) - Anticipate your buyer’s stock outs, delays in delivery and suggest alternate products and even get proactive on offering product warranty support for repairs and replacements.
3. Employees (B2E) – Employees of a Consumer Goods company can just use their AI powered internal network to swap shifts for store coordinators based on their skills and supervisor’s requirements
Even internal stakeholders with an Inside-Out perspective can make use of AI system. These stakeholders are typically the chief management officers. Let me illustrate:
A CEO can use an AI powered system to demand predictions and plan for warehouse inventory storage all the while identifying new markets of penetration for a product. A CTO can look decide when or if at all automated chat bots can improve organizational or revenue generating efficiency, and a CFO can identify more accurately which client is most credit worthy and even monitor fraud and anomalies in vendor payments.
Such examples give only a taste of AI applications at a Consumer Goods company to inject decisions with some sense that is human error-free. This is indeed possible because AI systems are designed to give out decisions post analyzing behaviors with diverse data sets lying within and outside an organization. The analysis incorporates elements of Machine Learning (ML – to learn human behavior over time), Natural Language Processing (NLP – to extract meaning from natural languages) and other niche capabilities useful for human like comprehension of data for enabling decisions..
