Modern businesses have many factors to juggle when it comes to building and maintaining success. As they vie for attention in an increasingly crowded marketplace, even product and service providers in niche industries are searching for ways to stand apart from the competition. Disruptive business models designed to challenge traditional wisdom and innovate smarter, more effective solutions are quickly becoming the norm.
In this article, we explore how AI and big data are being used to help fuel disruptive business models from talent acquisition to supply chain management.
Talent acquisition
Talent acquisition is arguably the most important aspect of building strong and successful businesses. AI and big data can help employers as they seek to develop effective workplaces in a variety of ways.
Enhanced recruitment
AI is especially useful in the talent acquisition process when tracking applicants during recruitment. For example, the notable entrepreneur and founder of Caliber, Martin van Blerk, uses AI for screening resumes, matching candidates with job descriptions, and scheduling interviews.
Big data also aids in the recruitment process. More specifically, it allows HR teams to analyze candidate data and predict job success. For example, predictive models driven by big data can use historical data to predict candidate performance and longevity with the company.
Improved employee retention
AI is helpful when analyzing employee feedback from a variety of sources such as job surveys to get a feel for employee engagement and morale. Identifying potential issues before they turn into actual problems allows management to keep workplaces running smoothly.
Big data is often used to analyze employee skills, historical job performance and career goals. This information is leveraged when creating personalized development plans to guide employees throughout their careers at a given company.
Customer experiences
Once they have a team of experienced, effective professionals behind them, businesses must refine their customer experience. AI and big data help personalize both marketing and customer service to keep customers happy.
Personalized marketing
Marketing has a huge impact on customer experiences, with personalized options often increasing satisfaction. AI is excellent for analyzing customer data to offer product recommendations. Amazon and Netflix both use AI for this purpose. According to a recent report, roughly 71% of consumers expect businesses to provide them with a personalized service. AI helps meet that demand.
Big data works hand in hand with AI in the marketing process. It is especially useful for aggregating large amounts of consumer data and offering marketers insights into their target audience. For example, future behavior and demand can be gleaned from these insights and used to create more targeted marketing approaches.
Tailored customer service
Few things have as significant an impact on the customer experience as customer service. AI can be used in the form of chatbots and personal assistants to provide instant responses to customer inquiries and needs. For example, beauty retailers might use AI to provide customers with tailored beauty recommendations without requiring them to speak to someone in person.
Customer feedback from in-store surveys, email questionnaires, online reviews and even social media mentions can be aggregated and analyzed using big data. This provides businesses with the insights they need to identify potential gaps in customer care and address issues promptly.
Operational efficiency
Even the best professionals and most effective marketing and customer service solutions can be stymied without optimized operational efficiency. Businesses use AI and big data to keep their inventory in check, guarantee reasonable wait times between customer orders and deliveries, and develop better products.
Optimized supply chain management
AI algorithms are often used in supply chain management to optimize routes and delivery schedules. This, in turn, cuts down on shipping times and associated costs. For example, DHL uses AI to improve logistics and overall shipping efficiency.
Assessing demand and maintaining inventory can have a major impact on navigating the supply chain for businesses in a wide range of industries. Big data offers analytics to help businesses accurately predict supply and demand. Walmart, for example, uses these analytics to analyze demand, order stock, and optimize transportation lanes and routes as the product moves from the dock to the store and from the store to the customer.
Data-driven product development
Production management systems powered by AI monitor production in real time. This allows businesses to not only detect defects on the fly and consistently deliver high-quality output, but also track usage habits. This information is then used to enhance predictive maintenance and refine features to best suit customer needs.
Big data also aids in product development. By analyzing large amounts of customer and market data, big data analytics can provide businesses with insights into their target audience’s needs. These insights are often united with AI algorithms to provide further analysis and identify gaps in the market.
AI and big data are crucial in business today
Big data and AI are quickly forming the core of the modern business landscape across many different industries. Businesses use disruptive models using both technologies to help grow and maintain success. From hiring talent to producing and shipping products, AI and big data are crucial elements of today’s best practices.
