Significant hurdles leaders face this year include managing talent, formulating strategies, operational plans, and organizing employee tasks in ways that ensure everyone accesses growth opportunities. These challenges emphasize the importance of good strategy, and are essential for organizational survival.
Vijay Pereira, Professor and head of department of people and organizations, at NEOMA Business School in France, believes artificial intelligence (AI) can help leaders undertake these challenges. For example, his recent work concludes that evolutionary computation and data mining can explore large databases or social media to locate potential talented individuals for recruitment purposes. In addition, machine learning helps reanalyze and recognize patterns from data collected from existing decision support systems to help organizations improve their strategic planning processes. Pereira consequently believes that AI reduces the cost of reassigning and reorganizing tasks, allowing for more efficient dynamic optimization of organizational functions in response to changing conditions.
This is important because customer experiences providing a hybrid of digital interfaces and tangible interactions are becoming increasingly popular. Consequently, while this benefits the end-consumer, many leaders need a better strategy to plan for and measure success. AI can help. In fact, according to Pereira, AI can simulate and quantify outcomes of each strategy and help leaders discover better ones in their respective industries. Still, there are many misconceptions about its power – so here’s what you need to know.
Customer experiences providing a hybrid of digital interfaces and tangible interactions are becoming … [+]
Predictability of behavior
Advancing operations and facilitating ever-more creative consumer experiences appear to be two significant trends for 2022. As people become more accustomed to the metaverse, personalized online shopping experiences, and curated targeted ads, organizations’ use of category management tools is rising. Category management can accurately predict sales based on tracked behavior patterns fuelled by machine learning. Seemingly out of reach in recent years, because complex product assortment strategies are now easily assessed by new technology, leaders can today shrink that category relay process and more quickly act on intelligent forecasts that generate recommendations with precision and within minutes.
Such insight can be advantageous for leaders in many verticals, particularly those in retail, because far from dead, the sector continues to be the financial backbone of world economies. Consequently, as retailers employ new technology, sales will continue to grow. According to Pereira, leaders of firms who earn their spot on top will recognize the power of data-driven insights and AI-fueled tech to create elite, personalized, and efficient customer experiences that offer the right products at the right time to the right people. That recipe is possible when using machine-learning approaches like HIVERY Curate, which seeks to use hyper-localized product and space recommendations and usher in a new age of actionable insight through strategy simulations – a sort of “Know Before You Act.” For example, AI allows retailers and Consumer Packaged Goods (CPG) manufacturers to quantify the potential outcome of any assortment decision before being implemented on shelves. “The smartest in the industry are leveraging AI-powered solutions to run assortment strategy simulations to find the best assortment strategy to execute in a retail store,” agrees Ashish Malik, Associate Professor at Newcastle Business School in Australia.
Bypassing human bias
Millions of retail transactions happen in-person in a variety of contexts every day. Trade promotion management (TPM) and trade promotion optimization (TPO) are vital activities that empower business leaders to know when, where, and how to promote products, for example. But, of course, the timing must be just right, and trade promotion calendars are often planned months in advance. Imagine if those could be designed with greater accuracy, informed by historical trends and forecasts that enhance each sales cycle and deliver more consistent revenues. That is what emerging technology is capable of doing, striking the right balance of promotion consistency and bypassing human bias. Taking data from diverse sources and aggregating it into meaningful insights is what systems such as the HIVERY Trade Promotion Optimization tool achieve.
Four founders of the data-management platform Hivery
With commercial real estate in high demand, and a need to minimize expensive overhead, retail leaders have to get smarter about maximizing every square foot of space in a store. This happens on a macro level, with store-wide space allocation, and on a micro-level, with by-shelf planning. Both are essential to achieving an optimal, comprehensive customer experience with the best chance of generating high revenues. Historically, each process has been meticulously scrutinized and carefully planned using manual methods based on historical data. But any leader recognizes that this is inadequate, and, often, an understanding of what customers will do has come too late. Art and science need to be activated, which is met in a combination of artificial and human intelligence as a collaborative augmented team. In fact, premier global market intelligence firm, IDC, found that 65% of retailers now say AI is essential for merchandise analytics, and 54% of them cite that improving ecosystem collaboration with suppliers is a top priority, IDC is seeing the emergence of Next Generations (“Next-Gen”) merchandising solutions. Current, on-demand data can inform the brightest human ideas, ensuring that what is implemented is not only relevant but as future-proof as possible. This means augmenting strategic decisions in minutes, not months. Decisions to everything from store assortment and space mix, layout, to shelf design gets a boost when the right technology fuels these insights and decision-making processes.
Pereira reiterates that organizational challenges such as these are a leader’s principal responsibility, therefore serving as drivers for using AI in operational and strategic planning areas when formulating more effective talent management strategies, succession plans, staffing plans, and in organizing employee tasks more effectively across the organization.
Pereira further reiterates that post 2022, AI will be the cornerstone of industry 4.0 as it is widely acknowledged that the use of human and machine intelligence will bring a new level of augmenting and a radical change, especially the way organizations function and tasks are executed in the future. AI is already envisioned to optimize production and its associated processes through robot-based smart manufacturing lines, intelligent scheduling systems, and advanced strategy simulation capabilities and can help leaders solve a variety of complex retail, engineering, and financial problems within organizations in the near future.
Therefore, the critical question is, are leaders ready and proactive for the future, given the power that AI can provide to propel the global economy in 2022 and beyond?