Business Sustainability: Artificial Intelligence and Machine Learning (AI and ML) is Not Enough

Proshare

Saturday, December 11, 2021 / 02:00 PM / Teslim Shitta-Bey, CE/ME, Proshare / Header Image Credit:  Simplilearn

 

Technology is not a substitute for products or services but it does provide the variables needed to design the character, texture, and context for the next business success story, the next winning product, or the next market-disrupting service. Artificial intelligence (AI) and machine learning (ML) will not create consumers' reality but they will provide the data and algorithms needed to understand consumer sentiment and initiate a process of inquiry and product design that ultimately delivers on consumer expectations

 

Corporations must, therefore, learn to ramp up their data gathering, mining, and analytics skills. However data is not enough, organisations must know how to use it. Several businesses gather massive amounts of data routinely but fail to use the data to refine their product or service offerings. The nuggets of consumer preferences and expectations buried in the zeros and ones of complex corporate algorithms must find expression in services and products aligned to the customer's pains and desires. If a business is to remain in the land of the living, it cannot afford to forage in the graveyard of the dead.

 

A corporation's longevity will depend on how it uses contemporary consumer data to understand underlying customer sentiments and build an agile and responsive product or service pipeline that lives in customers' imagination rather than their memory.



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Strategy on Steroids

The corporate survival strategy will be digital over the next half-decade but to take advantage of the business transformation and technology adoption processes companies will need to look beyond algorithms to customer perception and user experience journeys and engineer products and services to be fit for consumer purpose.

 

In addition, companies will need to scale technology adoption and worker adaptability. If a company adopts technology nut its staffers are lagging in the ability to use the technology, the service and product delivery propositions fail. Agile companies need to ensure that technology adoption is matched by worker adaptability (see illustration 1 below).


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Technology would need to be supported by fresh thinking and a different approach to tasks and responsibilities. The shift to predominantly digital platforms for work would mean that workers will have to have a mastery of both the tool (laptop or desktop) and the software that carry out the assignments involving big data analytics, infographics, dynamic dashboard scenario analysis, and decision-making templates using R or Python programmes. Of course, other analytical and statistical programming techniques could be used for strategic corporate decision-making such as e-views and SPSS for economic analysis but workers will be required to have more than a casual understanding of these tools. At the centre of tomorrow's workspace is data and employees will need to adapt to the requirements of a data-soaked business landscape.

 

Admittedly in the short-term, traditional business practices and 'old school' factory operations will still have a place in emerging markets (EMs) like Nigeria, but the shelf life of these enterprises continue to grow shorter by the day as competitiveness requires companies to dominate uncontested markets. At the heart of the emerging competitive landscape would be the capacity of organisations to process data speedily, accurately, and cleanly to meet customer journey experience (see illustration 2 below).

 

 

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It bears repeating that as much as technology is important and artificial intelligence (AI) and machine learning (ML) will separate corporate losers from winners over the coming decade, a human capital upgrade is critical to any strategic corporate remake. Companies must be intentional in their recruitment strategies for bringing in new workers as the emerging requirements of competitive advantage is not only to meet the needs of existing customers but also to provide solutions to the challenges of the customers of tomorrow or perhaps those of old customers with new needs. The new workplace and worker must be forward rather than backward-looking.

 

Questions that may need answering include:

  • What is the nature of tomorrow's markets and their dominant customers?
  • What are the primary and unique characteristics of these customers (progressive, conservative, risk-averse, risk-taking, risk-neutral, digital natives, digital immigrants)?
  • What demography do they fit into?
  • Why will tomorrow's customers buy a good or service, and what product or service gap must be filled?
  • When will the customer's new experiential journey start, and why?
  • Can companies discern future shifts from present spending behaviour?
  • How can technology support a faster route-to-market?
  • Is there an alignment between internal corporate processes and the future desires or needs of customers?

 

Organisations in the post-COVID-19 economy must make efforts at aligning people, processes, and strategy.  The implication is that while AI/ML brings a springiness to the steps of corporations, achieving sustainability requires that they improve worker adaptability in addition to technology adoption.

 

Some companies have spent tidy sums on technology adoption but the staff is yet to build a new culture around the acquired technologies to improve their service delivery speed or product quality promise. Without upscaling human capital, technology adoption may become an impotent part of corporate transformation.

 

Thinking Change

To embed technology into corporate culture requires new thinking and this starts from the top. CEOs must be role models and guide the process of thought towards customer-centric approaches to resolving tentative problems or satisfying transient expectations. The leader must build conviction in his colleagues and guide a shared vision of corporate progress that dovetails into personal growth.

 

In doing this the organization must become a melting pot of clever ideas and agile skills mixed in new and exciting ways to create value. Workers must see the corporate vision melt into personal aspirations and expectations. If a culture of personal growth and creative license is reinforced by the removal of stereotype corporate barriers fostered by conservative concepts of hierarchy, then sustainability becomes an attainable digital vision (see illustration 3 below).



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Leading Change

Leadership and execution are crucial components of strategies if companies are to survive the expected disruptions of the decade. Chief Executive Officer (CEO) of the Stack Centre, Dr, Ayotunde Coker, at an Institute of Directors (IoD) Nigeria conference in 2020 noted that for companies to take full advantage of technological disruption, "The issue is leadership". According to the tech specialist "leadership must continually upscale itself and rethink the corporate purpose against shifting realities. Leadership is knowing when to reinvent yourself. Leadership must open its mind up to the possibilities of technology". He observed that, "It is important to understand the context in which you are operating in, you either shape the context or walk into the context because if you do not do either, you die as a CEO or get replaced or go down taking your company with you"




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AI/ML in 2022

The race for the consumer will intensify in 2022 and with the Omicron variant of COVID-19 ravaging countries and continents the digital world will give meaning to Facebook's love for the concept of a metaverse and its decision to change its parent companies name to 'Meta' in 2021.


The new software-aided consumer journey experience will improve the pleasure users derive from products and services (meaning interactivity will improve functionality and design) and separate corporate slouches from their faster and smarter contemporaries. The race for AI/ML dominance has already started in Nigeria's financial services industry with deposit money banks going toe-to-toe to ease the customer's journey experiences through chatbots that enable customer inquiries to be treated digitally (see illustration 4 below of Nigerian banks with chatbots).


 

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While the AI/ML rat race has begun, it is still at its first lazy mile of a corporate marathon, with banking halls and customer care units still inundated with customers' physical inquiries and support requests. The digital banking interfaces of Nigeria's tier 1 banks are still relatively unintuitive and involve discomforting repetition of online processing procedures.

 

That being said, 2022 will see banks and other non-bank institutions intensify their use of big data and consumer data analytics to upgrade service speed and product delivery quality. The problem is that while AI/ML will give insights into how consumers behave, it will not interpret why they behave that way, this would require the intellect of an analyst or group of analysts who would look at the social, political, economic, technological and environmental convergences occurring that give rise to consumer actions. By 2022 understanding consumer behaviour and preferences will become increasingly important as younger customer demographies throw out the loyalty playbook and impose a higher burden of performance on businesses.



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Breaking Bad

Throwing out the loyalty playbook will be part of consumers' efforts at breaking bad corporate practices. Regardless of how well AI/ML performs, they can only improve the customer journey experience if the right corporate culture is in place, AI/ML complement healthy corporate cultures, they do not replace them.

  

AI/ML will reposition organisations in 2022 (including Proshare) but the effectiveness of advanced technology applications will depend on the quality of the people that adopt and adapt to these technologies. A snappy and offensive front desk officer does not get pardoned by a beautiful service delivery algorithm he or she does not understand or is not prepared to use. Also, customer service queues and complaints will not disappear if the backend technical personnel are sloppy, lazy, or simply incompetent. 

 

To ride the crest of a new digital service or product delivery order in 2022, corporate personnel must step up their games and be comfortable with a revised culture of sustained service excellence.  Being customer-centric is no more a fad but a creed. To be sure, future-facing companies know that at the heart of their bottom lines is their customers and their purse or wallet.  

 

EndNote

So far, mainly two banks appear to be at the forefront of AI/ML applications to retail service delivery; UBA with Leo and Zenith Bank with Ziva, other banks appear to be dipping their toes into the AI customer service pool without strong conviction.  Other banks do, however, show strong digital revenues, especially the tier 1 banks described as FUGAZE (FBNH, UBA, GTCO, Access Bank, Zenith Bank and ETI) despite a modest attempt at customer-centric service delivery through AI/ML (see table 1 below).


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Does AI have such a strategic importance to meeting customers service or product delivery expectations? Certainly. In a recent survey consuducted by McKinsey, a global consulting organization, the analysts noted that  "The results of our latest McKinsey Global Survey on AI indicate that AI adoption continues to grow and that the benefits remain significant-though in the COVID-19 pandemic's first year, they were felt more strongly on the costsavings front than the top line. As AI's use in business becomes more common, the tools and best practices to make the most out of AI have also become more sophisticated".

 

The report further observes that "AI adoption is continuing its steady rise: 56 percent of all respondents report adoption in at least one function, up from 50 percent in 2020. The newest results suggest that AI adoption since last year has increased most at companies headquartered in emerging economies, which includes China, the Middle East and North Africa: 57 percent of respondents report adoption, up from 45 percent in 2020. And across regions, the adoption rate is highest at Indian companies, followed closely by those in Asia-Pacific".

 

Nigerian companies that want to excel in 2022 must adopt increasingly more sophisticated levels of AI adoption and adaptation but this must be done with effort addressed towards retooling and upgrading existing worker skills. Sustainability going forward will be more complex than in the past and as Daniel Craig's last James Bond movie noted, for agile companies focused on meeting customer needs this is 'No Time to Die'.



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Proshare Nigeria Pvt. Ltd.

 

Proshare Nigeria Pvt. Ltd.

 

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