Change is inevitable. Change also makes planners lives, at best, complicated and, at worst, miserable. Plans are static and remain applicable only if the status quo doesn’t change — but change is unrelenting. Dwight D. Eisenhower once observed, “In preparing for battle I have always found that plans are useless, but planning is indispensable.” Jason M. Girzadas (@jgirzadas), a Managing Principal at Deloitte, seems to agree with Eisenhower. He asks, “Can leaders effectively formulate strategies in a world defined by disruption?”[1] He adds, “If there’s a single theme informing the C-suite’s most pressing challenges today, it’s the unrelenting pace and scale of change. Disruption continues unabated in virtually every sector and industry, making it difficult for organizations to feel confident in their long-term plans. Yet plan they must, or risk being disrupted themselves.” Both short- and long-term planning are affected by change and disruption.
Long-term planning
“No one can predict the future,” Girzadas asserts, “but today’s leaders can help shape it by understanding the long trajectories that connect it to the past — trajectories we continue to ride.” He agrees with Confucius, who once said: “Study the past if you would define the future.” When disruption not continuity is the chief characteristic of the business landscape, looking to the past might seem counter-intuitive. Girzadas points to three ongoing business trends, each of which builds upon historical precedents, to make his case about the importance of understanding the past in order to maximize benefits from future planning. Those historical trends are:
1. New tools to augment and automate human activities. According to Girzadas, “Humans have been developing new tools to work faster and make activities less labor-intensive ever since cave dwellers used sticks and stones to subdue dinner. Originally, the focus of innovation was manual work, and during the past half century we’ve created more advanced tools to undertake bigger and bigger portions of routine cognitive work. Today, however, we’re beginning to apply technology to nonroutine cognitive tasks. The tools may feel dramatically different, but the fundamental challenge still lies in understanding their application in a business context and envisioning how they can be used to deliver different outcomes.”
2. The decomposition and virtualization of the enterprise. Girzadas explains, “It used to be common for manufacturers to own every element of the supply chain — for example, Henry Ford owned sandpits as a source for the glass in his cars’ windows. Over time, that approach has been replaced by virtualization, specialization, and co-creation enabled by sophisticated supply chains. Today we’ve arrived at the next stage: ecosystems encompassing an increasingly complex web of actors competing, collaborating, and co-evolving over time.”
3. An increasing focus on customer-centricity. Girzadas writes, “Back when Ford was mining his own sand, he famously uttered the words that have come to epitomize the ‘before’ state of customer-centricity: ‘Any customer can have a car painted any color that he wants, so long as it is black.’ It was several decades before the mantra of business became ‘the customer is king.’ Companies have spent the intervening years sharpening their focus on customers, and today that’s come to include developing and communicating a larger social purpose. Whether it’s sustainability, diversity, fair trade, transparency, or another cause, consumers increasingly expect brands to pursue values beyond mere profitability.”
Girzadas concludes, “The organizations that will lead in the future are likely those that use the new tools to find ways to reinvent work, combining the capabilities of machines and people and tapping the best of both. They will be unafraid to embrace and make the most of ecosystems and be comfortable with the notion of losing some autonomy and direct control in the marketplace. At the same time, they will successfully convey and act consistently with a broader purpose and set of values.” Although he applies those three trends specifically to long-range planning, they are equally applicable to short-term planning.
Short-term planning
Short-term planning (sometimes referred to as demand planning) requires continual updating because conditions continually change. In the past, near-real-time updating of short-term plans was not possible. Cognitive technologies (i.e., those mentioned in Girzadas’ first trend) are now making near-real-time updating possible. Jörg Junghanns, Head of Europe Digital Supply Chain for Business Services at Capgemini, explains, “The advent of technology is allowing — and at the same time forcing — demand planning to become much more strategic. Digitalizing demand planning is becoming imperative for organizations that want to stay ahead of competitors, impress customers and drive company profits. Demand planning is no longer a case of simply reacting — instead, it requires continuous proactivity to successfully predict demand. In line with this, artificial intelligence (AI) is becoming an intrinsic part of the demand planning function, further boosting planning accuracy through sensing the markets’ desires.”[2] He adds, “Demand planners no longer need to dedicate large amounts of time to creating short-term demand plans or triggering stock replenishment — AI can do this for them.” Cognitive solutions, like the Enterra Supply Chain Intelligence System™, are augmenting human decision-making in ambiguous, changing, and anomalous situations and companies are finding such solutions very useful. As a result, reports David H. Deans (@dhdeans), a technology analyst and business consultant, “Global revenue from demand planning applications will generate over $8 billion by 2025, as Artificial Intelligence capabilities offered by forward-thinking IT vendors and service providers continue to improve data-driven supply chain transformation.”[3]
Cognitive solutions also play a role in Girzadas’ other two trends (i.e., complex supply chain ecosystems and customer-centric supply chains). Cognitive solutions can handle many more variables than previous analytic platforms and, as a result, can deal with the complexity found in today’s supply chains. Although data provides actionable insights for supply chain planners, Junghanns asserts it can occasionally obscure things as well. He explains, “With so much data readily available, it has become more difficult to detect customer purchasing patterns. Artificial intelligence can work to cut through this noise, processing the data to uncover subtle patterns that humans would have missed. By aggregating datasets from Enterprise Resource Planning (ERP), Customer Relationship Management (CRM) and Internet of Things (IoT) systems — and combining this with external variables and contextual data such as a calendar of events, seasonality and the weather — AI works to provide more accurate demand planning forecasts.” For example, the Enterra Shopper Marketing and Consumer Insights Intelligence System™ can leverage all types of consumer data to provide high-dimensional consumer, retailer, and marketing insights.
Concluding thoughts
I agree with Girzadas that no one can predict the future. Today’s roiling business environment presents an enormous challenge for supply chain planners. Nevertheless, Junghanns insists cognitive technologies can make these challenges more manageable. He writes, “AI forecasts can … be linked through supply and inventory planning to automate replenishment triggers, so that organizations consistently have the correct amount of products in stock. This results in increased sales by improving order fill rates and shelf availability.” Girzadas adds, “Rather than be indecisive in the face of uncertainty, leaders can [leverage cognitive technologies to] consider multiple possible future scenarios and plan their next steps accordingly.”
Footnotes
[1] Jason M. Girzadas, “3 Enduring Trends Inform Strategic Planning Efforts,” The Wall Street Journal, 25 April 2019.
[2] Jörg Junghanns, “How Digitalization – through automation and AI – is transforming demand planning,” Supply Chain Digital, 10 May 2019.
[3] David H. Deans, “How AI innovation is transforming supply chain planning, Telecoms, 23 April 2019.
