Structured Uncertainty – An Approach for Enterprise Transformation in the Age of AI

Why Is Enterprise Reimagining Essential?

Many leaders fully understand the transformational impact of AI on business models and businesses. Other leaders may not. And few workers do. Why? Because like anything huge, hairy, and nebulous, it’s easy to talk about conceptually, but more difficult to make real and tangible.

So, let’s get concrete. It’s essential that every American—every leader, worker, student, and citizen—understands just How Big this thing is.

My primary goal is not to ignite fear but to reduce the uncertainty, apathy, and ignorance surrounding AI and the Future of Work, which I wrote about recently. (You can read about that here.) My secondary goal is to provide high-leverage practices and tools—immediate actions—enterprise leaders can take as you begin to embark on reimagining your business in the age of AI. These tools will aid you in thoughtfully and strategically guiding your transformation activities ahead, while supporting and advancing your workforce.

So, let’s pull up 30,000 feet and take a peek at how AI could potentially transform, for example, the value chain of the consumer goods sector, which includes manufacturing, service, and packaging businesses. “Value chain,” for those who may not be familiar, refers to the series of steps that go into the creation of a finished product, from its initial design to its arrival at a customer’s door. For consumer goods, the process, at the highest level, looks like this:

1. R&D and Innovation
2. Manufacturing
3. Marketing
4. Online and In-Store
5. Payment
6. Distribution and Logistics
7. After-Sales/Support

If we look at the areas of business that are being transformed by various AI technologies aligned with our high-level value chain (see detailed list at the end of this article), we see that AI plays a transformational role across the entire process.

But organizationally, we can’t stop at the value chain. There are other areas where AI blows up businesses and business processes as we know them—e.g., supply chain is one additional area. Then there’s the business platform where data centralization is the key theme. Finally, we must consider AI’s impact on the business ecosystem, which has, in large part, replaced the more simplified value chain. The ecosystem refers to the network of organizations involved in the delivery of value to enterprise customers and extends beyond traditional suppliers and customers to government and regulatory bodies, investors, trade associations, unions, and more.

See how big this is?

Leveraging AI technologies necessitates not merely the surgical transformation initiatives of days past but a total reimagining of the enterprise.

And while there’s nothing that gets me jazzed more than rooting out pesky inefficiencies and redundancies to yield extraordinary cost savings, the impact on jobs —on human lives—is not lost on me. Nor should it be lost on you. If we carve out one chunk of the value chain and but one subprocess within it, we’re talking potentially hundreds or thousands of (human) jobs that will be either eliminated or modified in some way, or new jobs that will be created to align with the new “teched-up” infrastructure.

Managing the Change for our Workers

Change is inevitable. And so is the impact to workers’ lives. How can we manage the transition more effectively?

If you follow my Workplace Stress + Innovation Newsletter (here), you know that EWING are experts at the intersection of workplace stress, innovation, and performance with distinctive expertise in organizational environments that go sour when the (change) pressure exceeds the environmental and human capacity for change and/or the change management practices are insufficient, ineffective, and/or poorly managed.

Our experience has shown that the overarching “temperature” of workplace environments can escalate swiftly from normal to high to crisis-state stress levels—where unsavory or damaging fear-based worker behaviors arise—if we don’t stay on top of things to understand when shifts are underway, as well as the drivers behind those shifts.

As enterprises race to transform through AI, it’s imperative that we get ahead of potential workplace environment, people, and change management process issues that can stymie even the smallest of change initiatives.

Where to Start the Reimagining Process?

The EWING Approach to Structuring Uncertainty

The Big Vision – Strategy Development

Change and transformation will not happen without a Big Vision. Cost-cutting with technology is not a Big Vision. Enterprises don’t grow by shrinking themselves via cost-cutting measures, however monumental; they grow by creating compelling value that markets and customers want.

A Big Vision is essential for superior market performance and longevity. The EWING approach to strategy development has four components. And while these four areas are initially shaped during the strategic planning process, they should be ongoing activities. Periodic “pressure testing” against the market and customer enables market-driven adjustments. (Caveat: beware of losing focus with every minor market shift.)

1. Strategic Landscape/Opportunity Assessment—This includes intelligence gathering, but it is more strategic and broader in scope. AI can assist with this process but the truly differentiated, breakthrough enterprise vision and strategy you’re looking for your business comes from human minds.
2. Capability Strategy—Strategic wishing doesn’t yield results; strategic planning does. A true plan must include how current capabilities will be leveraged to achieve specific end goals;  a roadmap from "now" to "next," and a plan to develop new capabilities essential to attain the Big Vision of your enterprise’s future.
3. Culture and Workplace Environment Strategy—What core values will carry us forward to our future? What may we need to replace or refresh? What is the envisioned workplace environment than will enable our workers to innovate, collaborate, and produce extraordinary results? What is the baseline “temperature” or overarching workplace stress level of our organization now? What variables are elevating stress and impacting worker interactions and outcomes today that we can adjust to optimize for our future? What is the plan for creating the optimum culture and workplace environment that will allow us to compete for talent and achieve market success?
4. Strategic Financial Management— This is not budgeting to the current year’s goals; this is a multiyear assessment of investments that are required to create growth, build the organization capabilities, and tech up the strategies enabling efficiency and cost optimization that will make your enterprise the market leader.

Set the Stage for Success with High-Leverage Practices and Tools

There are other things that you can be doing now to set the foundation for future success – including setting your people up for success – and to provide a framework and guardrails for the reimagining process. At EWING, we’re centered on Transformations that Work, and here’s a few of our tools you can take advantage of right now:

4 Essentials to a Change-Capable Workforce – Workshop for Executives

To fully realize the value of change we need everyone in the organization to see themselves as part of change and change as part of themselves.

What is a “Change-Capable Workforce?” Workers that possess the requisite skillset, mindset, and intention to embrace the uncertainty enveloping them during times of transformation to forge a path – your organization’s desired path - through it anyway to deliver results.

In our customized session, we outline the attributes workers must possess to enable organization-wide change capability and agility, the requisite mindset and skillsets that underscore each attribute and share different ways you can introduce the attributes to your workforce based on its composition.

It's worth noting that the same attributes that lead to a change-capable workforce also lead to a culture of product discovery/innovation.

Workplace Stress Diagnostic Tool

We’re not in the industrial age anymore; we’re in the information age. Excluding workplace violence (which, by the way, is exacerbated in high stress environments), threats against employees’ physical safety are not the critical issue of our time. The issue of our time is threats against workers’ emotional health and safety.

We know, from three decades in the field, that in environments experiencing massive change (like the kind of change AI will drive ahead) worker fear is real. Fear fundamentally changes organizational environments and human behavior (not in a good way.) 

As leaders, we need to understand the “temperature” of our organizational environment before we embark on driving monumental change so we can anticipate and circumvent fear-based behaviors before they occur.

EWING’s proprietary Workplace Stress Diagnostic helps you gain not just the critical baseline understanding you need about your environment and stress drivers today, but tangible, actionable steps to begin to shape your environment to support your people during the business reimagination ahead. 

The Change Management Landscape: A Framework for Transformations That Work

Getting innovation and transformation “right” necessitates defining vision and synchronizing strategy and cylinder movement. EWING’s Change Management Landscape Framework helps leaders shift their orientation to think bigger and differently about their future vision while providing them with a structured “lay of the land” to understand the gaps to get there and articulate and operationalize the process and plans to do so. It does this by breaking down the transformational terrain into bite-sized chunks to make a monumental effort both structured and digestible.

Enterprise Software

Our patented technology solutions are designed to help enterprises and individual workers manage and optimize workplace stress levels and individual stress levels for high performance and successful business outcomes.

EWING helps enterprises reimagine their business and realize transformations that work via consulting and proprietary training, methods, research, frameworks, tools, and technology. We work with you and your partner selected to “tech up” your enterprise by providing specialty services and software solutions.

Let us help you realize your transformation.

Kristen Heimerl | EWING Innovation | Kristen@GrowWithEwingco.com

Consumer Goods Sector Value Chain—AI Impact Illustration

ONE - R&D AND INNOVATION

• Business Intelligence - e.g., interpreting large volumes of data that helps executives, managers and workers make informed business decisions.
• Strategic Sourcing - e.g., new product attribute and ingredient analysis to aid in sourcing (sustainable, ethical, cost-effective, market and consumer aligned.)
• Market and Consumer Insight - e.g., analysis, trend predictions, and forecasting to isolate opportunities and reduce time to market.
• Product Formulation and Testing - e.g., data analysis to assist with formulating and testing new products and their impact on humans.

TWO - MANUFACTURING

• Quality Assurance - e.g., image and video interpretation for quality control.
• Raw Material Optimization - e.g., predicting the weight of raw materials pre-production.
• Packaging Processes - e.g., computer vision (CV) implementation across factories to automate packaging processes.
• Equipment Optimization - e.g., Predictive maintenance models to reduce machine downtime.
• Smart Robots and Motion Control Sensors -  e.g., to transform many aspects of manufacturing and distribution.
• Smart Managers/Analysts - e.g., analysis of thousands of data points to optimize operations and reduce costs such as driver scheduling, predicting preparation and delivery times, and suggesting real-time operational improvements.
• Inventory Automation - e.g., use of predicted demand to reduce waste, CV driven quality assurance to reduce mistakes, optimizing staffing.
• Waste Reduction - e.g., help farmers improve their environmental footprint, improve yields, and reduce water and fertilizer use. AI-enabled tools in foodservice that take photos and weigh discarded food, helping kitchens measure, monitor, and reduce food waste.
• Maintenance Scheduling - e.g., sensors to monitor machines and other equipment to predict when maintenance is required to reduce energy consumption and cost of maintenance.
• Recycling Process Automation - e.g., robotic systems to automate the recycling process by recognizing patterns in materials and communicating with robotic arms that sort material based on those characteristics.
• Demand-Based Supply Chain - e.g., predictive analytics to predict the supply needed based on consumer interest and sales figures.
• Inventory Monitoring - e.g., ongoing and during the phase in and out of products.
• Supply Chain Visibility - e.g., creating a digital model of the value chain and using predictive analytics improve forecasting, monitor quality, and track the movement of ingredients.
• Identification of Production Line Anomalies - e.g., analysis to identify anomalies or patterns for detection of hazards or prevention of dangerous incidents; to notice patterns of a machine malfunctioning and alert when replacement is needed.

THREE - MARKETING

• New Product Development - e.g., predictive and behavioral analytics models to curate new product offerings based on emerging customer needs. AI technologies play across the NPD process including product curation, packaging design, and marketing campaign creation.
• Marketing Campaigns - e.g., create campaign content and visuals; targeting to specific audiences.
• Content Development - e.g., generate audio, text, or images for communications and promotions. More broadly, press release writing, contract drafting, sales proposal creating, budget drafting, and customer service.
• Business, Market, and Consumer Intelligence - e.g., aid with interpreting data in business intelligence to make informed decisions.
• Improve Brand Experience - e.g., simplify data analysis to improve and optimize multiple customer touchpoints.
• Curate New Product Offerings - e.g., data and online content analysis to curate new product offerings based on customer preferences.
• One to One Marketing - e.g., use of customer data to personalize shopping experiences, make product recommendations, and create targeted ads in real-time.

FOUR - ONLINE AND IN-STORE

• Online Consumer Experience - e.g., conversational platforms to improve online experiences, customer service, and after-sales support.
• Fraud Detection - e.g., AI algorithms to detect fraud in payment procedures and determine customer suitability in buy now, pay later programs.
• Personalize Shopping Experiences- e.g., use customer data to personalize shopping experiences and create targeted ads in real-time.
• Service Delivery - e.g., faster, and more streamlined service through automated processing/direct interaction with the consumer using a combination of AI platforms.

FIVE - DISTRIBUTION AND LOGISTICS

• Supply Chain Visibility - e.g., predictive analytics to provide end-to-end supply chain visibility for consumer, foodservice, and packaging companies.
• Optimize Distribution - e.g., predictive maintenance models are used in manufacturing and distribution to reduce machine downtime and optimize distribution schedules.
• Smart Robots, Motion Control Sensors, and Autonomous Vehicles (AVs) - e.g., increase transportation efficiency; eliminate human error and worker restrictions such as driver rests.

SIX - AFTER-SALES/SUPPORT

• Service Delivery - Chatbots - e.g., improve agent efficiency and productivity, make proactive recommendations, provide 24/7 customer service access (convenience), personalized support.
• Customer Satisfaction and Feedback - e.g., gather customer insights; NLP to analyze a customer interactions, understand sentiment and intent.
• Content Development - e.g., service interactions and spoken and written responses to customer inquiries.

SUPPORT PROCESSES

• Recruiting and Onboarding - Decision-making AI capabilities to automate and streamline recruitment and onboarding.
• Data Analysis Simplification / Automation of Repetitive Tasks - e.g., automating repetitive tasks across management, legal, and HR departments related to business intelligence. ML algorithms to assess the candidate fit;  conversational platforms to help answer candidate and new employee questions.
• Workplace Safety - e.g., AI-powered autonomous vehicles to improve long-haul and delivery driver safety; increase journey efficiency.

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