How Generative AI Will Change Sales

Thinking of testing this in the real world where enough data exists.  

How Generative AI Will Change Sales    by Prabhakant Sinha, Arun Shastri, and Sally E. Lorimer, March 31, 2023

Sales teams have typically not been early adopters of technology, but generative AI may be an exception to that. Sales work typically requires administrative work, routine interactions with clients, and management attention to tasks such as forecasting. AI can help do these tasks more quickly, which is why Microsoft and Salesforce have already rolled out sales-focused versions of this powerful tool.    close 

Last month, Microsoft fired a powerful salvo by launching Viva Sales, an application with embedded generative AI technology designed to help salespeople and sales managers draft tailored customer emails, get insights about customers and prospects, and generate recommendations and reminders. A few weeks later, Salesforce (the company) followed by launching Einstein GPT.

Sales, with its unstructured, highly variable, people-driven approach, has been a laggard behind functions such as finance, logistics, and marketing when it comes to utilizing digital technologies. But now, sales is primed to quickly become a leading adopter of generative AI — the form of artificial intelligence used by OpenAI (the company behind ChatGPT) and its competitors. AI-powered systems are on the way to becoming every salesperson’s (and every sales manager’s) indispensable digital assistant.

Sales is well-suited to the capabilities of generative AI models. Selling is interaction and transaction intensive, producing large volumes of data, including text from email chains, audio of phone conversations, and video of personal interactions. These are exactly the types of unstructured data the models are designed to work with. The creative and organic nature of selling creates immense opportunities for generative AI to interpret, learn, link, and customize.

But to realize the true potential, there are hurdles and challenges to overcome. Generative AI must be non-intrusively embedded into sales processes and operations so sales teams can naturally integrate the capabilities into their workflow. Generative AI sometimes draws wrong, biased, or inconsistent conclusions. Although the publicly accessible models are valuable (hundreds of millions of users like us have already used ChatGPT to query the knowledge base on practically every topic), the true power for sales teams comes when models are customized and fine-tuned on company-specific data and contexts. This can be expensive and requires scarce expertise, including people with significant knowledge of AI and sales. So how can sales organizations harvest the value without wasting energy on heading down unproductive pathways?

What’s Possible

Before addressing the how, consider what generative AI can do for sales organizations.

Reversing administrative creep. Almost every sales organization we touch is cursed with the gradual increase of administrative work over time. As selling complexity grows, so does the need for documentation, approvals, and compliance reporting. Unwittingly, the increasing use of sales technology is also a large factor. New technologies often lead to more training, more data entry, and more reports to peruse. Generative AI can reverse administrative creep, for example, by helping salespeople write emails, respond to proposal requests, organize notes, and automatically update CRM data.

Enhancing salespeople’s customer interactions. The use of AI in sales has been progressing of late. We have helped many companies deploy AI-powered systems that recommend personalized content and product offers, along with the best channel for salespeople to use to connect with customers. Recommendations are based on data about the preferences and behaviors of the customer and similar customers, as well as past interactions with the customer. Salespeople accept or reject the recommendations and can rate their quality to improve the algorithms.

By layering on generative AI, the models can produce better recommendations. One example would be considering customer sentiments gleaned from the nuances of language and subtle signals of customer interest or distrust — in emails, conversations with salespeople, posts on social media sites, and more. Further, the salesperson can collaborate with the system to improve recommendations in real-time. For example, after receiving a suggestion to approach a customer with a new offering, the salesperson can dig deeper — both vertically into the customer’s own needs and horizontally to find other customers who might benefit from the same offering. An interactive, conversational user interface makes the application easy to use. In a truly collaborative seller-buyer environment, even the buyer can be part of the dialog.

Assisting sales managers. Sales managers spend a lot of time studying reports and analytics on sales performance. Recently, most sales reports have progressed from passive, backward-looking documents to more interactive, diagnostics tools with drill-down capabilities. With generative AI, reporting systems can become even more powerful and forward-looking. Managers can pose questions to get insights for helping salespeople improve and for delivering more pointed and motivational coaching feedback. Sales planning tasks that took weeks can be performed in an hour, as managers dialog with the system to discover opportunities, formulate key account strategies, and determine how to allocate effort to geographies, customers, products, and activities. ... ' 

Summary.   

Sales teams have typically not been early adopters of technology, but generative AI may be an exception to that. Sales work typically requires administrative work, routine interactions with clients, and management attention to tasks such as forecasting. AI can help do these tasks more quickly, which is why Microsoft and Salesforce have already rolled out sales-focused versions of this powerful tool.close  ... ' 

Case for and Against Digital Employees

Business landscape is changing rapidly .I wonder how much HR typically knows about digital options, especially with the newly integrated chat capabilities.     And how can  those capabilities be enhanced  with key external specialty knowledge as well as internal knowledge?

The Case For and Against Digital Employees,  By Harvard Business Review  February 23, 2023  in CACM

Rapid progress in computer graphics, coupled with advances in artificial intelligence, is putting humanlike faces on chatbots and other computer-based interfaces. These digital humans mimic human communication as they offer a range of services.

When deployed at scale, digital humans will radically change the business landscape. They may not be as capable or versatile as human employees, but they have clear advantages when it comes to cost, customizability, and scalability. Once "hired," they never tire, never complain, never seek a raise, and always follow company policy.

Digital humans are already making real money for their employers. Within a decade, managers at most companies are likely to have a digital human as an assistant or an employee.

From Harvard Business Review

View Full Article 

Platforms vs Users

 Obviously, but worth a thought:

Platforms Need to Work with Their Users – Not Against Them

by Ethan Bueno de Mesquita and Andrew Hall, May 04, 2022  in HBR.org

As online platforms have become dominant, many have leveraged their power by raising fees and changing rules. In the short run, this hurts the producers they work with — software developers, small retailers, game designers, content creators. In the long run,...more

As we write, thousands of online communities created for a wide variety of purposes — everything from providing crypto financial services to crowdsourcing art collecting — are building new democracies rapidly evolving systems for discussion, debate, voting, and representation. This movement, often known as Web3, has created an explosion of interest in giving ownership and decision-making power to community participants rather than to a small number of business executives.

This phenomenon highlights a critical challenge for traditional platforms like Amazon, Meta, Google’s play store, and Apple’s app store, gaming platforms like Roblox or Steam, and even for newer centralized crypto platforms like Coinbase and OpenSea. Historically, as platforms became dominant in their domain, they have raised fees and changed rules to their benefit and their producers’ loss. They could do so because those producers — be they software developers, small retailers, game designers, or content creators — had nowhere else to go. But once learned, twice a fool: How can platforms keep producers making new investments in building for environments whose undemocratic governance systems cannot credibly promise to reflect their interests in the long run?

There is a way. By granting governance tokens to producers that give them the unbreakable right to vote on key decisions about fees and rules, platforms can give producers the ownership and assurances they need to unleash their innovation — to the benefit of the platform, its users, and its creative partners.

We are academics who study democratic systems of governance, and we are also advisors in the tech sector who think about the future of decentralized governance. In this essay, we’ll explain the challenge platforms are facing in maximizing the efforts of their producers, we’ll show how insights from blockchain governance can help, and we’ll discuss some specifics of how to implement a governance-token system that avoids common pitfalls that democracies have been grappling with for thousands of years.

The Lock-in Problem

In the early days of Web 2.0 — the movement that gave us mega platforms like Amazon, Facebook, and Uber — producers flocked to build for new platforms because that’s where the users, and thus the profits, were. But as some platforms failed and others became dominant in their spaces, the producers’ outside options dwindled, and so did their market power.  ... ' 

What Makes a Company Future Ready?

 Mostly paying close attention to changes, testing adaptations in changing contexts. 

What makes a company “future ready”?   in the HBR     by Howard Yu, Jialu Shan, Angelo Boutalikakis, Laurence Tempel, and Zuriati Balian,     March 21, 2022

Summary.   

What makes a company “future ready”? The author analyzed top companies by revenue across four sectors, measuring seven equally weighted factors, then analyzed what leading companies were doing differently. They discovered industry specific insights, which also informed more universal lessons. First, don’t play zero-sum games with disruptors. Looking at the financial industry, companies that explored new tech early were able to develop partnerships and exploit that tech more quickly. Second, when everyone is digitizing, only going deep sets you apart. Learning aggressively, with a strong viewpoint, helped retail companies find opportunities to differentiate. Third, in a high-speed sector, you have to branch out fast. Looking at the tech sector, the author saw the importance of knowing what kind of decision you’re making, so you can make it quickly. ....'

The pandemic put companies under a tremendous amount of stress. It revealed who is ready for the many changes the near future will bring — and who is not. In times of crisis, this type readiness doubles as a source of resilience. It reflects how companies can adapt, the robustness of their internal capabilities, and how capable of finding new sources of growth they really are. And the more uncertain the world seems to be, the more important for companies to become future ready.

Consider how fashion brands and retailers have navigated the past two years. Executives have been talking for more than a decade now about how retail is moving toward direct-to-consumer, omnichannel, and personalized offerings. Then the pandemic hit. The winners have been the ones who have scaled such capabilities ahead of their competition. Stock prices at Hermes, Nike, and Target have hit all-time highs as they have pivoted to e-commerce, in stark contrast to the parade of bankruptcies among some of retail’s most iconic names: Brooks Brothers, J. Crew, and JC Penny.

The automotive industry offers another example of the importance of becoming future ready — specifically, in cultivating mastery of software and electronics. While major carmakers have made strides to pivot to electric vehicles, the ongoing semiconductor shortage has forced companies like VW and GM to halt their production lines. Tesla, on the other hand, was able to “substitute alternative chips, and then write the firmware in a matter of weeks,” explained Elon Musk. This process required quickly rewriting the car’s software, which was possible because of Tesla’s in-house mastery, and helped Tesla deliver 308,600 vehicles in the fourth quarter — up from 180,667 the previous year — achieving a “trophy-case” performance.

Becoming future ready means scaling up capabilities relevant to future competition. In previous research, we found that a company must make regular shifts in its know-how in order to stay ahead of competitors over the long run. If a company’s know-how stagnates, it will face competition from copycats, fall behind in advancements, and eventually fail.   ... '

Work in the Era of no Retirement

 Brought to my attention from the HBR.   Do we or should we want this?

Getting the Best Out of the Five-Generation Workforce

A 6-part series.

Work in the Era of No Retirement.   Longevity is an opportunity for companies — but only if they can overcome ageism.   by Susan Wilner Golden

Read More

HBR IdeaCast on AI and Marketing

Brought to my attention, the podcast below, and ongoing ...

HBR IdeaCast

A weekly podcast featuring the leading thinkers in business and management.... 

What We Still Need to Learn about AI in Marketing — and Beyond

Eva Ascarza, professor at Harvard Business School, studies customer analytics and finds that many companies investing in artificial intelligence fail to improve their marketing decisions. Why is AI falling flat when it comes to this key lever for profit? She says the main reasons are that organizations neglect to ask the right questions, weigh the value of being right with the cost of being wrong, and leverage the improving abilities of AI to change how companies make decisions overall. With London Business School’s Bruce G.S. Hardie and Michael Ross, Ascarza wrote the HBR article "Why You Aren’t Getting More from Your Marketing AI."   ... 

Quantum Computing Coming. What Can it do?

Good overview in the HBR.  Emerging investments.  Emphasizes combinatorics, as has been seen since the beginning.

Quantum Computing Is Coming. What Can It Do?   by Francesco Bova, Avi Goldfarb, and Roger Melko

Summary.   Digital computing has limitations in regards to an important category of calculation called combinatorics, in which the order of data is important to the optimal solution. These complex, iterative calculations can take even the fastest computers a long time to...more

Quantum technology is approaching the mainstream. Goldman Sachs recently announced that they could introduce quantum algorithms to price financial instruments in as soon as five years. Honeywell anticipates that quantum will form a $1 trillion industry in the decades ahead. But why are firms like Goldman taking this leap — especially with commercial quantum computers being possibly years away?

To understand what’s going on, it’s useful to take a step back and examine what exactly it is that computers do.  ... ' 

IKEA Digital Trasformation

 A long time follower of IKEA, both as a customer, and briefly interacting during our building innovation centers.  Most notably in their use of VR approaches to deign consumer uses of IKEA furnishing design.  Like to see more about what they are doing digitally, had been impressed by past work.  Note mention of pandemic closure of stores in pandemic, which I was not aware of..

Inside IKEA’s Digital Transformation  by Thomas Stackpole

Summary.   How does going digital change a legacy retail brand? According to Barbara Martin Coppola, CDO at IKEA Retail, it’s a challenge of remaining fundamentally the same company while doing almost everything differently. In this Q&A, Martin Coppola talks about how...more

What does it mean for one of the world’s most recognizable retail brands to go digital? For almost 80 years, IKEA has been in the very analogue business of selling its distinct brand of home goods to people. Three years ago, IKEA Retail (Ingka Group) hired Barbara Martin Coppola — a veteran of Google, Samsung, and Texas Instruments — to guide the company through a digital transformation and help it enter the next era of its history. HBR spoke with Martin Coppola about the particular challenge of transformation at a legacy company, how to sustain your culture when you’re changing almost everything, and how her 20 years in the tech industry prepared her for this task.

How is the digital transformation at IKEA changing how the company actually operates in the day-to-day?

In practical terms, we’ve approximately tripled ecommerce levels in three years. We have transformed our stores to also act as fulfilment centers. To make that work, the flow of goods needed to change, the supply mechanisms needed to change, and also the floorplans of the store needed to change. Ecommerce is open 24 hours a day, while traditional stores are not, which means we’ve needed to learn how to operate at two speeds, while operating from one space. Goods can be delivered from the stores, or from different distribution centers — and algorithms are helping figure out where the goods are being sourced from. We’re rapidly expanding data and analytics and changing how they’re embedded in decision making.

With the pandemic and with the closure of approximately 75% of our stores, we ramped-up and accelerated even more as people turned online and towards digital solutions. Things that would normally take years or months were carried out within days and weeks.

The digital transformation is not a goal in and of itself, and it is so much more than technology. We are transforming our business: We are exploring potential new offers to customers, new ways to bring our offers to customers, and new ways to operate our business. And in order to be successful, digital needs to be embedded in every aspect of IKEA. Digital is a way of working, making decisions, and managing the company .... '

AI's competitive Advantage

Interesting podcast, and ongoing pieces I am now connected to:

Exponential View with Azeem Azhar / Season 5, Episode 32

Subscribe:  Apple Podcasts  Google Podcasts   Spotify    RSS

AI’s Competitive Advantage

AI can offer a new type of competitive advantage, but entrepreneurs need to know what it is and how to unlock it. Ash Fontana, author of The AI First Company and managing director at Zetta Venture Partners – a firm that exclusively invests in early-stage AI startups, joins Azeem Azhar to explore the risks and rewards of applying AI to business problems.

They also discuss:

Why the high up-front cost of developing AI models favors multi-sector businesses.

Which is more important for an AI-focused company: domain expertise or AI expertise?

How AI startups should assess the risk of being usurped by Big Tech.

Why Amazon’s sophisticated AI regularly offers nonsensical recommendations.

@ashfontana @azeem  @exponentialview

“Creating an AI-First Business with Andrew Ng” (Exponential View podcast, 2019)

“Businesses are finding AI hard to adopt” (The Economist, 2020)

“Competing in the Age of AI” (Harvard Business Review, 2020)

The AI First Company: How to Compete and Win With Artificial Intelligence (Ash Fontana, 2021)

HBR Presents is a network of podcasts curated by HBR editors, bringing you the best business ideas from the leading minds in management. The views and opinions expressed are solely those of the authors and do not necessarily reflect the official policy or position of Harvard Business Review or its affiliates.  ... " 

On Clearer Communications in Unclear times

Well done piece in HBR on implied rules of communications.  Have they changed?  Been made more important in hybrid times?  Now that we have a dozen more ways to communicate.   Below link to the broader article in Quester. 

Did You Get My Slack/Email/Text?  by Erica Dhawan    in HBR 

Summary.   We are in the midst of a major transition from remote to hybrid work. As this shift is happening, it’s essential for managers to establish norms around digital communication with their teams. Having a detailed guide will help ensure that everyone on your team is on...more

Back when we were in the office, we all knew the unwritten rules of communication. If someone had large headphones on, they probably were focused on work, and didn’t want to be interrupted to gossip about the latest drama. Or if your team was about to have an important meeting with a client, you would quickly run through last-minute questions before walking into the room.

We all learned these communication norms by observing our colleagues. But now with the rapid shift to hybrid work there is a need to create new rules for digital communication. Somehow it seems that the more platforms we have at our disposal, the more complicated digital communication gets.

I published a research study with Quester this month called “The Digital Communication Crisis” to understand the challenges that we all face in workplace digital communication. Through a survey of almost 2,000 office workers, we found that over 70% experienced some form of unclear communication from their colleagues. This leads to the average employee wasting four hours per week on poor or confusing digital communications, which adds up to an average annual amount of $188 billion wasted across the American economy.  ... ' 

(The additional stats in 'The Digital Communication Crisis', linked to above are interesting, and could help you redesign communications in your workplace. ")

Time to Rethink Your Global Logistics

Some thoughts about changes Post Pandemic adjustments in supply chains.

It’s Time to Rethink Your Global Logistics

by Willy C. Shih and Adrien Foucault  in the HBR

Over the last three decades, companies have established wide-ranging global supply chains that have taken advantage of steadily improving scale economies in global logistics. Efficient and reliable ocean and air cargo have linked low-cost manufacturing hubs across Asia with major markets in the United States and Europe. Much of this global sourcing was driven by the cost savings reaped through labor arbitrage, cost savings that were so dramatic that it more than covered the expense associated with moving products across vast distances to markets, or the extra cost of carrying inventory in long pipelines.

Yet the disruptions in logistics networks caused by the Covid-19 pandemic have added to the woes of supply chain managers who have tended to focus narrowly on their production partners and less on their geography and the links that connect them. With some of the shifts already underway to diversify production and make supply chains more resilient, it is a good time for managers to take a more holistic view of logistics as a dynamic and evolving link in their supply chains.

Concentrated East-West Trade Lanes

The massive increase in global merchandise trade of the last two decades and the shifts in production from the West (United States and Europe) to the East (Asia, particularly China) were fueled by labor arbitrage and cost advantages, but they were powered by low-cost container shipping and air cargo. On the ocean trade side, subsidies for shipbuilding and tax incentives for shipowners combined with giant new Euromax container ships (starting with the Emma Maersk in 2006) brought a step change in lower costs.

To utilize this capacity efficiently, container lines built east-west networks with efficient transshipment hubs, creating high-volume trade lanes on the trans-Pacific and East Asia-Suez-Europe routes. Fueled by a race to deploy larger and larger ships, chronic excess capacity also led to irrationally low prices for transporting goods halfway around the world. ... ' 

 

Stop Conversations Sooner?

Perhaps a guide for chatbots?  Or is the guide for them different?  Though like all such guides, and rules of thumb, depends highly on context.

When Should You End a Conversation? Sooner Than You Think, Harvard Research Shows In two experiments, more than 67 percent said they wanted out but the other person kept talking.

By Minda Zetlin     @MINDAZETLIN  in INC,   Harvard research 

Do you want people to enjoy talking with you? You should probably end your conversations more quickly than you do. Most people stay in conversations longer than they want to for fear of hurting the other person's feelings, new research shows. In fact, in about two thirds of conversations, whether between strangers or loved ones, at least one person wants out well before the exchange ends. Sometimes both people want to stop, but they keep on talking anyway, because neither wants to cause offense.

That's the finding from two recent experiments by a reearch team headed by Adam Mastroianni, a doctoral student in psychology at Harvard. In one, 252 strangers were paired up for conversations that could be as short or as long as they wished, up to 45 minutes. In the other, 806 online volunteers were asked to think about a recent conversation with someone they were close to. In both cases, more than two thirds of participants reported that the conversation had gone on longer than they wanted. Some participants thought the conversation was too short and wished they could have kept talking. How often were both people satisfied with the length of their conversation? Only 2 percent of the time.  ...  " 

Global Variances in Digital Trust

 Digital Trust, supposedly accurately measured.  Had not seen this before, probably useful if accurate.   The components of the measure also seem  they would be hard to generally measure.   And likely have   considerable variance over time, depending on the news.  Below a summary of a long article in the   HBR.   

How Digital Trust Varies Around the World  by Bhaskar Chakravorti, Ajay Bhalla, and Ravi Shankar Chaturvedi     February 25, 2021

Summary.   

As economies around the world digitalize rapidly in response to the pandemic, one component that can sometimes get left behind is user trust. What does it take to build out a digital ecosystem that users will feel comfortable actually using? To answer this question, the authors explored four components of digital trust: the security of an economy’s digital environment; the quality of the digital user experience; the extent to which users report trust in their digital environment; and the extent to which users actually use the digital tools available to them. They then used almost 200 indicators to rank 42 global economies on their performance in each of these four metrics, finding a number of interesting trends around how different economies have developed mechanisms for engendering trust, as well as how different types of trust do — or don’t — correspond to other digital development metrics.   ...' 

Boosting Inbound Sales

This happened to come up in a conversation last week.   Good summary below and more detail at the link.

4 Behaviors that Boost Inbound Sales  by Matthew Dixon, Ted McKenna, and Tom Shepherd  in  HBR

Summary.   

Particularly during the pandemic, when face-to-face visits with customers have been constrained, inbound selling in calls centers has become more important to company revenue. New research uses recordings of millions of such calls, analyzes the way salespeople drive the conversation, and record whether the call results in a sale. This analysis shows four behaviors that play the biggest role in converting callers into buyers: Disqualifying callers who shouldn’t be dealing with a salesperson, prescribing a solution to the customer problem, digging into objections, and de-risking the purchase so callers don’t get off the phone to “think it over.” Only 1% of calls contained all four of these behaviors — but when they did, 70% of calls resulted in a sale.   ... '

Limitations of a Fremium Approach to Marketing

Thoughtful examination of the approach of free ... and the idea of freemium. 

Don’t Count on Free Trials to Win You Customers  in HBR, by Sadat Reza, Dixon Ho, Rich Ling, Hongyan Shi, and Gemma Calvert

January 07, 2021

Summary.   The authors’ research provides evidence that for “experience” goods– those where value is only discovered after consumption, for example a holiday destination, a movie, or new software — free trial campaigns should be deliberately targeting existing customers of medium to high usage. For this...   more

Everybody loves a freebie. That’s probably why so many start-ups and even well-known brands often use free trials to draw customers’ attention and introduce them to new products. Yet free trials often fail to convert customers to paying ones. Even when they do convert, customers obtained using free trials can be significantly less valuable than other customers. The problem, our recent research suggests, is that too many free trial campaigns aim to bring new customers to a brand’s products rather than enticing existing customers to spend more. If this is true, our research can help marketers find the sweet spot for free trials.

When freebies work

In our study, we collaborated with a major mobile phone operator in a developing market, where the average usage of mobile data services was much lower compared to the developed market. The marketing team of the company sent out 60MB free mobile data — about an hour of low-resolution video streaming through the web — offer to 60,000 subscribers of their mobile phone services. The offer receiving subscribers were randomly chosen from the pool of subscribers who used smart-phones and used SMS services but had different levels of exposure to using mobile data, including non-users and heavy-users.

We anticipated that nonusers of mobile data would be more likely to redeem the offer and increase usage after the campaign. To our surprise, it turned out that the low usage customers were largely unresponsive to the trial offer and the campaign failed to stimulate higher usage among these customers. Customers familiar with using a lot of data did take advantage of the trial offer, but we found that their data usage didn’t change during the trial period. Our third group of customers — those who use a medium to high amount of data regularly — were most likely to redeem the offer and we also found that their data usage increased after the campaign. Lastly, we also found that peer effect matters. When the company gave some customers the option to forward the free trial to peers (who were also existing customers) they were more likely to redeem the offer.

Our research provides evidence that for “experience” goods — for example a holiday destination, a movie, or new software, where value is only discovered after consumption — free trial campaigns should be deliberately targeting existing customers of medium to high usage. Our study reveals that for this type of goods and services, relative to non-users, customers with some exposure to the product are more responsive to free-trial campaigns.   ... ' 

Lopsided Digital Transformation

Look at how automation of digitization can make a big difference.   And we are continuing to move to that. 

Digital Transformation Is Lopsided, Even Within the Same Organization    By ZDNet

A study of organizations in Harvard Business Review found that some corporate departments can be more digitally advanced than their counterparts at another location, or even down the hall. The IT department itself often finds itself on the wrong side of progress.

A Harvard Business Review study of organizations found "a growing divide between teams with ready access to automation and [artificial intelligence (AI)] tools and teams without," with the latter trailing "in terms of productivity and AI skill development."

Accenture's Ramnath Venkataraman and colleagues determined that two-thirds of investigated companies relied on a less-than-optimal blend of cloud-based and on-premises enterprise solutions.

Exacerbating the problem is information technology (IT) departments being mired in maintenance and upkeep, while other departments have access to cutting-edge systems.

The Accenture team also learned that some coders might devote 60% of their time executing automatable tasks.

The researchers suggested greater inter-enterprise collaboration to address these challenges, by de-siloing walled-off departments and encouraging open access to shadow IT systems. ... ' 

From ZDNet

Do Robots Make us Happier?

Not sure they are meant to.   Do calculators make us happier?  Computers? The Internet?   No they just give us the option for some assistive benefit ...  which includes happiness.     Like exploring the idea of happiness given to us by robots.   The exploration is good. 

Robots Save Us Time — But Do They Make Us Happier?  by Ashley Whillans , Emanuel de Bellis , Fabian Nindl and Tobias Schlager in HBR

HBR Staff/Duet Postscriptum/Stocksy/Nednapa Chumjumpa/Getty Images

As of 2019, more than 14 million Americans owned a robotic vacuum cleaner. Robotic lawn mowers tend to our yards, robotic suitcases follow us through the airport, and smart cooking machines prepare ingredients and implement entire recipes. Some autonomous products even play with and clean up after our pets. These tools are meant to improve people’s lives, relieving them of chores and making them happier as a result — and while some do this, other’s don’t. How can business leaders ensure that their companies are developing products that people actually feel good about using?

As consumer psychologists, we have accumulated a great deal of evidence that spending money to outsource disliked tasks — such as by paying for a housecleaner — can improve happiness, lower stress, and improve our romantic relationships (even during the pandemic). But as technology develops, we have begun outsourcing not only to humans, but to machines as well.  ... "

Considering the AI Factory

Nicely covered by Irving:

The AI Factory: A New Kind of Digital Operating Model

“Whether you’re leading a digital start-up or working to revamp a traditional enterprise, it’s essential to understand the revolutionary impact AI has on operations, strategy, and competition,” wrote Harvard professors Marco Iansiti and Karim Lakhani in “Competing in the Age of AI”, a recently published article in the Harvard Business Review (HBR).  Earlier this year, they also published a book of the same title, which expands on the ideas in the article and illustrates them with a number of concrete use cases.

The age of AI is being ushered by the emergence of a new kind of digital firm.  Rather than just relying on traditional business processes operated by its workers, these firms are leveraging software and data-driven algorithms to eliminate traditional constraints and transform the rules of competition.  Managers and engineers are responsible for the design of the new AI-based operational systems, but the system then runs the operations pretty much on its own.

“At the core of the new firm is a decision factory - what we call the AI factory,” note the authors.  “[T]he AI factory treats decision-making as a science.  Analytics systematically convert internal and external data into predictions, insights, and choices, which in turn guide and automate operational workflows…  As digital networks and algorithms are woven into the fabric of firms, industries begin to function differently and the lines between them blur.”

The Industrial Revolution transformed the economy by developing a scalable, repeatable approach to manufacturing.  The AI factory is now driving another fundamental transformation by industrializing the data gathering, decision making, and overall digital operations of 21st century firms.  

The AI factory involves four key components:   

Data pipeline - the process which systematically gathers, cleans, integrates, and safeguards data;

Algorithm development, - the component which generate predictions about the future states of the business and drives its most critical operating activities;

Experimentation platform - the mechanism on which predictions are tested to ensure that they will have the intended effect; and

Software infrastructure, the systems that embed these various components in software and connect it as needed to the appropriate internal and external users. ..... 

(Much more at the link)   Will look at this more closely.  

The Effect of Privacy Notices

An example of behavioral response to alerting consumers,

The Bulletproof Glass Effect: When Privacy Notices Backfire

by Aaron R. Brough, David A. Norton, and Leslie John in HBSWK

Consumers regularly encounter privacy notices explaining if and how their personal information will be collected, stored, used, and shared. Evidence in this study demonstrates that privacy notices, though designed to promote a sense of confidence that personal data will not be misused, can undermine consumer trust and decrease purchase intent.

Author Abstract
Firms typically provide assurances to consumers about data management practices in the form of privacy notices. This manuscript proposes that ironically, such assurances can fuel rather than alleviate privacy concerns. Indeed, we show that consumers react to assurances as if they were warnings—a counterintuitive phenomenon because unlike warnings, which communicate danger, assurances are designed to communicate protection. Across one field experiment and five lab experiments, we show that a salient (vs. an absent or less salient) privacy notice can lead to decreased rather than increased purchase intent. This effect is mediated by consumer trust and is robust to the language in the privacy notice—it occurs even when the notice is overtly assuring, as well as when consumers see only a link to the notice but do not view its contents. The attenuation of the effect in joint (vs. separate) evaluation suggests that consumers’ hesitation to transact with organizations that have a salient privacy notice is not likely driven by an active aversion to assurances but rather by the arousal of dormant privacy concerns.

Paper Information
Full Working Paper Text (pdf) http://www.hbs.edu/faculty/pages/download.aspx?name=20-089.pdf
Working Paper Publication Date: February 2020
HBS Working Paper Number: HBS Working Paper #20-089
Faculty Unit(s): Negotiation, Organizations & Markets .... "

Teams Fighting Burnout

Rarely seen this attempted, or effectively done.  Lip service.  In one on one cases, but not as a group.  Rewards?   And usually too late. 

Teams Fight Burnout Together  in the HBR
By Tony Schwartz, Rene Polizzi, Kelly Gruber, Emily Pines

Here’s a vexing paradox. On the one hand, companies are offering more wellness and well-being options than ever before, including mindfulness and yoga classes, nap rooms, and fitness facilities. On the other hand, employee burnout has risen to such a level that the World Health Organization now considers it a workplace hazard.

Most corporate well-being offerings are well-intended and potentially valuable. The problem is that without challenging the deeply embedded mindset that more, bigger, faster is always better, these offerings don’t get fully supported, nor are they widely and freely utilized.

Earlier this year, Ernst & Young (EY) and The Energy Project set out to test a hypothesis: If all members of a client-serving team rallied together to build more rest and renewal into their lives, they would feel better and they’d get more work accomplished in less time.   ... "