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The cost of intelligence: How CIOs can manage AI demand at scale

McKinsey

Jul 2026

The cost of intelligence: How CIOs can manage AI demand at scale

McKinsey

HR Dive

HR Dive

Anchita Ranka

Jul 2026

PRINTABLE VERSION HERE

Dynamic pricing deserves attention now because three developments have converged. Artificial intelligence has made individualised pricing accessible, allowing for the possibility of a different price for every consumer. The growth of e-commerce has supplied both the behavioural data and the repricing infrastructure to act on it. Meanwhile, regulation is beginning to take shape, and the rules that will govern individualised pricing are being written before most retailers have decided where they stand.

As individualised pricing spreads, the question for department stores is not whether to run a data operation — they already run one, through their loyalty programmes, apps and data partnerships — but what to do with it. Two answers follow, and only one is defensible. The first is to point that operation at customers the way big tech does, personalising prices to extract the most each will pay but its failure mode is defeat by big tech itself. IADS argues that the second is to run the same machinery under a public commitment that it will only ever move a customer's price downward, and to make that transparency the differentiator.

The taxonomical pricing debate

The fundamental source of confusion in the contemporary pricing debate stems from the conflation of four concepts by media, regulators, and retailers. That many retailers have never resolved the confusion inside their own organisations is why so few can take a clear position on it. Algorithmic pricing, often powered by AI and machine learning, recalibrates prices across any combination of factors including, but not limited to, demand, competitor data, seasonal patterns, supply costs, and customer behaviour. NRF contends that this is simply the digitised and accelerated version of what retailers have always done manually.

Algorithmic pricing spans a spectrum in terms of data input, transparency, and degree of personalisation. Dynamic pricing lies on one end, differential pricing somewhere in the middle, and personalised (or surveillance) pricing on the opposite end:

Dynamic pricing is the real-time adjustment of prices based on immediate demand signals, inventory levels, or competitor pricing. It is market-facing, with prices fluctuating for everyone based on these conditions, not depending on the specific customer. Given its scale of digital and infrastructure capabilities, Amazon reportedly made over 2.5 million price changes per day as far back as 2013. The business models of airlines, hotels, ride-hailing apps, and fuel retailers are based on dynamic pricing.
Differential pricing refers to charging different customer segments different prices such as seniors' discounts, student rates, and trade pricing. This is legally well-understood as it price discriminates based on market-facing customer characteristics.
Personalised pricing (also called surveillance pricing or individualised pricing) is the most contested variant. It uses personally identifiable data such as browsing history, location, credit score, purchase history, and mouse-movement patterns to infer each individual customer's maximum willingness to pay and price accordingly. Fordham Law professor Zephyr Teachout, explains it as using "the same data infrastructure that social media uses to sequence feeds, only here the information doesn't determine what someone sees but what they pay" The aim is to charge each buyer the most they can be induced to pay rather than a single market price.

The mechanism of individualised pricing

While modern dynamic pricing is proliferating across online storefronts, it is increasingly operationalised in physical stores, with the same interlocking technologies – in-store and online price labels, AI systems, and consumer data pipelines - enabling both. In either channel, the shopper's inability to observe the mechanism is engineered in rather than incidental.

In-store, electronic shelf labels (ESLs) are the enabler. The digital displays remove the need to manually re-sticker shelves, allowing prices to change in real time across an entire store silently, and leaving no record a shopper can inspect of what an item cost an hour earlier. While NRF argues that ESLs exist primarily for price accuracy and consistency, and to reduce compliance risk, rather than as a vehicle for surge pricing, they are also vehicles of enabling dynamic pricing when combined with backend analytical modelling, enhanced by AI.

AI systems learn over time how to find ‘optimised prices’ by running elasticity models examining how price changes affect demand across different SKUs, customer segments, and time windows. Digitalisation has resulted in the reduction of ‘menu costs’, allowing platforms to change prices as a function of demand at negligible cost. This can look like Uber and Deliveroo’s algorithmic surge pricing and discount coupons based on demand.

Consumer data pipelines power the entire process and separate algorithmic pricing from individualised pricing. None of the inputs they draw on are visible to the shopper being priced and include credit scores, GPS location patterns, search duration and frequency, individual purchase histories, browser cache and cookie data, and keystroke dynamics that correlate with different emotional states. The US Federal Trade Commission’s surveillance pricing study on intermediary firms such as McKinsey, Mastercard and Accenture, found that behaviours including mouse movements and items left in shopping carts are tracked and fed into individualised pricing models and used by at least 250 retail clients from grocery to apparel.

Loyalty programmes have historically been the most socially accepted form of individualised pricing as a straightforward exchange of data for rewards. However, that social contract has been hollowed out: in many cases the programme is now less a reward mechanism than the primary data-collection infrastructure that makes surveillance pricing possible. The clearest result is the reverse loyalty programme. Once a retailer has accumulated enough behavioural data to recognise a frequent customer's demand as inelastic, it can offer that customer fewer discounts rather than more resulting in the most loyal ending up being charged the most because their loyalty looks like captive demand. Reporting on Starbucks, whose loyalty data was found to have been shared with 64 third parties without customers' awareness, showed how loyal customers ended up paying more than others. The former director of the FTC's Bureau of Consumer Protection found that companies mine loyalty data to gauge how much customers will tolerate, and that programme designs are structured to obscure whether consumers save anything at all.

Why department stores cannot win the data war

The data asymmetry between big tech and any other retailer is structural and uncloseable. Amazon sees the full browsing and purchase graph of hundreds of millions of shoppers across every category plus the sales data of the third-party sellers who compete on its own marketplace. Through initiatives reportedly grouped under Project Starfish, a unified internal data system, Amazon ingests the product listings, prices, and transaction data of thousands of third-party brands, surfacing their goods and completing checkout inside its own app, even as it sends cease-and-desist letters to those who scrape its marketplace in return. Because many of those brands depend on Amazon's own cloud, the cost of resisting falls entirely on them.

Every transaction adds to Amazon's data, that data sharpens its next price, and the sharper price wins the next transaction, compounding the lead it already holds. A department store entering the same contest starts with less data, learns more slowly from what it has, and so improves its pricing more slowly than Amazon improves its own; the gap does not hold steady but widens with every cycle. The contest is also frequently run on Amazon's own ground: a department store that lists on its marketplace or builds on its cloud feeds the same transaction and cost data into the engine it is trying to beat, so the effort to compete on data can end up subsidising the competitor. A gap of this kind is not closed by spending more; spending only buys a place on a faster treadmill.

The data feeding Amazon's pricing engine therefore includes competitor and brand data that a department store could neither lawfully nor practically acquire. It reprices millions of times a day and runs continuous live experiments at a volume that produces reliable elasticity estimates for each SKU at a given moment. A department store simply lacks the traffic to learn at that scale. And because Amazon spreads the fixed cost of pricing infrastructure and data-science talent across a sales base no single retailer can rival, each increment it invests buys a sharper model than a department store's can. A retailer that competes on the platform's own terms therefore builds a permanently inferior copy of Amazon's machine and loses the data war anyway while giving up the one advantage Amazon cannot buy - a customer's trust that they are not being milked.

How individualised pricing erodes trust

The sharpest critique of personalised pricing is that it targets vulnerability and circumstance rather than preference. It prices the moment a shopper's bargaining power is lowest — the borrower with a poor credit score, or the parent buying for a sick child at midnight — pricing the weakness of the position, not a preference for better service.

Opacity is a core feature that makes individualised pricing sustainable. Because its operation is almost impossible to verify from the outside, a shopper has no basis on which to challenge it. As Teachout writes, "When different prices show up for different people, companies tend to claim it is not the work of surveillance pricing." Amazon and Delta have attributed observed price variation to "market dynamics, third-party sellers or A/B testing."

Economist and CEO of aiRESULTS, Matt Hasan argues that an algorithm may estimate what a customer can pay but cannot measure how they feel about paying it. Once a shopper discovers, or even suspects, that a price reflects what the system knows about them, the relationship turns adversarial. Those tools are already mainstream: price-history trackers such as CamelCamelCamel and Klarna's PriceRunner have made comparison a reflex, and a 2025 Deloitte survey found that 56% of US consumers planned to use AI assistants to compare prices and hunt deals. As that capability spreads, a growing share of consumers will police prices and disengage until they fall. This is still a trajectory, not a settled state, but it runs one way. As opacity grows costlier to defend, the endpoint is agentic commerce: buyer and seller algorithms manoeuvring against each other until the human relationship with the brand thins to nothing. A customer who starts tracking prices is no longer loyal but transactional, and the extra margin taken from them now is lost when they disengage. Nearly 70% of consumers said they are very or extremely protective of their personal data and would trust a merchant less for covertly using it.

This is what makes transparency decisive, and it answers the obvious objection that a platform like Amazon is trusted despite its data practices. Consumers do not process prices as rational negotiators but as signals of fairness and intent. Once a shopper starts to feel like a target rather than a customer, concealment cannot undo it — and suspicion alone, not proof, is enough to trigger the shift. Personal income shapes both how unfair a price feels and how strongly consumers act on it, so for households with the least budgetary room a shifting price reads as exploitation rather than just annoyance. The only long-term control is to make the logic of prices legible. Amazon is tolerated on convenience and price, not on pricing candour. This is the uncomfortable point: its scale is proof that most shoppers reward convenience over candour, so transparency is a bet on the segment that values being dealt with straight.

How a department store earns trust

Making that bet credible begins with an honest admission: department stores too operate loyalty programmes, apps, and data partnerships built on the same infrastructure described here. The real position is therefore not that a department store holds less customer data, but that it commits to using it in only one direction, to lowering prices, but not to raise them. The same behavioural signals that could locate a customer's ceiling can instead fund discounts, protect the price of essentials, and reward frequency, while the retailer refuses on principle to convert a rewards relationship into a map of who can be charged more. But a promise to hold that data and not weaponise it is not self-enforcing. The capability to find each customer's ceiling stays in-house, the margin from using it is permanent, and its use is nearly impossible to detect from the outside, so restraint is precisely the claim a shopper cannot verify.

Christine Montard

Jul 2026

IADS Exclusive - The great Marks & Spencer reset: A retail transformation case study

Christine Montard

Jul 2026

PRINTABLE VERSION HERE

With its 142 years of history, Marks & Spencer (M&S) is a British retail institution, originally a penny bazaar in Leeds with the radical proposition: “don't ask the price, it's a penny”. M&S built its first competitive advantage not on price alone but on simplicity and trust, principles that remain the foundation of the brand. From the 1930s, the company began bypassing wholesalers entirely, working directly with British manufacturers with quality specifications, and selling exclusively under its own St Michael label. By 1997, M&S had become the first UK retailer to record a pre-tax profit of £1bn, a milestone followed by a continuous decline triggered by stiff competition and overreliance on UK sourcing (until the 1990s, M&S’s policy was to sell 99% UK-made products). FY2000/01 ended with a £145m pre-tax profit. In 2000, the St Michael brand was retired. In 2008, M&S started selling external brands, which confused consumers. The following fifteen years saw clothing sales falling while food sales increased.

The current recovery, under chairman Archie Norman (the architect of Asda's 1990s turnaround) and CEO Stuart Machin from 2022,has restored M&S to its strongest competitive position in over two decades by returning to fewer, better products, quality and value for money. In FY2025/26, group sales grew just 1.9%, from £13.9bn to £14.2bn. The food division accounted for £9.7bn, growing by 7% YoY.When it comes to general merchandise, in FY2024/25, M&S held 10.5% of total UK clothing sales despite losing a fifth of its UK clothing market share between 2014 and 2024. Group profit before tax hit £881.1m in FY2024/25, the highest in over 15 years. FY2025/26 fell to £671.4m, down 23.8%, due to a severe April 2025 cyberattack that paused e-commerce operations for approximately eight weeks.

The turnaround plan is on at the legacy retailer, but what is driving the change? Rationalising the product offering, transforming the brand's style credentials, developing a new consumer and marketing strategy, and an operational rethink could represent a basic plan, but its execution seems to be what matters for M&S.

How M&S redesigned its product offer

M&S Food: feeding growth

When Machin took the helm, M&S Food was a business with a strong identity but increasingly perceived as an expensive treat destination rather than a credible everyday choice. As stated in their 2024 annual report, Machin doubled down on product quality, upgrading over 1,000 existing products and launching more than 1,300 new lines, while simultaneously addressing the value perception gap through a Trusted Value Promise that delivered price cuts across more than 200 products. This dual approach, protecting M&S's elevated DNA while making the brand more accessible, proved effective. Food delivered LFL sales growth of 8.6% in FY2024/25, followed by a further 7% growth in FY2025/26. Critically, these figures were not inflation-driven as M&S outperformed the market over the three years leading to FY2024/25.

However, structural limitations remain. M&S Food still operates primarily through convenience-sized stores and food halls rather than full-line supermarkets, which limits its ability to capture the full weekly food shopping. M&S Food is seen as a complementary premium destination for most households rather than their primary grocer. However, Machin does a lot to reduce the gap with mainstream grocery by increasing store surfaces to offer a larger daily product range and more conventional meal planning.

Fewer, better: fashion brand portfolio simplification

Not only is food on the menu, but M&S is also undergoing a fashion makeover. Long derided by some as a destination for the over-55s, the retailer enforced a strategy to become a more style-conscious, trend-aware brand. The brand portfolio was simplified. M&S eliminated range clutter, reduced product options by 9% season-on-season until Spring/Summer 2026, and focused its tiered architecture on five clearly defined brand identities built around private labels: M&S Collection for everyday essentials, Per Una for a feminine occasion-wear customer, Goodmove for activewear (launched in 2020, it became M&S's biggest in-house own-brand by 2022, selling over 1.6 million items annually), Autograph for accessible premium, and a curated third-party brand platform.

The Autograph case demonstrates private-label relevance. Total Autograph sales grew 47% year-on-year in 2025. Men's Autograph alone reached approximately £200m, up from £50m just three years earlier, a four-fold increase driven by buying more deeply into core lines, elevating quality (cashmere, merino, Supima cotton, silk), increasing style and fostering innovation. For example, in October 2025, M&S launched Autograph Performance, a men’s technical workwear featuring four-way stretch, crease-recovery, water-resistance and machine-washable tailoring, which grew by 100% in under two years. Best-selling styles within Autograph include a £20 Supima cotton t-shirt that generates approximately £20 million annually on its own.

In parallel, the focus was on full-price discipline. By the end of 2025, about 80% of clothing was sold at full price, up from 63% pre-Covid, demonstrating that disciplined full-price selling offset any volume reduction. Furthermore, the time spent holding stock in inventory has fallen from 18 to 11 weeks. The Fashion, Home & Beauty (FH&B) division revenues grew from £3.72 billion in FY2022/23 to £4.24 billion in FY2024/25, while operating margins expanded from 8.7% to 11.2%. However, in FY2025/26 and mostly due to the April 2025 cyberattack, FH&B revenues were down 7.7% to £3.92 billion, and margins compressed to 5.5%. But the second half of that same year returned to +4.3% LFL growth. Online FH&B sales dropped 41% in H1 and recovered to +5% in H2.

Finally, a Brands at M&S platform was built as a parallel strategy, primarily conducted online and in-store, where relevant. M&S onboarded 60 external brands by FY2022/23, growing that revenue by 67% to £158m. In 2025, partner-brand fashion sales online increased by 42%, and the overall third-party brand sales exceeded £200m. Labels include Hugo Boss, Nobody's Child, Whistles, Hush, Calvin Klein, Tommy Hilfiger, Adidas, Sweaty Betty and Speedo. Those brands strengthen categories where M&S is weaker, while reinforcing its quality and fashion positioning by association. The external brand strategy was tried in 2008 without any success, as it was introduced as a substitute because M&S's own brand had lost credibility. There was no clear strategic rationale or curation principle. Rather, it looked like a contingency plan. Finally, it confused customers about what M&S stood for. What seems to be different this time is that M&S’s own brands have been fixed first and foremost. External brands are complementary, only filling gaps where needed. Brands at M&S also expand into beauty with the addition of brands like Clinique. In 2022, the strategy proved efficient in driving cross-selling: 96% of third-party brand purchases included another product.

M&S had done a good job re-establishing its value, quality and style credentials, with apparel market share rising to 10.5% in 2024/25, from 9.1% in 2021/22. In early 2025, John Lyttle, Managing Director of Clothing & Home, was tasked with transforming the end-to-end supply chain, consolidating suppliers to reduce risks and doubling online FH&B revenues from £1.4 billion to approximately £3 billion.

Home categories: less is more

In Spring 2024, the company formally exited its own-brand bulky furniture business. The logistics cost relief accrued in FY2025/26 contributed to overall supply chain cost reduction even in a year severely disrupted by the cyberattack. Bulky furniture required a dedicated distribution network with structurally low returns. Exiting it allowed M&S to concentrate its home investment on categories where its quality credentials are strongest: bedding, bath, soft furnishings, tableware and home fragrance. In addition, the Kelly Hoppen collaboration, launched in September 2024, gave M&S a design identity in the home that matches what Autograph does for fashion: authority through private labels.

From perception to purchase: M&S's consumer strategy

Demographics and brand perception

The critical data point regarding consumer perception of M&S is that style perception improved, reaching #1 for style in YouGov rankings, overtaking all competitors despite the trading disruption caused by the cyberattack. Quality and value perception both maintained #1 positions. In more detail, M&S clothing's brand perception and market position strengthened from 2020 to the 2025 cyberattack, rising from 40 to 50.1 in 2025. It now significantly outperforms the average high street fashion retailer in quality, value, reputation, satisfaction, and recommendation scores. M&S ranks first among all high street fashion brands for consumer consideration, with a score of 46.8%, well ahead of Next (34.8%) and Primark (30.1%). With 54% conversion from consideration to purchase intent, M&S also leads in converting interest into actual purchase intent (Next is at 40%, and Primark at 45%). Private labels also help the retailer’s consumer perception. The demographics of Autograph's new customers proved particularly relevant for attracting a younger crowd: 52% of Autograph menswear buyers in FY2024/25 were new, and 55% of all Autograph customers were under 45.

With consumer data stolen, the question of customer loyalty rapidly emerged in the wake of the cyberattack. A survey of 500 UK consumers on the public perception of M&S, conducted by consumer research company Maru, found that the number of consumers who would recommend M&S to others dropped from 87% before the cyberattack to 73% after it was made public. Despite the devastating event, YouGov's Best Brand Rankings 2026, measuring full-year 2025 data, show M&S as the #1 brand in the UK for the second consecutive year, with a score of 52.7, leaving the second-ranked brand (IKEA at 42.6) more than 10 points behind. In 2019, the retailer’s reputation score was 38.9. It was 45.6 at the end of 2025.

Influence, celebrity and community: M&S's marketing playbook

A commercially efficient example of the retailer’s marketing strategy is the M&S Insiders Programme, 22 colleagues in 2025 who post on Instagram and TikTok about M&S fashion and home products. Early on, they had a combined following of over 300,000. They found that with an M&S Insider post, customer sentiment is, on average, 10% higher, and 30% more customers choose to shop through M&S.com compared to a conventional influencer post. In FY2023/24, the programme generated 21 million impressions.

The celebrity layer has been developed over the years. Sienna Miller's September 2023 Anything But Ordinary collection and campaign exemplify M&S's A-list positioning. The campaign generated a Google search spike and a viral TikTok creator moment. A second party-oriented Sienna Miller collection followed in October 2024, driving younger customers in-store, 10 years younger than the store average of 35- to 50-year-olds. It also sold through quickly, with more than 42,000 customers clicking “contact me when available” for the sold-out styles. According to M&S, 92% of customers who bought from the Sienna Miller collection also bought from the store’s core womenswear lines. Their Bella Freud collection sold 9,000 jumpers in two hours. Machin regretted that it was a small buy.

In March 2026, Gillian Anderson joined M&S as "Chief Compliments Officer" in a new role focused on affirmation and customer connection, including expansion into platforms like TikTok Shop. This quirky initiative builds on the retailer’s Love That! campaign, which originated as a social media series and quickly gained viral traction, generating 20 million views. Through this approach, M&S is tackling emotional branding to increase its bond with customers.

Loyalty scheme: Sparks reignited

In April 2026, M&S overhauled its Sparks loyalty scheme, replacing traditional point-earning and burning with spendable cash rewards. The new digital Sparks wallet allows shoppers to earn cash rewards across all categories, with additional bonuses for cross-category purchases and partner activities, such as booking holidays with Virgin Atlantic. This overhaul is possible thanks to advanced AI and data analytics, enabling the delivery of offers tailored to individual shopping habits. The programme also encourages customers to explore new areas of the store, rewarding discovery and engagement beyond their usual purchases.

The M&S's comeback: culture, international expansion, crisis and infrastructure transformation

A new management style and mindset

Chairman Archie Norman created the conditions for Machin to succeed by enabling candid conversations about the state of the business. With more than 60,000 employees and around 1,500 stores, Machin’s leadership style is hands-on and detail-obsessed. For example, Machin is the number one M&S menswear customer, buying everything from shoes to jackets, regularly visiting stores unannounced to shop and observe. Also, he keeps a black book in which he writes down every product, its price, his views on it, and comparisons with competitors. Store managers have his phone number in case they need to text him with questions or feedback. The Straight to Stuart programme allows any staff member to contact him with ideas and to get a reply. More than 25,000 people have written to him in his first two and a half years as CEO.

One of Machin's earliest moves was to break a culture of defensiveness and silence. Key actions included standing on a box every Monday to share real trading numbers with the team, including bad news, creating psychological safety for staff to speak up, and tackling resistance to change from within, which Machin compares to the instinct to reject a transplanted organ.

Machin articulated a simple, memorable strategy: protect the magic, modernise the rest. That transformation includes closing shops, reducing the space M&S dedicates to clothing, and improving its online capabilities to reach 50% of the clothing business achieved online. Despite strong results, Machin resists complacency, describing himself as positively dissatisfied. He warns against "rose-tinted spectacles" and maintains that the journey is ongoing, especially considering the April 2025 cyberattack.

A renewed international expansion

M&S started its international expansion in the 1970s by buying local chains. By the mid-1990s, they were rapidly opening franchised and owned stores, with the ambition to reach 25% of revenues from overseas by 1997. The overexpansion unravelled quickly, leading to a complete withdrawal from all international markets. Starting from 2006, CEO Stuart Rose relaunched international growth, this time through a lighter franchise model, including the first store in China in 2008. His successor, Marc Bolland, declared the ambition to become a truly international retailer, with India and China as priorities. After Bolland opened a flagship on Paris’ Champs-Élysées in 2011 and announced plans for 250 new stores worldwide, his successor, Steve Rowe, reversed course entirely, closing 53 overseas stores in 10 countries in 2016, including Paris.

Under Machin, and learning from past experiences, M&S pursues its international development differently. This time, they partner with other established e-tailers and retailers: online with Zalando from 2022 and with Amazon from 2026 in European markets, and also with department stores in the US and Australia. M&S has partnered with 24 David Jones stores in Australia since 2025 and, more recently, with Nordstrom in 30 stores and online. With these partnerships, M&S acts as a brand rather than a retailer, capitalising on established customer bases to build brand awareness and test its appeal in new markets, while avoiding risky standalone stores. This move demonstrates the relevance of department store partnerships. Finally, to enhance global brand visibility, initiate additional partnerships and confirm its fashion ambition, M&S’s latest initiative is to present a see-now-buy-now collection at London Fashion Week in September 2026.

The attack that accelerated everything

The assault on M&S began quietly, months before it became public. Threat actors infiltrated the company's systems, stealing the database containing passwords for all domain users. The entry point was a social engineering attack in which hackers impersonated an M&S employee, convincing staff at a third-party IT contractor (reported to be Tata Consultancy Services, which has provided IT helpdesk services for over a decade) to reset an internal user's password.From there, the group linked to Scattered Spider deployed ransomware that encrypted M&S's virtual machine infrastructure. Customers first noticed something was wrong when contactless payments and click-and-collect terminals began failing across the chain. By April 25, M&S had shut down all online purchases. The online store remained closed for 46 days. In May, M&S confirmed that personal customer data had been stolen, prompting a mass password reset and official notification to affected customers.

The operational fallout was total in the weeks that followed. With automated stock ordering, inventory management, supply chain logistics, and internal systems all offline, M&S reverted to pen and paper. The financial consequences were severe and cascaded across the full year. M&S recorded £131.3 million in direct incident-related costs. Against this, it got £100 million in insurance proceeds, bringing the net direct cost to approximately £31 million. But the real damage was operational: online sales fell 41% in the first half of the year, resulting in a gross operating profit impact of approximately £300 million.

What the attack changed inside M&S is to be found in acceleration and transparency. Machin announced at the May 2025 results that M&S would use the disruption to compress a planned two-year technology transformation programme into six months, rebuilding on an accelerated timeline rather than recovering to the original plan. Digital and technology expenditure is planned at £140 million in FY2026/27 alone. Chairman Archie Norman called for mandatory reporting of cyberattacks to the National Cyber Security Centre, revealing that he believed two other major UK companies had been hacked in the preceding four months without public disclosure. The M&S general counsel, Nick Folland, told Members of Parliament that M&S would advise other businesses to ensure they can run their operations on pen and paper when a serious attack hits.

M&S's operational overhaul

As product appeal increased in FH&B, the business was still constrained by its legacy supply chain and outdated processes. Besides, the cyberattack prompted a new strategy that explicitly shifted toward better operational execution. M&S is spending £600m to £650m in FY2025/26, of which between £200m and £250m is being invested in technology infrastructure, store maintenance and upgrades to its logistics fleet. Automating what was previously largely a manual task, a new fashion planning platform that connects budgeting, buying, and replenishment is being fast-tracked following the cyberattack. A £120m three-year automation investment for the FH&B supply chain was announced to increase capacity, reduce complexity, and deliver cost savings estimated at multi-millions. A new 437,000 sq ft automated fashion distribution centre at Lichfield, acquired in FY2025/26, is expected to increase capacity and speed up deliveries.

When he took over, Stuart Machin inherited a brand with true equity but structural drift. He chose to act on both at once by leveraging retail fundamentals: fixing the product, sharpening the portfolio, investing in the infrastructure required to compete in a digital-first market, and bringing a new management style and a refreshed mindset. Demonstrating greater impact than pure innovation, the retail back-to-basics results are clear: share price has tripled from 130p in 2022 to 350p in 2026, profit is soaring, and the brand ranks #1 in the UK. Also, the space M&S occupies, more expensive than high street brands but cheaper than luxury, with a good value-for-money ratio, has been successfully reclaimed. This positioning is difficult and requires discipline. Few retailers succeed here: Zara may be the best example (see our Exclusive here), and M&S is now another to follow. The only thing Machin’s turnaround plan couldn’t avoid was the April 2025 cyberattack. Despite being highly disruptive and costly, this event is seen as an accelerant for continued transformation, or at least advertised as such.

Credits: IADS (Christine Montard)

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What 60 years of data reveals about how men and women experience leadership

Harvard Business Review

Jul 2026

What 60 years of data reveals about how men and women experience leadership

Harvard Business Review

Jul 2026

What: Sixty years of leadership data show that women executives still face harsher judgment, higher standards, and weaker access to advancement pathways.

Why it is important: This matters because uneven leadership pathways can weaken succession planning, talent retention, and long-term organisational resilience.

The article revisits a Harvard Business Review research series that began in 1965 and has tracked perceptions of women in executive leadership every twenty years. The latest survey, based on responses from 193 senior U.S. executives, shows that attitudes toward women leaders have improved over time, but the experience of advancement has become more divided by gender. Women executives are far more likely than men to believe they are judged more harshly, held to higher standards, and evaluated through systems that are not genuinely meritocratic. The authors describe this as “underground bias”: informal sponsorship, subjective promotion criteria, and unequal access to roles that lead to the top. Women remain more concentrated in staff functions, while operational P&L roles continue to serve as critical pathways to CEO positions. The article argues that organisations already have the tools to address these barriers, including predefined criteria, structured documentation, stronger P&L pipelines, and actionable feedback. The remaining challenge is the willingness to apply them consistently.

IADS Notes: The HBR findings mirror a broader leadership challenge. In October 2025, LEADNetwork reported that women held 39% of senior executive roles in European retail and CPG, but progress remained uneven across functions, reinforcing the article’s point that representation gains do not automatically translate into access to operational leadership. In February 2026, Retail Week noted a record number of new female retail leaders, while still highlighting that only half of retailers had reached the 40% executive target. In January 2026, Reuters showed how Walmart, Amazon, and Target were reassessing DEI initiatives under legal and political pressure, and HR Dive’s April 2026 analysis linked inconsistent DEI commitments to reputational, financial, and talent risks. Together, these sources support the article’s central argument: companies need structured promotion criteria, sponsorship, and measurable inclusion practices to turn visible progress into durable leadership pipelines.

What 60 years of data reveals about how men and women experience leadership

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AI talk is cheap. Value creation is rare.

BCG

Jul 2026

AI talk is cheap. Value creation is rare.

BCG

Jul 2026

What: AI value creation depends less on corporate messaging than on scaled deployment, broad talent development, and reinvested productivity gains.

Why it is important: This is significant because retailers risk mistaking AI investment for AI impact unless they connect deployment to revenue, margins, and productivity.

BCG argues that AI value is far rarer than corporate messaging suggests. Its outside-in analysis of more than 600 US public companies finds that although talking about AI can lift valuation multiples, only 6% qualify as true adoption leaders. These companies outperform peers by 9 percentage points in industry-adjusted total shareholder returns, driven by revenue growth and margin expansion rather than P/E multiple hype.
Leaders create value in three ways. Only 10% mainly use AI to reduce costs. Most (59%) use it to scale what each employee can deliver, reinvesting productivity gains into growth rather than headcount cuts; in fact, AI leaders grow headcount 3 percentage points faster than laggards. Another 21% use AI to build new products, services, and business models. The path to leadership moves from broader toolkits to production-grade deployment and then to the decisive talent gap. Companies risk getting stuck in disconnected pilots, but leaders build AI fluency across the organisation: 13% of employees have AI-related skills, versus 1% at laggards. BCG concludes that AI amplifies strong strategy; it cannot replace it.

IADS Notes: The BCG article’s distinction between AI talk and measurable value closely aligns with recent retail evidence showing that adoption alone does not confer an advantage. In June 2026, BCG found that retailers and CPG companies pulling ahead are those linking AI use cases to EBIT impact, improving data foundations, redesigning operating models, upskilling teams, and governing risk rather than remaining in experimentation. The Wall Street Journal’s December 2025 coverage similarly showed that retail CEOs continue investing in AI despite uneven returns, with value constrained by scaling, privacy, cybersecurity, and workforce-readiness challenges. Bain & Company’s December 2025 survey reinforced the shift from pilots to production, emphasising leadership, workflow redesign, governance, and employee adaptation. BCG’s September 2025 workforce analysis supports the article’s central talent point: AI value depends on systematic upskilling and human-machine integration, not simply specialist hiring. BCG’s November 2025 analysis of the AI-first retailer adds the strategic dimension, showing that retailers such as Walmart and Sephora are using AI for both automation and customer-facing innovation, with scalable infrastructure and organisational change separating leaders from followers

AI talk is cheap. Value creation is rare.

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