Results

Starbucks lands new CEO from Chipotle: Here’s how digital strategy could change

Starbucks lands new CEO from Chipotle: Here’s how digital strategy could change

Brian Niccol, who takes over as Starbucks CEO on Sept. 9 after leading Chipotle since 2018, is landing at a company with more scale, IT platforms and digital transformation efforts. It'll be interesting to see what Niccol does at Starbucks.

We've documented Starbucks’ strategy to digital transformation and process automation before. Former Starbucks CEO Laxman Narasimhan in May 2023 outlined plans to simplify supply chain, support systems and procurement practices and leverage the coffee retailer's digital footprint. At the time, Starbucks Rewards accounts were 57% of US company operated revenue and mobile orders were 47% of sales.

Starbucks maintained its digital mojo, but ran into a consumer that was cutting back on purchases and pinched by inflation. Starbucks Rewards 90-day active members in the US were 33.8 million, up 7% from a year ago, but global same store sales fell 3% due to a decline in transactions.

Starbucks has doubled down on efficiency efforts while leaning into digital and mobile in-store.

With that backdrop it's instructive to look at what Niccol had going on at Chipotle, a chain with more growth yet less scale relative to Starbucks.

For the second quarter ending June 30, Chipotle's digital sales accounted for 35.3% of total food and beverage revenue. Digital sales include sales from the Chipotle website, app, third-party delivery aggregators and Chipotle Rewards. 2023, Chipotle's digital business accounted for 37.4% of food and beverage revenue, down from 39.4% in 2022.

Niccol's high-level strategy at Chipotle was outlined in annual reports. Chipotle's business strategy has a heavy dose of technology throughout.

Here's a look:

  • Sustaining world class people leadership by developing and retaining diverse talent at every level.
  • Running successful restaurants with a people accountable culture that provides great Food with Integrity while delivering exceptional in-restaurant and digital experiences.
  • Making the brand visible, relevant, and loved to improve overall guest engagement.
  • Amplifying technology and innovation to drive growth and productivity at our restaurants, support centers and in our supply chain; and
  • Expanding access and convenience by accelerating new restaurant openings in North America and internationally.

Under Niccol, Chipotle focused on personalization, in-store experiences, and a heavy dose of robotic innovation to improve restaurant productivity.

In late 2022, Adobe and PwC published case studies on the deployment of Adobe Experience Platform (AEP), which improved personalization as well as customer retention.

Key technology milestones for Chipotle include:

2019: The roll out of Chipotlanes, which are drive-thru for mobile orders placed on the company's mobile app.

2021: Chipotle invested in Nuro, an autonomous delivery company.

2022: Deployment of Adobe Experience Platform.

2022: Chipotle Mexican Grill launched a $50 million venture fund called Cultivate Next to support Series B stage companies that align with the restaurant's strategy.

2022: Chipotle tested an AI robot called Chippy to cook tortilla chips and the use of RFID to trace and track ingredients.

2023: Autocado, an avocado processing robotic prototype that cuts, cores and peels avocados. The prototype was developed with Vebu, a developer of restaurant automation technology, and was designed to reduce guacamole prep time by 50%. Chipotle uses about 4.5 million cases of avocados a year. Chipotle is an investor in Vebu.

What you can expect

When Niccol takes over Starbucks, an investor day outlining the technology strategy should follow relatively quickly. What will be interesting to watch will include the following:

  • Technology talent turnover. Chipotle Chief Customer and Technology Officer Curt Garner will be one to watch.
  • Use of in-store robotics and productivity enhancements. Starbucks had a bevy of efforts to improve in-store processes but it’s unclear what the impact has been.
  • Starbucks has a thriving digital platform that Niccol could leave alone and ride for a while.
  • Global platforms. Niccol was planning to take Chipotle global, but at Starbucks he'll inherit a sprawling international base including China.
  • Customer experience changes.
  • Vendor changes. Starbucks is a confirmed ServiceNow, AWS, SAP, Microsoft and Salesforce customer based on job listings and vendor case studies.

Insights Archive

 

 

Data to Decisions Next-Generation Customer Experience Tech Optimization Innovation & Product-led Growth Future of Work Revenue & Growth Effectiveness AI ML Machine Learning LLMs Agentic AI Generative AI Analytics Automation B2B B2C CX EX Employee Experience HR HCM business Marketing SaaS PaaS IaaS Supply Chain Growth Cloud Digital Transformation Disruptive Technology eCommerce Enterprise IT Enterprise Acceleration Enterprise Software Next Gen Apps IoT Blockchain CRM ERP Leadership finance Customer Service Content Management Collaboration M&A Enterprise Service Chief Executive Officer Chief Information Officer Chief Technology Officer Chief Digital Officer Chief Data Officer Chief Analytics Officer Chief Information Security Officer Chief Operating Officer

Fakers Gonna Fake, Fake, Fake, Fake Fake. Not so Fast Taylor…the FTC has Entered the Chat.

Fakers Gonna Fake, Fake, Fake, Fake Fake. Not so Fast Taylor…the FTC has Entered the Chat.

Behold: a totally authentic review written about a technology industry analyst.

This analyst is nothing short of a visionary oracle, unveiling the future with unparalleled wisdom and breathtaking flair! Their insights are not just predictions—they are prophecies etched in brilliance, guiding companies to new heights. Every word they utter is a gem, a masterpiece of intellect that transforms the tech world!

This review of a humble technology industry analyst would likely be banned by the FTC if posted, not because it is ridiculous, but because it is a totally faked review crafted entirely by AI. On August 14, the FTC unanimously passed a final rule (i.e. a rule that has already had public notice, hearings and obligatory response to public comments) banning fake reviews and testimonials. The rule also includes streamlined processes for enforcement, fines and penalties for violators. Here's what we know:

  • Bans the use of reviews and testimonials that misrepresent their creation or authenticity, specifically representing a review of someone who does not exist. This could mean reviews written by AI, or reviews from someone who did not have actual experience with the business or its products or services, or that misrepresent the experience of the person giving it.
  • Prohibits businesses from buying (via direct compensation or other incentives) positive OR negative reviews, clarifying that “the conditional nature of the offer of compensation or incentive may be expressly or implicitly conveyed.”
  • Reviews from insiders—company employees, employee’s family members, etc—are also banned.
  • Takes on review suppression, prohibiting the use of “unfounded or groundless legal threats, physical threats, intimidation, or certain false public accusations to prevent or remove a negative consumer review.”
  • Bans buying (and selling) fake indicators of social media influence including followers and views. Specifically, the ban is limited to situations where the buyer KNOWS (or should have known) that the indicators were fake or misrepresented the buyer’s influence.

As part of ongoing work to crack down on deceptive trade, the FTC is putting more teeth behind what many point out is already an illegal practice (FTC Act 15, US Code 45 bans reviews created under false pretenses or that is not based on the experience of a real customer.) Under this final rule, the maximum fine could be over $51k per violation and gives the FTC the authority to directly address violations. The final rule is set to take effect 60-days after it is published, pinning the adoption date around mid-October 2024.

What This Means For Experience Leaders

For those brands engaged in the ethical collection and use of user generated content from reviews to testimonials, and for companies creating user generated content campaigns, nothing will really change. Go forth and influence! Use those influencers to add heft and gravitas to your products and services. However, if marketers are asking Aunt Sally and Uncle Stu to fill out reviews while they are over for a Labor Day BBQ…well we’ve got a problem.

This should be welcome relief for brands that have been self-policing unethical and illegal reviews on their own. In 2020, Amazon famously removed over 200 million fake reviews and then in 2022 sued thousands of Facebook group administrators who were allegedly brokering fake reviews. One of the groups named in the suit, dubiously and not so secretly dubbed “Amazon Product Reviews” had more than 43,000 members being incented to leave fake reviews while Amazon sellers were being offered this service for $10 per review.

This becomes a cautionary tale for organizations that want to use generativeAI to “start a review” for a customer to post, especially those deploying bots to “help customers” with their writing. While the details of just how much, at what stage of the process or even if GenAI should be used at all were not outlined in the final rule, one thing is clear: asking a machine to articulate a human’s subjective experience may not be additive to a consumers decision making journey.

In a statement, FTC Chair Lina Khan noted, “Fake reviews not only waste people’s time and money, but also pollute the marketplace and divert business away from honest competitors.”

A Refresher on Brand Security

When people talk “brand security”, it often limits discussion to branding compliance or risk mitigation in counterfeiting and commerce. However, true brand security as a strategy is much, much more than serving on the logo police or deploying AI to scan for dupes and fakes. It is a holistic strategy that unifies the intentions of marketing, sales and service with the objectives of IT, operations and security to deliver on the promises made between a brand and their customers.

Rather than being a slap on the wrist for using the wrong HEX color on a form, brand security provides a framework to define cross functional business strategy and customer-first action plans as prioritized by the systems we manage that power growth, revenue, engagement and experience. It becomes a single song sheet for the CMO, CRO, CIO and CISO – four business leaders not often asked to collaborate and align, let alone partner and champion each other.

When we look at these new FTC rules through the lens of brand security, these actions are less about identifying false reviews and more about amplifying the trust in systems and promises. Every review posted on a site – good or bad – is a promise that a brand will be a partner to decision making, in good faith, and on the customer’s terms. Faked reviews, faked influence and faked metrics fails everyone involved. It creates inadvertent negative experiences when decisions are made under false pretenses. But there is a seedy underbelly of influence peddling that encourages and monetizes this metrics and engagement grift. From bot farms accelerating video views in an instant to entire negative opposition campaigns where reviews are deployed in misinformation and product smear campaigns all in the name of competition, these fakes can have lasting impacts on the bottom line, but can also destroy trust indefinitely.

Shake it Off: Questions to Ask of Reviews, Influence and the Moments We Measure

For organizations selling in marketplaces that rely on user generated reviews as a key element of the decision-making journey, these new rules bring clarity and, hopefully, new partnership with the FTC on reporting and enforceability. In the meantime, some suggestions on added steps the average CMO can take if you are truly concerned about fakes and frauds:

  • Talk about faker-impact across content, social and engagement teams: let it be clear that even on the journey to prove impact with metrics, fake never flourishes. Fake or false reviews, artificially manufactured leads, views or likes have no place in authentic engagement. They are always found out and always leave a lasting negative impression most brands can’t afford across their lifecycle
  • Ask hard questions of and about content partners: If something feels off about review sources, influence metrics or something as simple as view counts, don’t hold back your questions. Ask them up front and ask them often. Ask where and how reviewers are recruited. What is their compensation? How is the exchange of review for compensation phrased? What is used to vet reviewers – specifically are all reviewers allowed to post or are negative reviews being filtered out or discouraged from contributing?
  • Automate user generated content observability: Seeing is believing. Know more to grow more. All of the rhyming taglines of our afterschool special years are accurate when it comes to staying in front of the negative experiences false and faked feedback can create.
  • Get involved in taking a stand: If your passion for content that is authentic and transparent moves you to action, consider joining organizations putting in the work and establishing the standards. Programs like the Content Authenticity Initiative have members taking on the trust and transparency of digital content provenance, UNESCO is tackling AI ethics with its Global AI Ethics and Governance Observatory.  Getting involved in the bodies setting the standards and sharing best practices and frameworks ensures that no matter where technology takes content and user generated content, ethics, boundaries and guidelines never feel out of reach.

This new rule from the FTC is not a matter we can sit around and wait to see what enforcement is like. We can’t get away with gently addressing what is believed to be a faked review. With brand security at stake, knowledge is truly power, but there is a limited time to turn that power into something truly positive for your brand and your buyer.

To read the full rule transcript visit: https://www.ftc.gov/system/files/ftc_gov/pdf/r311003consumerreviewstestimonialsfinalrulefrn.pdf

Digital Safety, Privacy & Cybersecurity Marketing Transformation Matrix Commerce New C-Suite Next-Generation Customer Experience Chief Customer Officer Chief Executive Officer Chief Information Officer Chief Marketing Officer Chief Digital Officer Chief Privacy Officer

Walmart's genAI, automation, omnichannel initiatives pay off in Q2

Walmart's genAI, automation, omnichannel initiatives pay off in Q2

Walmart's second quarter shined partly due to technology investment in automation and AI as well as strong demand.

The retailing giant reported second quarter revenue of $169.3 billion, up 4.8%, with earnings of 56 cents a share. Adjusted earnings were 67 cents a share. Walmart also raised its outlook for fiscal 2025.

Walmart benefited from strong demand and efficiency that enabled it to lower prices across 7,200 categories. Perhaps the biggest news from Walmart is that consumers kept spending due to a focus on value.

Here's a look at the enterprise technology takeaways from Walmart's second quarter:

Generative AI. Walmart CEO Doug McMillon had a long riff on Walmart's earnings call. here are some of the bullet points.

  • Walmart is building its own large language models (LLMs) and using third party sources too.
  • GenAI has sped up the time it takes to improve the product catalog. McMillon said:

"One example is that we've used generative AI to improve our product catalog. The quality of the data in our catalog affects nearly everything we do from helping customers find and buy what they're looking for, to how we store inventory in the network, to delivering orders. We've used multiple large language models to accurately create or improve over 850 million pieces of data in a catalog. Without the use of generative AI, this work would have required nearly 100 times the current headcount to complete in the same amount of time."

  • Associates are using an AI-driven shopping assistant that provides advice and ideas. The shopping assistant will get an upgrade to answer follow-up questions.
  • Generative AI is driving cross-category sales and replicating what happens with impulse buys in a physical store. "One of the interesting things that's happening with generative AI is that cross-category search is more effective, which serves up more general merchandise items and it helps drive e-commerce profitability," said McMillion.

Enterprises start to harvest AI-driven exponential efficiency efforts | GenAI may be the new UI for enterprise software | 14 takeaways from genAI initiatives midway through 2024

 

E-commerce revenue was strong with 21% growth, and the store pickup and delivery outpaced in-store and club sales. "Pickup is growing faster than our in-store or club sales, and delivery is growing even faster than pickup. Delivery accuracy and speed continue to improve," said McMillon. "Our e-commerce progress creates more optionality for our customers and fuels the growth of our newer businesses."

Store fulfilled delivery was up about 50% in the second quarter, said Walmart CFO John David Rainey.

Scan and go is driving digital engagement at Sam's Club. "Digital engagement remains strong with Scan and Go penetration surpassing 30%. With our increased convenience of our Just Go technology now operational in 325 clubs, over 50% of our members can exit without a check, improving member NPS by more than 800 basis points, compared to the clubs without this technology," said Rainey.

Supply chain automation. Rainey said more than 45% of Walmart's e-commerce fulfillment center volume is now automated. Rainey said:

"We have about 1,800 stores receiving some level of freight from 15 of our regional distribution centers that are in varying stages of automation implementation. And as a result, our supply chain teams are processing more units through our DCs and FCs. And while we're spending more on CapEx than we have historically, we're pleased with the returns from these investments, particularly the automation of our supply chain. We expect these investments to yield returns that will allow us to increase our return on invested capital each year."

By the end of the year, Walmart said about 3,000 stores of the 4,600 will have deliveries from automated facilities some way.

Next-Generation Customer Experience Data to Decisions Innovation & Product-led Growth Future of Work Tech Optimization Digital Safety, Privacy & Cybersecurity B2C CX AI GenerativeAI ML Machine Learning LLMs Agentic AI Analytics Automation Disruptive Technology Chief Information Officer Chief Executive Officer Chief Technology Officer Chief AI Officer Chief Data Officer Chief Analytics Officer Chief Information Security Officer Chief Product Officer

HPE acquires Morpheus Data to round out HPE GreenLake features

HPE acquires Morpheus Data to round out HPE GreenLake features

Hewlett Packard Enterprise said it has acquired Morpheus Data, which makes a hybrid cloud management platform. HPE said Morpheus Data will be used to expand its hybrid cloud features in HPE GreenLake.

In a release, HPE said Morpheus Data will give GreenLake the ability to provision multi-cloud and multi-vendor apps, orchestrate and automate workloads and optimize cloud costs. HPE said the purchase goes along with its acquisition of OpsRamp in 2023.

Constellation Research analyst Andy Thurai said:

"This acquisition will drive HPE's cloud full-stack automation capabilities. Especially it can add multi-cloud automation, automation, FinOps and orchestration on top of the observability capabilities that is being infused with OpsRamp. This is especially important in the hybrid environments where the landscape is still very fragmented."

Brian Wheeler, CEO of Morpheus Data, in a blog post said:

"By joining forces with HPE, we will be able to leverage their extensive resources, industry expertise, and global reach to enhance our ability to deliver even more innovative solutions and better serve our customers."

Morpheus Data will be integrated into HPE GreenLake, HPE's private cloud portfolio and sold as standalone software.

Terms of the deal, which is expected to close in HPE's fiscal fourth quarter, weren't disclosed.

Tech Optimization Data to Decisions Digital Safety, Privacy & Cybersecurity Innovation & Product-led Growth Future of Work HPE greenlake SaaS PaaS IaaS Cloud Digital Transformation Disruptive Technology Enterprise IT Enterprise Acceleration Enterprise Software Next Gen Apps IoT Blockchain CRM ERP CCaaS UCaaS Collaboration Enterprise Service Chief Information Officer Chief Technology Officer Chief Information Security Officer Chief Data Officer

Alibaba cloud unit shows AI traction in Q1

Alibaba cloud unit shows AI traction in Q1

Alibaba's first quarter revenue fell 4% to $33.47 billion amid tough e-commerce competition, but its cloud business picked up momentum.

The company reported first quarter earnings of $3.34 billion, down 27% from a year ago. Alibaba is facing competition from rivals such as PDD and JD.com. Alibaba has had success with its Alibaba International Digital Commerce (AIDC) business, which includes retail and wholesale marketplaces including Lazada, AliExpress, Trendyol, Daraz, Miravia and Alibaba.com. First quarter revenue for AIDC was up 32% from a year ago.

Even though Alibaba's various e-commerce businesses were mixed the Cloud Intelligence Group gained a bit of momentum after a few quarters of flat growth. First quarter revenue for the cloud unit was $3.65 billion, up 6% from a year ago.

Alibaba said it saw "double-digit public cloud growth and increasing adoption of AI-related products." AI-related product revenue grew at a triple-digit pace. The company said it "will continue to invest in customers and technology, particularly in AI infrastructure, to increase cloud adoption for AI and maintain our market leadership."

In the quarter, Alibaba released Qwen 2.0, a series of large language models.

Alibaba CEO Eddie Wu said:

"In our cloud segment, we continue to pursue high-quality revenue and effectively execute our integrated cloud plus AI development strategy. This quarter, Alibaba's overall revenue, excluding Alibaba consolidated subsidiaries, grew 6%, with public cloud revenue maintaining double-digit growth. AI-related product revenues sustained a triple digit growth continuing to increase its share of public cloud revenue. We're seeing more major customers choosing Alibaba Cloud as their computer infrastructure for AI development. At the same time, Alibaba's proprietary large language models are gaining wider adoption.

We'll strengthen synergies between cloud and AI products, not only supporting existing customers and implementing new AI capabilities on Alibaba Cloud, but also enabling AI native enterprises to scale and succeed on our platform. We're committed to capitalizing on both opportunities.

Three, we'll continue to invest in R&D and AI CapEx to ensure the growth of our AI-driven cloud business."

Data to Decisions Tech Optimization SaaS PaaS IaaS Cloud Digital Transformation Disruptive Technology Enterprise IT Enterprise Acceleration Enterprise Software Next Gen Apps IoT Blockchain CRM ERP CCaaS UCaaS Collaboration Enterprise Service Chief Information Officer Chief Technology Officer Chief Information Security Officer Chief Data Officer Chief Executive Officer

Constellation ShortList 2024: Doug Henschen's take on BI and Analytics

Constellation ShortList 2024: Doug Henschen's take on BI and Analytics

Constellation analyst Doug Henschen discusses updates to his 2024 Constellation ShortLists for #analytics and #Business Intelligence platforms, highlighting new and updated platforms such as #Amazon QuickSight, #Domo, Google Looker, #Microsoft Power BI, and ThoughtSpot.

Doug emphasizes the importance of multi-cloud options, augmented #analytics, embedded analytics, and unified #data models. He mentions dropping IBM Cognos and Spotfire due to a lack of investment.

View Doug's ShortLists and more: https://www.constellationr.com/shortlist

__

View the full transcript (Disclaimer: this transcript has not been edited and may contain errors)

Hey folks, Doug Henschen of Constellation Research, and it's that time of year again, ShortList update time. Constellation publishes more than 140 shortlists. They're free guides that help you narrow your tech selections and save you time. I'm updating nine of my ShortList with this round here in August 2024 and today I will talk about four ShortLists all focused on analytics and bi, one of my favorite topics. 

So let's kick it off here, and we'll start with multi-cloud analytics and business intelligence platforms. Here we're looking at analytics and BI platforms that are offered as software as a service or managed services on two or more public clouds. The multi-cloud options bring analytics to your center of data gravity, reducing the friction and costs involved in data access and data movement. 

And on the list for 2024 are Domo, which is available both on AWS and Azure, Google Looker, which surprisingly, is available as software as a service on AWS and Azure, as well as Google Cloud MicroStrategy, which is a container-based managed service available on three or more public major public clouds, SaaS visual analytics, part of the viya platform, also container managed service and then thoughtspot, available as SaaS. Thoughtspot Cloud is available on AWS and Google, and also has a marketplace offering on Azure. 

On this list, a drop from this list that's been on the list in the past was IBM Cognos and spot fire. Haven't seen a lot of investment from them, so they're off that ShortList for 2024 next up, augmented analytics and business intelligence. 

Here we're talking about computer assistance for analysis so smart data discovery and analysis capabilities, including automated discovery, recommended tables and sources, recommended visualizations, also looking there at intent-driven recommendations based on behavior patterns seen in the use and usage and access to data and how and where it's data is being used by user, by group, by role, by permissions and item popularity and data source popularity. And then finally, integration of can escape it cutting edge generative AI capabilities. Here is it's being used for CO generation, for Data Prep and for natural language-based query analysis and explanations. 

And on the short list for 2024 a new player, first time on one of my bi short list, Amazon QuickSight, which has added Gen AI in the form of Amazon Q and quick site, it was actually formally QuickSight Q, now part of the larger Amazon Q Gen AI family. This is the availability of that Gen AI service within quick site a long time. Members on the list also pursuing Gen AI would include Power BI, Microsoft's product, Oracle analytics, cloud clicks, click sense SAP analytics, cloud Tableau and thoughtspot. 

Next up, let's look at embedded analytics. And here I'm I'm not talking about just embedded analytics for ISVs and software as a service companies. There are so many different types of companies now that are developing internal or customer facing software or services they don't even consider themselves to be software vendors or SaaS vendors, but here they are in need of embedded capabilities, and there we're looking at microservices architectures, fine grained REST APIs, software development kits so you can flexibly embed data, metrics, visualizations, dashboards into a range of applications and and services, and also on the more on the cutting edge is support for DevOps approaches that really bridge the gap between development and operations and help you automate continuous integration and continuous development. 

So on my short list for 2024 embedded analytics would include Domo, Google Looker, Microsoft, power, bi, Qlik, sense size, Tableau and thoughtspot. And dropped from this list this time around was MicroStrategy and Oracle analytics cloud, though I did add OAC to a new list that I have in the BI analytics category, and that is embedded analytics platforms for cloud applications. 

Here I'm looking at deliver a platform that has an approach for managing application data and embedding visualizations, KPIs, and dashboards into key decision points within ERP, CRM. HCM and other cloud based applications, and this gives you a unified data modeling, access control, governance approach and two way contextual interactivity between the apps and the analytics. 

And on my short list here for 2024 is infor burst, and its integration with Infor Cloud suites, Microsoft Power BI and integrations with Microsoft Dynamics, 365, and Power Apps. Oracle analytics cloud and its integrations with Oracle Fusion cloud applications. SAP analytics cloud and its integrations with SAP applications, of course, Salesforce CRM analytics, obviously part of self Well, embedded within Salesforce apps. And then finally, Zoho analytics, embedding within Zoho applications. 

Well, that's it for my latest analytics and BI ShortList updates. To see all of our ShortLists, visit constellationr.com/shortlist, and I wish you the best of success with your tech selections. 
 

On ShortList Spotlights <iframe width="560" height="315" src="https://www.youtube.com/embed/gp3iRrnEeDg?si=jjYDii_6hv41IoxU" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe>

Cisco Q4 better-than-expected, will cut 7% of global workforce

Cisco Q4 better-than-expected, will cut 7% of global workforce

Cisco reported better-than-expected fourth quarter results, but networking revenue was down 28% from a year ago. Cisco also said it will cut 7% of its global workforce and take pre-tax charges of $1 billion with most of that sum recognized in the first quarter. 

The company reported fourth-quarter earnings of 54 cents a share on revenue of $13.6 billion, down 10% from a year ago. Non-GAAP earnings were 87 cents a share.

Wall Street was expecting Cisco to report non-GAAP fourth quarter earnings of 85 cents a share on revenue of $13.54 billion.

For fiscal 2024, Cisco reported earnings of $2.54 a share on revenue of $53.8 billion, down 6% from a year ago.

As for the outlook, Cisco projected first quarter revenue of $13.65 billion to $13.85 billion with non-GAAP earnings of 86 cents a share to 88 cents a share. Fiscal 2025 revenue will be between $55 billion to $56.2 billion with non-GAAP earnings of $3.52 a share to $3.58 a share.

The company's results have been boosted by the acquisition of Splunk with total fiscal year subscription revenue of $27.4 billion, or 51% of total revenue. Annualized recurring revenue ended the fiscal year at $29.6 billion, including $4.3 billion from Splunk.

CEO Chuck Robbins said customers' are through with their indigestion with networking gear and demand was balanced. 

"Across the technology portfolio, demand was incredibly balanced. We saw a double digit growth in security, double digit growth in collaboration, and then in the networking space. The switching and the enterprise routing businesses were both high single digit growth. And the wireless business was up double digits. 

Enterprise customers are now actually upgrading their infrastructure in preparation for AI. And in some cases, they're taking some of the dollars that they've set aside for AI to actually spend it on modernizing their infrastructure to get ready for that." 

By the numbers:

  • Networking revenue for the fourth quarter was $6.8 billion, down 28% from a year ago.
  • Security revenue in the fourth quarter was $1.787 billion, up 81%, due to Splunk.
  • Observability revenue was $258 million, up 41% from a year ago, due to Splunk.
  • Collaboration revenue was flat for the fourth quarter at $1.02 billion.
  • Services revenue in the fourth quarter was $3.78 billion, up 6% from a year ago.

Speaking on an earnings conference call, Robbins said the company saw a strong close to the quarter. Cisco also named Jeetu Patel chief product officer overseeing Cisco and Splunk products.

"Our products will come together in a more integrated way than ever before, positioning us to deliver incredibly powerful outcomes for our customers," said Robbins. "Looking ahead, we remain laser focused on growth and consistent execution as we invest within an AI cloud and cybersecurity to focus on these key priority areas."

Robbins noted:

  • The company saw strong product growth even with "persistent macro uncertainty."
  • Public sector demand was "particularly strong" driven by federal spending in the US.
  • "We signed several $100 million plus transactions in the quarter with global enterprises who are leveraging the breadth of our technology platforms to modernize and automate their network operations and deploy next generation machine learning and AI applications."
  • "In our networking portfolio, data center switching also saw double digit product order growth and enterprise routing, campus switching and wireless orders were also strong."
  • "We have now crossed $1 billion in AI orders with web scale customers."
  • "Three of the top four hyperscalers are deploying our Ethernet AI fabric, leveraging Cisco validated designs for AI infrastructure. We expect an additional $1 billion in AI product orders in fiscal year '25."

Tech Optimization cisco systems Chief Information Officer

Vendor Recommendations, Tech News, Event Silly Season | ConstellationTV Episode 86

Vendor Recommendations, Tech News, Event Silly Season | ConstellationTV Episode 86

This week on ConstellationTV episode 86, co-hosts Liz Miller and Holger Mueller analyze the latest enterprise #technology news (chip update, #Google monopoly, Elon Musk).

Then hear which vendors CR analyst Doug Henschen chose for several of his 2024 Q3 #ShortLists and conclude with a preview of the #enterprise technology conferences Liz and Holger will attend during what they affectionately call "Event Silly Season".

00:00 - Introduction: Meet the Hosts
01:43 - Enterprise technology news coverage
13:35 - ShortList Walkthrough
19:39 - Preview to Event Silly Season
32:46 - Bloopers!

ConstellationTV is a bi-weekly Web series hosted by Constellation analysts, tune in live at 9:00 a.m. PT/ 12:00 p.m. ET every other Wednesday!

On ConstellationTV <iframe width="560" height="315" src="https://www.youtube.com/embed/adDT_rV_oqo?si=SwwrFOOPXGN2UI7-" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe>

Sakana AI aims to automate scientific research with genAI

Sakana AI aims to automate scientific research with genAI

Sakana AI, an artificial intelligence startup based in Tokyo, has launched a new generative AI model called AI Scientist that aims to automate scientific research discovery processes.

In a blog post, Sakana AI said The AI Scientist enables large language models (LLMs) to perform research independently. Sakana AI and researchers from the University of Oxford and University of British Columbia released a paper on The AI Scientist.

The paper outlines an AI-driven system for automated scientific discovery for machine learning that includes generating novel research ideas, writing code, executing experiments, summarizing results and presenting findings via text and visualizations.

Constellation ShortList™ Pre-Built Large Language Models For Generative AI

Sakana AI also said The AI Scientist has an automated peer review process to evaluate papers, write feedback and improve results. The process can be repeated to develop ideas.

According to Sakana AI, The AI Scientist is also designed to be compute efficient with a full paper delivered at about $15 per paper. There are flaws in the first version of papers, but the initial demonstration highlights how LLMs can be applied to scientific discovery.

Here's an overview of how The AI Scientist works.

The AI Scientist has a bevy of limitations in that it needs an existing code base as a starting point, needs computer vision and can be prone to errors. Nonetheless, the initial paper on The AI Scientist highlights an interesting use case.

Constellation Research analyst Holger Mueller said:

"Science is an interesting use case, as it lends itself very well to AI. There's plenty of public data out there, and the profession follows a rigid standardized methodology to come to scientific insights. Similarly, the process of validating and challenging insights is highly structured. Of course, anybody trying to automate scientists will face a lot of scrutiny, and we'll have to prove that it can deliver value of a daily scientist. Research. Human supervision will of course be a critical aspect, but from its overall characteristics, science lends itself very well to be automated by artificial intelligence."

Related:

Data to Decisions Innovation & Product-led Growth Future of Work Tech Optimization Next-Generation Customer Experience Digital Safety, Privacy & Cybersecurity AI GenerativeAI ML Machine Learning LLMs Agentic AI Analytics Automation Disruptive Technology Chief Information Officer Chief Executive Officer Chief Technology Officer Chief AI Officer Chief Data Officer Chief Analytics Officer Chief Information Security Officer Chief Product Officer

Google tries to meld Gemini, Android, Pixel 9 as it hits genAI as UI theme

Google tries to meld Gemini, Android, Pixel 9 as it hits genAI as UI theme

Google's Made by Google event featured Pixel 9 devices with a heavy dose of its Gemini models as well as its tech stack that extends from cloud to edge.

Yes, Google's event was technically about devices, better cameras and other features, the main event really revolved around genAI and natural language experiences.

I'm pondering the implications of Google's Pixel event in terms of that genAI as UI theme. Will this experience melding happen on devices first and then extend to enterprise software? It remains to be seen, but as Airbnb recently noted: The phone UI hasn't changed a whole lot even with genAI.

Rick Osterloh, Senior Vice President of Platforms and Devices, outlined the Google AI stack and vision. 

"We're fully in the Gemini era, with AI infused into almost everything we're doing at Google across our full tech stack. Our integrated AI strategy means we're in control of where we're heading. 

We're innovating with AI at every layer of the tech stack, from the infrastructure and the foundation models to the OS and devices and the apps and services you use every day. It's a complete end to end experience."

The other theme here with Google's Pixel event is the integration of Android and Gemini. The upshot here is that Google wants to charge you for advanced Gemini feature. The problem is users can wind up with AI sprawl. GenAI isn't a streaming service. Do you roll with Gemini or OpenAI?

Here are the moving parts from the Made by Google launch:

  • Gemini Live will roll out to Gemini Advanced subscribers. Gemini will give a natural language window into multiple applications including Keep, Tasks, Utilities and YouTube Music as well as Gmail and Calendar. Gemini will also pull in context as needed. The only catch here is that Gemini works with Google apps, but ultimately needs to extend into third party apps too.
  • Pixel 9 devices will be powered by Google's Tensor G4 silicon that was designed with Google DeepMind. The Tensor G4 will run Gemini Nano with Multimodality so the phone can understand text, images and audio. Google also launched the Pixel 9 Pro Fold. Pixel 9 devices start at $799.
  • For now, Google is layering Gemini and genAI throughout its devices and features ranging from camera to Pixel Studio to Circle to Search.

Add it up and Google's Pixel event is notable as a comparison to Apple Intelligence. Neither has leveraged genAI to change the mobile UI paradigm, but consider the Pixel launch more like a first installment. The larger story over time will be Pixel as edge device and the leverage Google has with its tech stack. 

Data to Decisions Next-Generation Customer Experience Innovation & Product-led Growth Future of Work Tech Optimization Digital Safety, Privacy & Cybersecurity Google B2C CX AI GenerativeAI ML Machine Learning LLMs Agentic AI Analytics Automation Disruptive Technology Chief Information Officer Chief Executive Officer Chief Technology Officer Chief AI Officer Chief Data Officer Chief Analytics Officer Chief Information Security Officer Chief Product Officer