| Constellation Research

Cisco's Q3 posts strong networking gear sales, ups outlook

Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

Cisco reported better-than-expected third quarter earnings and raised its fourth quarter outlook as its networking portfolio revenue surged 29% from a year ago.

The company reported fiscal third quarter earnings of 78 cents a share on revenue of $14.6 billion, up 14% from a year ago. Non-GAAP earnings were $1 a share. Wall Street was expecting Cisco to report a third quarter adjusted profit of 97 cents a share on revenue of $14.38 billion.

Cisco projected fourth quarter revenue growth of 14% to 16% with non-GAAP earnings of $1.05 a share to $1.07 a share. For fiscal 2023, Cisco projected revenue growth of about 10%. For fiscal 2024, Cisco said non-GAAP earnings will outpace modest revenue growth due to strong comparisons.

Speaking on an earnings conference call, CEO Chuck Robbins said the company's transition to software is accelerating with software revenue checking in at $4.3 billion in the third quarter. Forty two percent of Cisco's revenue is software.

Robbins also said that it has a big opportunity in security, and it will outline new products at its Cisco Live conference. Robbins also said Cisco is moving rapidly to leverage generative AI in its own products.

Cisco's results were helped in part by moves last year to simplify its supply chain, so it had the parts to build its networking gear. Lead times for product shipments have improved 40% over the last two quarters. Going forward, Cisco customers are likely to digest systems that have been bought.

"As we expected, the actions we took in supply chain last year have paid off," said Robbins. "Customers continue to invest in key technologies core to their overall strategy. We will end the fiscal year with double our normal backlog."

Cisco's networking unit was the star of the quarter with revenue up 29% from a year ago. Demand was strong across multiple switch and router products. Cisco's Secure, Agile Networks unit delivered third quarter revenue of $7.55 billion. Secure, Agile Networks consists of hardware and software for switching, enterprise routing, wireless and compute products. Robbins said Cisco is in a much better position to play a role in AI workloads than it was with the cloud transition.

Cisco saw gains in other product lines except for collaboration sales, which fell 13% from a year ago.

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SoftwareOne acquires Beniva Consulting, adds ServiceNow services

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

SoftwareOne Holding AG, which provides software and cloud services, said it has acquired Beniva Consulting Group to expand into ServiceNow implementations. SoftwareOne's cloud and software services have revolved around Microsoft and SAP Cloud deployments.

With the purchase, SoftwareOne enters the services market for ServiceNow Configuration Management Database (CMDB), IT and operations management (ITOM), cloud advisory and application services. SoftwareOne already provides IT asset management services (ITAM).

ServiceNow, which is holding its Knowledge 2023 conference this week, has been expanding its total addressable market via a platform that accelerates value from ERP systems. Beniva, founded in 2016 and based in Calgary, has been riding that workflow and automation wave as a ServiceNow partner.

According to SoftwareOne, Beniva will bring 75 cloud technology experts and directors to the company's software and cloud services practice. The Beniva purchase will also expand SoftwareOne's portfolio of services, increase its ITAM addressable market from $2 billion to $7 billion and be accretive to margins. Terms of the deal weren't disclosed.

Beniva derives 60% of its revenue from ServiceNow deployments and has practices in process automation with RPA (robotics process automation) with UIPath, Microsoft's Power Automate and ServiceNow RPA.

SoftwareOne also reported its first quarter results. The company said first quarter revenue was CHF 239.4 million ($266.45 million), up 4.5% from a year ago, with adjusted EBITDA of CHF 39.6 million ($44.1 million). The company also said it was implementing a program to deliver CHF 50 million in annual savings as well as a CHF 70 million share buyback program. SoftwareOne added that up to 50% of cost savings a year will be re-invested in strategic growth areas.

Brian Duffy, CEO of SoftwareOne, joined the company in early May and said he will be spending the next few weeks meeting the global team. Duffy was most recently President of Cloud for SAP and responsible for scaling "RISE with SAP" to move customers to the cloud.

Duffy said SoftwareOne has a big opportunity in cloud and will focus on customer success and enhancing partner relationships.

SoftwareOne reiterated its 2023 outlook, which calls for double-digit revenue growth and adjusted EBITDA margin of 24% to 25% of revenue.

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ServiceNow outlines generative AI roadmap, bring your own LLMs

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

ServiceNow said customers will be able to bring their own large language models to its platform, but the real returns are likely to come from industry and customer specific generative AI models.

CJ Desai, ServiceNow's Chief Product Officer, outlined the company's platform roadmap. ServiceNow's latest Utah release is live now with Vancouver scheduled for September. A Washington DC release lands in 2024.

"GenAI is a catalyst for our platform. It's an augmentation of our platform that's good for our customers," said Desai, speaking at ServiceNow's Financial Analyst Day on Tuesday. "Customers can bring their own LLM and we will provide you with a connector just like we integrate with systems of record. The value for our customers is domain specific LLMs for our workflows and use cases." Indeed, ServiceNow said it would use Nvidia infrastructure to develop LLMs for its platform.

ServiceNow expands finance, supply chain process, workflow automation | ServiceNow Offers AI-Powered Service Operations for Modern ITOps

In September, ServiceNow's Vancouver release will include generative AI enhanced Virtual Agent Q&A experiences, summarized search results and accelerated configuration and extension tools. In 2024, the Washington DC release will include complete self-service, automated knowledge creation for agents and generative AI for admins and builders.

Desai said ServiceNow's platform capabilities built on its data model and code base speeds up innovation and enables the company to use generative AI throughout its portfolio. In addition, ServiceNow has invested in AI for years, often through acquisitions. ServiceNow has been expanding into new use cases, processes and industries such as financial services, telecom and media, manufacturing, public sector, healthcare and life sciences to increase its total addressable market.

ServiceNow CEO Bill McDermott said the company "is the center of the great reprioritization in the enterprise." McDermott said ServiceNow has evolved from mostly talking to CIOs to CEO-level conversations. "We're getting market pull from CEOs," said McDermott. "Just a few years ago they were trying to figure out what ServiceNow does. They want collaboration. They want integration. With AI, the IT strategy is the business strategy."

McDermott added that the company is landing more CEO conversations because enterprises are looking to consolidate tech vendors to take costs out. "Point solutions have gone out of favor and platforms, especially if cloud based, are ruling the day," he said.

Indeed, those CEO conversations are part of the reason why ServiceNow is focusing on finance and supply chain processes at Knowledge 2023. Those processes include a lot of manual work that generative AI can replace and automate. In addition, CEOs are looking to streamline ERP processes, but migrations take too long to truly transform to a clean core ERP instance.

ServiceNow is looking to transform and mitigate the risk with ERP migrations. Nevertheless, the company frequently noted that it is not replacing ERP but building a force multiplier to make systems of record more productive.

Other items of note from the Financial Analyst Day:

ServiceNow operates its own data centers and has 34 globally to date.
Executives demonstrated new workflows for finance and supply chain as well as generative AI capabilities.
Once ITSM is live at an enterprise, additional ServiceNow applications deliver time to value faster with implementations that take anywhere from 8 weeks to 16 weeks.
The company referenced an average selling price uplift as it sells more of the platform to enterprises. Desai said ServiceNow is delivering strong value.
66% of ServiceNow's existing customer base spent incremental dollars with the company in 2022.

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Tableau Moves Beyond Dashboards and the Self-Service Glory Days

Doug Henschen

Former Vice President and Principal Analyst
Constellation Research

Doug Henschen is former Vice President and Principal Analyst where he focused on data-driven decision making. Henschen’s Data-to-Decisions research examines how organizations employ data analysis to reimagine their business models and gain a deeper understanding of their customers. Henschen's research acknowledges the fact that innovative applications of data analysis requires a multi-disciplinary approach starting with information and orchestration technologies, continuing through business intelligence, data-visualization, and analytics, and moving into NoSQL and big-data analysis, third-party data enrichment, and decision-management technologies. Insight-driven business models are of interest to the entire C-suite, but most particularly chief executive officers, chief digital officers,…...

Tableau Pulse, Tableau GPT and a new VizQL Data Service will enable customers to deliver metrics and insights, natural language explanations, and event and workflow triggers in the context of work.

Tableau was founded 20 years ago, and in its earliest days it disrupted the market with data visualization. It helped spark a movement toward self-service dashboards that changed business intelligence. Flash forward to 2023 and it’s not uncommon to hear comments about dashboards being dead.

At its annual user conference, held May 9-11 in Las Vegas, Tableau introduced a battery of new capabilities that will help customers deliver insights in the context of work rather than through dashboards. It’s important to note that Tableau is going beyond dashboards, not leaving them behind, as the death of dashboards has been greatly exaggerated. But with the announcements of Tableau Pulse, Tableau GPT, and the VizQL Data Service the company is pursuing the fast-growing embedded analytics trend that’s all about delivering concise insights where people work rather than through dashboards and reports.

Tableau Pulse: A Stethoscope for Business

Tableau Pulse, as pilot tested by John Lewis Partnership, blends analyst-definedmetrics, business context, sparkline visualizations and generative AI explanations in card views that can be pushed to targeted users through email, Slack, or web landing pages.

Organizations have been investing in analytics and BI for a long time, yet deployments too often suffer from low adoption. Tableau Pulse, expected to preview in Q4, is a cloud-based service that starts with an-AI based understanding of how individual users and teams interact with data and Tableau analytics. Importantly, Pulse introduces a metrics layer and simple authoring user interface (UI) that enables analysts to define business measures and add business context, such as whether an increase or decrease in a particular metric is a good or bad thing. To avoid the cold start challenge, Pulse is said to leverage existing curation and configuration of measures already set up in Tableau.

The Pulse UI is also used to author simple cards (shown above) that combine sparkline visualizations and concise, natural language descriptions. These descriptions, which will be generated by Tableau GPT (detailed below), get to the point about good or bad changes, with root cause analysis as to why they are changing. Rather than asking users to seek out these insights, Pulse cards will be proactively delivered to targeted users via email, Slack, a Web-based landing page, and/or a mobile experience. It’s a form of embedding that brings urgent, business-relevant insights to users rather than asking them to log into an analytics and BI platform and interpret a dashboard.

Tableau GPT: Better Explanations for Trustworthy Facts

Tableau has addressed three key concerns about the use of generative AI: data security, trust and human oversight.

Much has been written about what generative AI does well (language generation) and what it does not do well (math, for one). Tableau emphasized that it will point Tableau GPT at the Tableau analytics engine as the source of facts and mathematical analysis. Tableau GPT will then use a choice of underlying large language models, including OpenAIs as well as others, to explain those trustworthy facts in nuanced natural language. Tableau GPT will also enable users to ask questions in truly natural language, rather than unnatural “query speak” that’s only natural for SQL-savvy users.

Tableau offered three reassurances about how Tableau GPT will work. First, customer data will never be sent outside the “Salesforce trust boundary,” meaning LLMs won’t be able to train on customer data. Second, the language generated by Tableau GPT will always be grounded in facts and analyses done by the Tableau Analytics Engine – so the LLM can’t “hallucinate” and make up facts, Tableau insists. Third, humans will always remain in the loop, so “think Iron Man” (a human assisted by technology) “not terminator” (a robot with its own agenda).

Tableau GPT, which is also set to preview in Q3, will be a behind-the-scenes service that will be available for both exploratory self-service analysis, including natural language query that’s handled by Ask Data today, and by the coming Tableau Pulse service.

VizQL Data Service: Headless BI liberates insights from the Front End

The VizQL Data Service, expected in 2024, will advance Tableau's embedded analytics capabilities.

In another sign of an embrace of the embedded BI trend, Tableau is planning to support so-called “headless BI” with the VizQL Data Service, expected to preview in 2024. VizQL will decouple Tableau’ back-end analytics engine from the front-end visualization, dashboarding and authoring interfaces. Using APIs, developers will use VizQL to programmatically deliver Tableau insights within chatbots, workflows, and third-party apps to drive and automate data-driven action based on analytic triggers (human oversight and interaction with visualizations optional).

The VizQL Data Service is complemented by a new usage-based licensing model, which supports ephemeral user, and by an embedded playground with no-code, drag-and-drop development options.

Constellation’s Analysis

Personalized insights and exception-based alerting are nothing new, but with its metrics layer, understanding of business context, and use of generative AI through Tableau GPT, Tableau Pulse has the potential to stand on the shoulders of prior efforts and bring business utility to the next level. In truth, Tableau first-generation augmented features including Ask Data, Explain Data, and Data Stories, had mixed success, so we’re eager to see how eagerly and widely customers will adopt these second-generation capabilities.

Also yet to be determined is how these new features will be packaged and priced. Tableau Pulse, for one, is a cloud-based service that will be coupled exclusively with Tableau Cloud (and not available with Tableau Server), though it’s not yet know whether it will be a standard or optional (extra cost) feature. Tableau GPT will likely be available both through Tableau Cloud and Tableau server, but feature vs. option decisions and pricing have yet to be determined. VizQL pricing and packaging decisions also are yet to be made, but I’d expect this to be exposed through Tableau Embedded.

For now what we do know is that Tableau, and analytics and BI deployments in general, are breaking out of the self-service reporting and dashboarding mold in a big way.

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ServiceNow expands finance, supply chain process, workflow automation

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

ServiceNow is expanding its financial and supply chain workflows on its platform as it aims to automate more processes such as accounts payable and procurement.

At its Knowledge 2023 conference in Las Vegas, ServiceNow outlined the new workflows. As previously reported, the race to automate business processes is on as multiple vendors are aiming to be the automation platform of choice.

ServiceNow also is layering generative AI features into its workflow automation platform.

ServiceNow is increasingly using its workflow automation platform to expand into new use process use cases. ServiceNow is actively courting finance, procurement and supply chain leaders.

The new finance and supply chain workflows include:

Accounts Payable Operations (APO), which will automate the accounts payable process. APO eliminates the need to manually enter data or reconcile invoices against purchase orders and goods delivered. ServiceNow said there will also be a single view that incorporates ESG, legal and compliance.
Clean Core ERP with App Engine, which uses ServiceNow's low-code tools to identify legacy ERP technical debt that can be removed, replaced or automated. This move has two objectives including making ERP migrations more efficient and highlighting ServiceNow as an automation platform that rides on top of ERP systems.

"Finance and supply chain are key processes ripe for automation," said Constellation Research CEO Ray Wang. "These processes are often highly defined and regulated, which make them great candidates for automation in this exponential year of efficiency."

Not surprisingly, ServiceNow outlined its generative AI case. The company outlined its Generative AI Controller and Now Assist Search that will bring generative AI to enterprise applications. ServiceNow and Microsoft also expanded their existing strategic partnership to connect the Now Platform to Azure OpenAI Service.

The ServiceNow Generative AI Controller allows customers to connect ServiceNow instances to both Microsoft Azure OpenAI Service and OpenAI API large language models. The AI controller also has built-in actions to integrate generative AI to answer questions, summarize and generate content and plug into ServiceNow's Virtual Agent.

Now Assist for Search provides natural language responses based on a customer's knowledge base. It will be available throughout Portal Search, Next Experience and Virtual Agent.

Among the other announcements from ServiceNow at Knowledge 2003:

ServiceNow Cloud Observability brings in Lightstep's observability metrics, tracing and logging into one system that can provide insights and actions across tools, processes and people.
ServiceNow Employee Growth and Development uses AI to close talent gaps and identify what skills will improve businesses. The platform also has guided career paths, development goals and learning resources.
ServiceNow Diversity, Equity and Inclusion Report, which uses data to determine the focus and objectives of new programs, progress made and processes and policies to advance DEI.
ServiceNow.org launched to enable nonprofits to manage resources better with a focus on use cases such as disaster deployment, refugee resettlement and volunteer management.
ServiceNow Global Impact Report is targeted at ESG and targeting sustainability and social goals with business metrics and objectives.

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SAP aims to infuse generative AI throughout its applications: Here's everything from SAP Sapphire 2023

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

SAP launched SAP Business AI and said it will embed generative AI throughout its applications as it made the case that enterprises should trust the ERP giant with making business processes more efficient.

Speaking at SAP Sapphire in Orlando, CEO Christian Klein said SAP's mission is to make businesses more agile with generative AI as well as process mining and other tools. "No company can afford to run in silos," said Klein. "Back to standard is key to continuous integration and improvement." SAP's main pitch to CEOs, CFOs and CIOs is to integrate into SAP's portfolio and standardize on its data model.

The software giant outlined 15 new business AI capabilities and use cases while touting customers such as Unilever and Pfizer and partners such as Google Cloud and Microsoft.

"AI will have a tremendous impact on our private and business lives," said Klein, who made the case that AI embedded in the SAP platform will increase productivity and change the way people work. "Our software will be able to answer any business related question and show you how to improve."

In the big picture, SAP is combining generative AI and large language models (LLMs) with its business process knowhow as it aims to make the case that its ERP base is the business performance management platform. SAP's reach is extensive when it comes to business processes. For instance, SAP announced generative AI plans to address multiple use cases including job description and interview question generation via SAP Success Factors, a digital assistant for CX and SAP Signavio Process Manager with process model generation and documentation.

Other use cases for SAP Business AI included finance, sustainability, transportation, warehouse management and procurement as well as sales order auto-completion in SAP S/4HANA Cloud.

The barrage of news from SAP landed a day after it extended a partnership with Microsoft. The two companies will integrate SAP SuccessFactors applications with Microsoft 365 Copilot and Copilot in Viva Learning along with Microsoft's Azure OpenAI Service. SAP has also formed partnerships with Databricks and Data Robot as well as Google Cloud integrations for SAP Datasphere. See: Business process automation platform debate about to heat up

Constellation Research analyst Doug Henschen said:

"Staying out of the LLM game is a practical and realistic approach, and one that competitors including Salesforce are also following. SAP delivers what it’s calling “Business AI” by using its intimate knowledge of business processes to apply the AI tech in intelligent, value-driving ways."

Among the announcements:

SAP Extended Warehouse Management is getting intelligent slotting capability that uses AI to suggest how to optimize warehouse organization as well as stock and replenishment processes.
SAP Transportation Management application will get SAP's document processing with generative AI. Generative AI will be used to automate manual checks of goods, receipts and delivery notes. This capability will be available in the fourth quarter.
SAP Business Network will embed AI with intelligent invoice conversion to make it easier for procurement teams to add new suppliers, extract data from invoices and map data. SAP Ariba Buying will also get AI to simplify processes.
SAP Customer experience will get SAP Digital Assistant, currently in alpha, to use generative AI to provide sellers and support teams insights.
SAP S/4 HANA Cloud will get built-in-support with live recommendations from SAP support teams and enhanced by AI. This feature is expected in May to July as it rolls out across the product line.
SAP Signavio Process Manager will use generative AI to identify recommended process models and KPIs. Availability will be later this year.
SAP Predictive Replenishment will use AI to calculate and order products automatically to optimize inventory levels and availability for retailers. SAP Intelligent Product Recommendation will be aimed at manufacturing customers to streamline quotes, opportunities and orders.
SAP SuccessFactors will use AI to improve talent intelligence and provide a consolidated view of skills, cost and availability across an enterprises workforce.
SAP announced an update to SAP Sustainability Footprint Management for carbon tracking and the SAP Sustainability Data Exchange, which will enable partners to exchange standardized sustainability data.
SAP Business Network buyers will be able to select vendors based on sustainability ratings via a partnership with EcoVadis.
SAP Business Network will add supplier insights as well as streamlined integration, marketplace catalogs, lead matching and enhanced company profiles. Henschen said SAP's sustainability efforts mark "good progress on improving the fidelity of sustainability data to match that of financial data." He added:
"It’s not just about reporting. Also required is planning and scenario-modeling capabilities that take into account dynamic and changing conditions. If companies are to make and keep carbon-reduction targets, they need to be able to look at the costs and business impacts of traditional energy and sourcing choices versus various alternatives."
SAP Business Network for Industry are prepackaged packs focused on supply chain collaboration use cases starting with industry and implementation best practices. The first rollout is focused on high tech, industrial manufacturing, CPG and life sciences. SAP CX will also get accelerators to help retail, CPG, automotive and utilities industries to improve experiences.
Taulia, a working capital management software provider acquired by SAP, is now integrated into SAP Business Network.
SAP Category Management will be available in August 2023 and include procurement pros with market and commodity intelligence, category management and insights for strategy as well as potential supply chain issues.
SAP Blockchain Business Connector, which features smart contract management and automated workflows, will launch in beta.
A series of integrations across SAP applications focused on processes including quote to cash, consumption revenue management, Signavio Process Explorer and other areas.

Media Name: AI-Built-for-Business_Announcements.jpg

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C3 AI CEO Tom Siebel: Generative AI enterprise search will have wide impact

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

C3 AI CEO Tom Siebel said generative AI is about way more than chat and enterprises are likely to use the technology more for enterprise search. "We're using these large language models to basically crawl the enterprise," he said.

Speaking on the company's fiscal third quarter earnings call, Siebel outlined his take on generative AI as well as the benefits of incorporating it into the C3 AI platform so customers can use it for enterprise search. C3 AI's plan is to integrate large language models and generative free trading transformers into the company's platform.

He said:

“By combining the utility of the C3 AI platform, predictive analysis enterprise search, natural language processing, generative pre-trained transformers and reinforcement learning, we have developed a new and novel technique to fundamentally improve the human computer interface for enterprise applications.

This is kind of a non-obvious use of generative AI. This is not about chat, okay? This is about enterprise search. And we believe that this invention represents a breakthrough development that will dramatically facilitate the ease of use and explainability of enterprise AI applications. In addition to providing users immediate, highly controlled access to potentially the entire body of data and information systems within an enterprise, be it Dow Chemical, the United States Air Force, Shell, whatever it may be.”

Siebel added that C3 AI generative search will be embedded into the C3 platform and applications with general availability this spring. Siebel explained that C3 AI has been working with generative AI models since 2020 due to a request from the Department of Defense, which wanted enterprise search that could answer multiple questions from sources as wide ranging as satellite coverage to supply chain status to diversity goals to slides.

He said generative AI also enables DoD to drill down into data via chat and natural language processing. The key point though is that "the chat universe that you know about is only the information content of the enterprise where it was installed." Siebel said C3 AI's architecture enables it to use new engines as needed.

Siebel acknowledged C3 AI is still working on scoping the monetization opportunity for generative AI but will increase usage of the platform.

C3 AI reported a third quarter net loss of 57 cents a share on revenue of $66.7 million. C3 AI's non-GAAP loss was 6 cents a share. The company projected fourth quarter revenue between $70 million and $72 million and guided toward sales between $264 million and $266 million for fiscal 2023.

Other takeaways:

C3 AI is currently moving to a consumption-based pricing model with more than 290 qualified pilots in the pipeline.
Google Cloud has become a key partner with the combined teams pursuing 291 enterprise opportunities for joint solutions.
AWS and C3 AI are pursuing 75 new deals with six agreements closed in the third quarter.
Siebel added that C3 AI and Microsoft Azure closed a deal "with a super major U.S. energy company."

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How process mining can revamp software development

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Process mining is being used to automate multiple processes in finance and supply chain and driving real bottom line value, but Bloomfilter is betting that the technology can revamp the software development lifecycle.

In an interview with DisrupTV, Andrew Wolfe, co-CEO of Bloomfilter, and Erik Severinghaus, co-CEO & co-founder of Bloomfilter, outlined how process mining can be used for the software development lifecycle. Bloomfilter recently raised $7 million in seed funding.

Process mining has been the domain of CFOs and CEOs and continuous improvement teams. Process mining takes logs from enterprise systems to show how work is actually done (compared to how it works on a whiteboard), and companies can make processes such as accounts payable, accounts receivable, order-to-cash, hire-to-retire and logistics more efficient. Since many of these processes revolve around real cash savings enterprises can drive top line and bottom line returns.

Software development has been a different animal, said Severinghaus. "Anybody that oversees and manages a complicated business process knows that there's a ton of waste and inefficiency," he said. "The hard part is always figuring out where that is so that you can root it out and make it more efficient."

Severinghaus added:

"The product development side has always been too hard of a challenge since you can't just go take a typical process mining tool and connect it into the various different systems. There's are a dozen different systems along the product development roadmap. You have everything from Figma up front where you're doing design all the way to Jira. There are different tools across the entire lifecycle to stitch together."

The good news, said Severinghaus, is there is a lot of data to analyze, but it has to be normalized and focused on product development. Bloomfilter has a few patents with more in the works for product development process mining.

Wolfe said there's a big opportunity to automate software development processes. In software development, the typical analytics are lagging indicators such as velocity. "What's missing is why you got there. You may know velocities but don't know where you're going or how you got there," said Wolfe, who added that process mining can enable you to have conversations to better manage sprints. "What we find is a lot of people we talk to are tracking processes in Excel. Some are using PowerPoint. I've seen some amazing Mona Lisa level spreadsheets."

Software development has had a limited picture across the entire process across Figma, product board, Jira, GitHub to AWS. "The indicators are too lagging to make any kind of strategic decisions," said Wolfe, a Business Transformation 150 alum.

Ray Wang, CEO of Constellation Research, asked Severinghaus about tips when considering process mining for software development. He outlined the following:

Drop the fixation on developers. Severinghaus said the first question Bloomfilter gets revolves around engineers and whether they're working multiple jobs. "There's an obsession that these really expensive developers are just screwing around and that's the reason software isn't getting built," he said.
Focus on the overall software development life cycle. "We show our clients over and over again that developers are a small piece of the software lifecycle," said Severinghaus. "You may have amazing developers sitting downstream from terrible requirements. It doesn't matter how great and fast developers code or how much AI you apply if the requirements aren't right."
Know the processes before hiring more engineers. Hiring 10 more engineers won't do you much if your software development process is hung up in QA. "Let's say you create 100 applications a day, but you still have to test them to make sure they're valid and you still have to deploy them," said Severinghaus.
Beware scaling bad code. AI can speed up the software development lifecycle and deployments, but without a holistic process approach enterprises may just scale bad code at a speed humans can't comprehend, said Wolfe. You have to attack the bottlenecks but keep a holistic view.

Constellation Research analyst Liz Miller asked Bloomfilter's co-CEOs whether they were going to apply process mining to other art-meets-process disciplines like marketing. The short answer is no, but clearly there's a market to apply process mining beyond the usual finance processes.

Here's the full episode with the Bloomfilter interview starting at the 22 minute mark.

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How 4 CEOs are approaching generative AI use cases in their companies

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Generative AI is the question of the day on many earnings conference calls, but the approach to leveraging the technology depends on the industry. Here's a look at how Bank of America, Airbnb, Lemonade and Deutsche Telekom are thinking about generative AI.

Bank of America CEO Brian Moynihan: Generative AI needs more transparency

With existing investments in its ERICA natural language AI, CEO Brian Moynihan needs more transparency before fully leveraging ChatGPT and other generative AI technologies. That approach shouldn't be too surprising given banks are highly regulated.

Speaking on Bank of America's first quarter earnings conference call in April, Moynihan said the bank started working on ERICA, a predictive Q&A bot, years ago. The bank created its own language for ERICA and deployed it. The catch is that ERICA was only looking at Bank of America systems without third party data.

"Because ERICA is captive to our data, where it's just looking at our systems, finding information and giving to clients it is really a service capability," explained Moynihan. "We've also taken ERICA internally and applied it to help us do work and we've seen it have those benefits."

He added generative AI can improve computer coding productivity and content creation as well as analytics. However, Moynihan said transparency is going to be an issue if you're integrating your corporate data with generative AI.

Research: Microsoft Shifts Coding From Typing to Language With ChatGPT

"The reason why a lot of it stopped in our industry and other industries was, it wasn't clear how it worked. It was your data and the outside world's data and how it would interact and pull stuff out and we have to be careful with that," he said. "We have to understand how the decisions are made, and, frankly, follow the laws and rules and regulations on lending."

"We understand the value of it, but we will carefully apply it and we see a great value. I don't think it's a great value in the next month, but in the overall sense, it will help us continue to manage the headcount down which we've been doing this quarter. This management team started with this company in 2010 with 285,000 and 300,000 people working here and we're running the same size company with 216,000 people or bigger company doing more stuff and that's been aided by digitization."

Airbnb, CEO Brian Chesky: All about the tuning

Chesky said generative AI may be as big of a platform shift as the Internet was. The competitive advantage will be for the companies that take a base model and uniquely tune it.

Chesky said on Airbnb's first quarter earnings call:

"All of this is going to be built on the base model. The base models, the large language models, are like major infrastructure investments. Some of these models might cost tens of billions of dollars towards the compute power. And so, think of that as essentially like building a highway. It's a major infrastructure project. And we're not going to do that. We're not an infrastructure company. But we're going to build the cars on the highway. On top of the base model is the tuning of the model."

He said the tuning of the model will be based on the customer data you have. When the base model is combined with customer data then there's a lot of innovation.

"I think that going forward, Airbnb is going to be pretty different. Instead of asking you questions like where are you going and when are you going, I want us to build a robust profile about you, learn more about you and ask you 2 bigger and more fundamental questions: who are you? And what do you want? Think of us with AI as building the ultimate AI concierge that could understand you."

MARKET OVERVIEW: Analytics and Business Intelligence Evolve for Cloud, Embedding, and Generative AI

Lemonade co-CEO Shai Wininger: Integration is easy if you have existing AI stack

Lemonade is a digital insurance company that has been using machine learning and AI for years. It uses models to predict losses and risk down the zip code as well as each discrete home it insures. The goal for the company is to have true precision in pricing and underwriting.

"Lemonade was built as a tech-powered insurance company. We were the first to provide customers with human-like chat-based experience that works 24/7 and handles all of our direct sales," said Wininger, speaking on the company's first quarter earnings call. "On the back-end, we built a first of its kind insurance operating system that lets our team service our customers efficiently and delightfully. This year, ChatGPT 4 and other large language models made a huge leap forward. The potential impact this technology brings to businesses like ours is substantial."

Since generative AI can reason and learn it has the potential to improve efficiency and customer service as well as risk assessment and underwriting decisions. "This technology will help us better anticipate customer needs, respond to more claims instantly and ultimately provide better coverage at lower costs," he said. "For our competitors, though, adapting to this change will not be easy. A traditional insurance company depends on hundreds of disparate software tools to run its business. many of which are outdated legacy systems built decades ago by third-party vendors."

Wininger's argument is that companies without an AI-friendly stack will be buried by technical debt. Lemonade's bet eight years ago revolved around conversational UI and chatbots and it has updated models as they have evolved. He said:

"Today, we use dozens of AI models to do pricing, underwriting, customer service, payments and many other internal operations. We even built our own internal AI framework to help us manage and deploy models seamlessly and quickly across the organization. In just a matter of days, our team was able to add ChatGPT and other generative AI tools to our platform. We now have more than hundred different initiatives, which we believe can have a meaningful impact on our business. As a result, we expect to see more savings in the next 18 months and anticipate continued improvements in both our expense and loss ratios."

Deutsche Telekom AG CEO Tim Hottges: Eying customer service benefits

Speaking on DT's earnings conference call, Hottges was inevitably asked about generative AI. He said:

"There was never in the last 20 years that I recall a technology that had so much impact on thinking in management but as well in the organization as the announcement of ChatGPT and OpenAI. This is really a game changer in the way we look at it."

DT launched a program that features a centralized team that works with OpenAI's ChatGPT as well as Large Language Models including fine tuning. "We are fine-tuning all the elements of it with our foundation in the customer service arena," he said. "We used it already in the past, but we will now trying to exponentially develop the area of chatbots, call center support, network optimization and other areas where big data is affected."

Generative AI guide: ChatGPT: Hype or the Future of Customer Experience

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HOT TAKE: Twitter Has a New CEO

Liz Miller

Vice President & Principal Analyst
Constellation Research

About Liz Miller: Liz Miller is Vice President and Principal Analyst at Constellation, focused on the org-wide team sport known as customer experience. While covering CX as an enterprise strategy, Miller spends time zeroing in on the functional demands of Marketing and Service and the evolving role of the Chief Marketing Officer, the rise of the Chief Experience Officer, the evolution of customer engagement, and the rising requirement for a new security posture that accounts for the threat to brand trust in this age of AI. With over 30 years of marketing experience, Miller offers strategic guidance on the leadership, business transformation, and technology requirements to deliver on today’s CX strategies. She has worked with global marketing organizations to transform everything from…...

When the Musk era of Twitter began, in a blog post I suggested that the first question the new owner would need to answer and articulate would be what Twitter actually was going to be moving forward:

Twitter is a media company: Twitter “must subsidize its capacity to host a broad, global, democratized media destination that holds professional accounts (from journalists and their publications to marketers and their brands) in equal footing to citizen creators… if this new massive recurring revenue base became predictable and stable over time, Musk could easily show advertising the door and instead charge a heftier fee to allow brands permission to even HAVE accounts.”

Twitter is an advertising company: Twitter “leverages citizen creators, brands and media accounts to attract more users hungry for quick snippets of information or engagement. This audience would, in turn, represent a massive potential audience for targeted promoted content and advertising…quantity of audience beats out quality and is a model where advertising pays the whole tab. “Cherry on top” revenue like subscriptions and priority access options like Twitter Blue become important for bigger numbers but are not the primary focus of revenue projections.”

For over six months, Elon Musk has done everything imaginable to turn Twitter into a media company. The results have not been great. The moves to prop up a subscription dominant business have not gone smoothly. According to a report in Bloomberg, the Twitter Blue subscription has only captured 1% of Twitter’s 500 million monthly users. According to Musk himself, advertising revenue had decreased by 50% between October 2022 and March 2023. There is little visible runway for Twitter to continue on this glidepath of being a subscription-centric media company.

The tweet-nouncement by Musk that NBCUniversal’s powerhouse sales leader, Linda Yaccarino, has joined Twitter as CEO feels like a clear sign that Twitter might be ready to shift course.

First, let’s dig into WHO Yaccarino is.

For all things I have personally heard about her, she is a powerhouse seller, dealmaker and business leader. She’s been credited with making some of the most lucrative deals in her tenure with NBCUniversal. Joining the company in 2011, Yaccarino was named the chair of global advertising and partnerships in October 2020 and her team has been credited with generating over $100 billion in advertising sales for one of the largest and more complex advertising portfolios of media properties that make up NBCUniversal.

When the rumor mill cranked into high gear in the late hours of May 11 most of the comments from advertising thought leaders was WILD approval noting that Yaccarino might be the ONLY executive out there to breathe life back into the ailing blue bird.

What does (or COULD) Yaccarino’s appointment really mean?

This could mean that Twitter will embrace being an advertising platform, bringing some stability to revenues and to the platform itself. This could also be an opportunity to bring back some of the content creators turned off by a once civil space for conversation turning into an almost daily shouting contest across differing ideologies.

But, as an advertising platform, this will mean that the significant and very real concerns advertisers have about content adjacency and moderation be addressed by serious people ready with serious answers. This will also give Twitter an exceptional opportunity to hit pause on hastily made subscription strategies that fostered more ill will with notable content creators than it did drive excitement over exclusive experiences.

As CEO, Yaccarino will need to dissect the business opportunities into segmented, distinct yet intersecting nuanced categories. If given the power, freedom, and capacity to do this, we could see new and even more profitable subscription types and experiences as Twitter evolves. She will need to reinvent the Twitter culture for both customers and employees and while this will initially be an exceedingly painful process (healing broken bonds where trust no longer exists is never easy and usually leaves scars somewhere) that doesn’t always work, it COULD result in something even better.

Musk, in his Tweet about the appointment, also pointed to his continued desire to turn Twitter into an “Everything” app – up until now, this has been an empty promise that felt more like being handed a burnt, stale everything bagel than an improved experience application. With Yaccarino’s arrival, there is the potential to bring that big dream into real world business focus. She could be the voice that articulates the opportunity for creators, consumers and advertisers…and all three parties have been missing this clear articulation of a Twitter vision since well before Musk’s takeover.

HOWEVER, this could also mean rough waters ahead if all Musk has done is hand over the title but withheld the territory from the CEO gig. In his own words, he will be staying on as “CTO in charge of the product.” But for many brands (and more than a few content creators) the product has been horrifically broken under his reign. If Yaccarino only has the mandate to bring advertisers back to a broken trough, it is unlikely we will see Twitter evolve beyond what it is today. And for the advertisers who DO return based on their relationships with Yaccarino and their trust in her skill and expertise, that return will only be as durable as her time is in the role.

Yaccarino is no slouch. She is smart, articulate, savvy and battle tested in some of the roughest media waters around. She isn’t going to wither in the face of irrational man baby tantrums. From what I have learned about her from those who call her a friend, she has a passion for the media business. My sincere hope for her…and frankly for all of us who have always wanted Twitter to succeed…is that she has been giving both title and territory. Only time will tell. And judging by how fast this strange timeline we are in has been moving, Yaccarino won’t have terribly long to make her mark and set the story of the new everything platform X also known as Twitter into motion.

(Image Credit: The image attached to this post was created using Adobe Firefly using the text prompt: Hyper Realistic Blue bird wearing armour standing in front of a burning fire)

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HOT TAKE: Twitter Has a New CEO

HOT TAKE: Twitter Has a New CEO

First, let’s dig into WHO Yaccarino is.

What does (or COULD) Yaccarino’s appointment really mean?

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How 4 CEOs are approaching generative AI use cases in their companies

HOT TAKE: Twitter Has a New CEO

First, let’s dig into WHO Yaccarino is.

What does (or COULD) Yaccarino’s appointment really mean?