TBR Joins Crayon’s New CI Partner Directory

TBR is proud to join Crayon’s CI Partner Directory, the first-ever collection of the competitive intelligence industry’s best services and solution providers

HAMPTON, N.H. (March 21, 2023) — Technology Business Research, Inc. (TBR) is proud to announce we have officially joined Crayon’s CI Partner Directory, a compilation of competitive and market intelligence providers. TBR is one of a select group to be included in the directory, which was created to help companies easily find the organizations that can supercharge their competitive intelligence (CI) efforts. Crayon is a leading CI platform, used by hundreds of companies to track their competitors and enable their revenue teams.

 

TBR has been empowering corporate decision makers since 1996, providing business-centric, vendor-focused subscription and tailored competitive research services to the global technology, telecommunications and professional services industries. Unlike other technology research firms, TBR’s research is empirically opinionated. TBR reports and projects are supported by a rigorous quantitative foundation that includes hundreds of financial models tracking millions of unique P&L, balance sheet, resource and go-to-market metrics, as well as a primary research workload of up to 5,000 interviews and 10,000 surveys fielded annually.

 

Crayon clients that choose to work with TBR will have access to an array of benefits, including early beta access to TBR Insight Center™, a dynamic, configurable CI research and data visualization platform; exclusive access to TBR subject-matter experts; and special pricing offers for primary research projects.

 

“The future of competitive intelligence lies at the intersection of people and technology,” said TBR Senior Director Bryan Belanger. “Technology platforms like Crayon help CI teams automate, scale and move faster. This frees up the most valuable CI resource — the people — to work with partners and can help them expand the services they provide to their stakeholders. Crayon’s directory is the first place to bring this all together for the CI industry.”

 

“Our customers know how critical competitive intelligence is for driving more revenue and are often looking for the right partner to ensure they meet their goals,” said Jonah Lopin, co-founder and CEO of Crayon. “We’re thrilled to have TBR included as one of the partners among this exceptional group in the initial directory. I look forward to our continued growth together.”

 

Have questions about the new partnership, or interested in learning more about TBR’s services?

EY’s Cybersecurity Practice: Global, Local and Trusted

EY continues to grow its capabilities, talent pool and expertise in the security consulting services space. The cybersecurity practice is organised around five cybersecurity solutions, with Cybersecurity Transformation generating the most revenue for EY, and Cyber Operations as the fastest-growing solution. In the last year, Cyber Operations contributed 26% of cybersecurity revenue. EY’s cybersecurity service demand is increasingly delivered through a managed services engagement model. Additionally, the Americas continue to be EY’s largest area in revenue, while EMEIA experienced revenue growth, thanks to an acute shortage of cybersecurity talent leading to increased demand for managed services contracts.

Delivering security for transformation and managed services engagements

In a series of discussions since the start of 2023, TBR has spoken with EY’s global cybersecurity practice leaders to better understand how the firm continues to grow its capabilities, offerings, talent pool and expertise in the security consulting services space.

 

To set the stage, EY organizes around five cybersecurity solutions, including Cybersecurity Transformation, Data Privacy, Cyber Operations, Cyber Incident Resilience and Response, and the emerging Cyber for Assurance. Of the five, the first generates the most revenue for EY, in line with the firm’s traditional strengths around consulting, tax and strategy. Cyber Operations, which EY increasingly delivers through a managed services engagement model, has been the firm’s fastest-growing solution over the last year, contributing 26% of cybersecurity revenue in 2022.

 

Geographically, EY leaders said the Americas continues to be their largest area in terms of revenue, with clients across a full range of industries. In EMEIA, an exceptionally strong track record of revenue growth has belied an acute shortage of cybersecurity talent, leading to increased demand for managed services contracts as clients looked to EY to complete essential cybersecurity tasks.

 

In TBR’s view, EY continues to operate through a global effort, complicated by regulatory and compliance requirements that vary by country as well as member firms’ different partnership structures. However, at multiple times during the discussion, EY leaders said the firm knew that cybersecurity services required being “local to be there with clients.”

 

Expanding on managed services, EY’s Krishna Balakrishnan, Global & Asia-Pacific Region Cybersecurity Managed Service (CMS) Leader, noted that clients engaging the firm’s managed security services offerings increasingly look for platform-based approaches that will provide outcomes faster than previous expectations. As a result, EY more readily leverages emerging technologies to elevate the value of the firm’s managed security services offerings, supported globally by more than 4,000 cyber managed services professionals and nine cybersecurity delivery centers.

 

As consulting engagements typically lead to interest in managed services, TBR followed up with questions about how often clients seek stand-alone security services from EY, including managed services. Befitting a Big Four firm, EY leaders explained that they are “increasingly seeing an infusion strategy where cybersecurity also is infused into security-adjacent offerings such as tech/IT risk, regulatory and compliance management, as well ESG risk disclosures related to enterprise resilience such as requesting security parameters and maturity assessment of their cyber and CISO [chief information security officer] function as part of ongoing client engagements.”

In TBR’s March 2023 Digital Transformation: Cross-Vendor Analysis report, we noted that, as shown above, “almost half of respondents ranked exposure to supplier’s risk as their organization’s top concern about investing in cybersecurity services, which puts pressure on vendors to develop properly scoped solutions and skilled and certified bench to gain buyers’ trust. Additionally, folding cybersecurity within vendors’ cloud and IT portfolio can be a double-edged sword if vendors do not build the use case and generate awareness around a particular cybersecurity capability area. This investment concern closely aligns with vendors’ ability to distinguish themselves as a leader in the space. Once again, the ecosystem is valuable, helping vendors to develop portfolio offerings aligned to their core value proposition and build a name for themselves, rather than just adding cyber on top of everything else they offer.”

Leveraging the ecosystem and being the best possible partner

During the discussion, multiple EY leaders stressed that the firm would not position itself as a technology company but would instead remain a consultancy aligned with technology companies to create transformative solutions — and not simply point solutions, but innovative and transformative solutions, cocreated with technology partners.

 

Expanding on this in follow-up discussions, EY Global Consulting Cyber Architecture, Engineering and Emerging Technology Leader Piotr Ciepiela described collaborations with Microsoft (Nasdaq: MSFT) and IBM (NYSE: IBM), Tanium and CrowdStrike, to name a few, and EY has launched several quantum security centers of excellence, complementing the IoT/OT Security Lab that EY opened in Warsaw, Poland, in 2018.

 

TBR asked how the lab had evolved in the last five years, and EY leaders explained that the firm uses it to “test customer deployments and conduct PoC [proof of concept] projects” as well as “show visiting customers a wide variety of cybersecurity solutions using the physical OT environment.” Ciepiela added, “At first, our EY clients wanted to test very specific OT solutions that were usually provided by startups and scale-ups. Today we are providing design and proof of concept for comprehensive OT environments dedicated to each OT sector.

 

With dozens of dedicated OT solutions as well as more than 350 physical and virtual environments, we can deploy and test entire ecosystems in days. That’s why [the] majority of our clients are coming back or treat our facility like lab ‘as a Service’ for new solutions and massive rollouts.” Circling back to technology partnerships, EY leaders described alliances and joint investments in physical centers dedicated to specific technologies, such as quantum and AI, with vendors as diverse as Red Hat, BT and Toshiba, in addition to EY’s strategic partners like Microsoft and IBM.

 

In TBR’s view, EY’s sustained emphasis on partnering well across the technology ecosystem — to include innovation, go-to-market initiatives, and even cobranded transformation centers, such as the EY wavespace innovation hub — has contributed significantly to the firm’s sustained success. TBR’s Voice of the Customer research confirms that clients prefer cooperative partnerships across an ecosystem of providers over a single vendor promising end-to-end solutions.

 

Further, regarding EY’s position within the larger security services ecosystem, EY leaders stressed that the firm does not pursue engagements based on requests for proposals or lowest-priced competitive bids; instead, it focuses on transformational work that leads to longer-term operations engagements. In addition, EY sees its greatest growth opportunities with clients in the financial services (although at a slower growth rate than previous years), energy, industrial/manufacturing, and public sector and defense sectors.

 

Simultaneously, EY leaders noted that Sectoral Security Operations Centers (SOCs) would likely become a significant trend across the cybersecurity industry, with EY intending to invest in SOCs that are dedicated to working with federal government, telecommunications and automotive clients, guided in part by client demand, as well as market research by EY-Parthenon and EY’s technology alliance partners. TBR has observed many IT services vendors and management consultancies develop strategies intended to focus on a select number of industries, with unsatisfactory results or abandoned strategies often tied to simply trying to focus on too many sectors at once. EY’s clear delineation around Sectoral SOCs looks to be a more tightly defined strategy, playing to the firm’s strengths and the market opportunity.

 

In the upcoming March 2023 Digital Transformation: Cross-Vendor Analysis report, TBR notes, “Almost half of survey respondents consider vendors’ brand leadership position to be a critical attribute for cybersecurity services. We believe this is a hard balance for vendors to strike, especially as cybersecurity can often be an unheralded area, so touting strength through use cases and/or portfolio offerings can entice malicious actors to exploit weak areas. Industry knowledge and price ranked as the No. 2 and No. 3  critical attributes, respectively, which is not surprising given the need for demonstrating regulatory and compliance knowledge tied to industry specialization during macroeconomic downturns. The No. 4 most critical attribute is vendors’ ability to rely on their partner ecosystems, which can be a challenge in the world of security as vendors try to protect their IP and best practices.

 

“We see partnerships between management consultancies and cyber-specialized vendors to be best aligned here as the former can bring in the risk and compliance knowledge and the latter group remains responsible for developing and managing the tech stack. While using automation for service delivery ranked the lowest in terms of being a critical attribute, we believe vendors need to consider elevating the value of automation as a tool that supports updated business continuity plans, especially as it allows them to address price-conscious buyers.”

What sets EY apart: Being EY

Three characteristics of EY’s cybersecurity practice stand out to TBR as key to the firm’s success to date and smartly playing to its strengths going forward: offering a whole-firm approach and delivery; partnering well across the ecosystem; and being simultaneously global and local. Throughout discussions with TBR, EY’s global cybersecurity leaders stressed that security services are complementary to the firm’s full range of services, including tax, risk and consulting; security is part of the package, not a stand-alone offering.

 

In TBR’s view, that approach builds on EY’s long-established brand as a trusted partner that is well versed in a client’s financials, operations and strategies, while also echoing a common refrain from clients themselves: security must be baked into everything. Most of EY’s peers also espouse a whole-firm approach to services, including cybersecurity, making this a necessary characteristic, rather than a differentiating one, that reinforces one of EY’s strengths.

 

The cybersecurity ecosystem may be the most diverse within the larger technology space, with seemingly endless pure play firms and every IT services vendor and management consultancy providing security services. In that maelstrom, EY has demonstrated a willingness and ability to play well, enhancing the technologies and capabilities of strategic alliance partners and vetting, nurturing and accelerating the development of smaller firms without compromising EY’s core value proposition around trust and transformation.

 

In an email exchange earlier this month, EY answered TBR’s questions about whether the firm will expand partner-branded SOCs by noting, “We already have several partner-aligned SOCs developed in partnership (U.S./EMEIA mainly) with our Big Six Alliance Partners, i.e., SAP [NYSE: SAP], Microsoft, ServiceNow [NYSE: NOW], IBM, Adobe [Nasdaq: ADBE], and now Dell Technologies [NYSE: DELL], and will continue to expand our partner-cocreation facilities and IP at pace.”

 

As with the whole-firm approach, EY’s alliance strategy does not provide, on the surface, easy differentiation from its Big Four peers, other management consultancies or most IT services vendors. TBR does believe EY’s difference may come through the breadth of these partnerships, EY’s willingness to cobrand SOCs, and the firm’s insistence that it stay within its only lane — which, as noted above, is not as a technology company but as a consultancy aligned with technology partners that can help deliver trusted transformation, including in the security space.

 

Lastly, EY’s global cybersecurity practice recognizes that every client’s security needs remain highly localized, even if the client maintains global operations. People, always the biggest security risk, physically reside somewhere. Regulations and reporting mandates start at the national, or sometimes state and local levels, requiring on-the-ground expertise and assurance. Any global cybersecurity services provider has to blend the need for borderless reach and capabilities with highly localized talent and expertise.

 

Once again, EY’s strengths and capabilities do not make it unique among peers, but a commitment to seamless and highest-quality security services at any client’s location, including the necessary talent on the ground lends credibility to EY’s claim that the firm is a market leader for cybersecurity. In TBR’s view, EY has nurtured three critical characteristics, playing to the firm’s strengths while positioning for growing opportunities in the cybersecurity space. In a crowded and noisy marketplace, EY seems to have found its place as a trusted, global, local, widely capable partner to technology partners and clients.
 

Our most-read analysis, free in your inbox each week — Subscribe today!


Competitive Landscape Shifts: Key Trends Impacting the U.S. Wireless Market

Rapid adoption of fixed-wireless services from T-Mobile and Verizon, in combination with accelerating wireless subscriber growth from cable MVNOs, including Comcast’s Xfinity Mobile and Charter’s Spectrum Mobile, is significantly impacting the U.S. telecom market competitive landscape. Telecom and cable operators will increasingly focus on improving the value proposition of their converged mobility and broadband service packages as customer discretionary spending is limited by inflationary pressures.

Join Senior Analyst Steve Vachon Thursday, April 13, 2023, for an in-depth, exclusive review of TBR’s latest research in the U.S. mobile operator space. Steve will discuss the financial and go-to-market performance of leading U.S. wireless operators as well as recent key developments impacting the U.S. market. TBR’s U.S. mobile operator research stream details and compares the initiatives, strategies and performance of the largest U.S. operators, including AT&T, T-Mobile, Verizon, UScellular, DISH Network, Spectrum Mobile, Xfinity Mobile and Optimum Mobile.

 

In this FREE webinar covering trends in the mobile wireless market you’ll learn:

  • How telecom and cable operators are revamping their go-to-market strategies to improve the value proposition offered by their converged mobility and broadband service packages
  • How U.S. operators are revamping their go-to-market and operational strategies in response to inflationary pressures
  • How 5G development is advancing in the U.S. and its impact on the competitive landscape and capex spending

 

 

 

Previous TBR webinars can be viewed anytime on TBR’s Webinar Portal. For additional information or to arrange a briefing with our analysts, please contact TBR at [email protected].

The Future of Telecom: Moving Forward

Mobile World Congress (MWC) 2023 brought together more than 2,400 exhibitors and 88,500 attendees from across the global ICT sector, including representatives from many enterprises that are pursuing digital transformation. TBR notes that the level of engagement and executive exposure at this year’s event returned to pre-pandemic levels, solidifying MWC’s role as the most important, must-attend event in the world for all things related to mobile technology. The most popular topics discussed at MWC23 included private networks, APIs, satellite connectivity, the metaverse and cloud transformation.

TBR Perspective

An undercurrent was evident at MWC 2023 that suggests communication service providers (CSPs) are losing their grip on their own market. New market opportunities, such as private networks and edge computing, are increasingly developing outside the purview of CSPs. TBR notes that an alternative ecosystem of players — including hyperscalers, pure play software companies, chipmakers, incumbent network and IT equipment providers, systems integrators, application developers, and non-telco enterprises — is emerging to capitalize on opportunities enabled by new technologies (e.g., private 5G networks, edge computing and AI). Even governments are participating in this disintermediation in the telecom sector via stimulus programs, regulation and the trend of spectrum democratization.

Thus far, the 5G era has been playing out very similarly to the 4G era, when CSPs invested hundreds of billions of dollars in spectrum and network infrastructure and realized paltry ROI as the majority of the new value from those investments went to over-the-top players, most notably hyperscalers. CSPs risk remaining largely confined to their traditional roles of providing mobile broadband (i.e., smartphone connectivity services) and high-speed broadband (i.e., internet services) as value from new areas benefits other players. There are very real concerns in the industry that CSPs could miss out on the nascent network API opportunity and be disintermediated from key markets such as edge computing.

With CSP capex set to decline this year, according to TBR’s research, vendors dependent on CSPs are holding out hope that 5G-Advanced will drive a new wave of capex spend growth starting in 2024 and, finally, enable CSPs to generate new revenue. However, delays in standards creation and increased complexity are causing many CSPs to push out deployment timelines or take a wait-and-see approach before implementing new technologies. This is currently reflected by most CSPs globally sticking with the 5G Non-Standalone (NSA) variant of 5G versus migrating to SA, which uses a 5G core. TBR notes an increasing number of vendors are hedging their exposure to CSPs by targeting opportunities with enterprises across a range of verticals.

Taken together, one thing was very clear at MWC: The ecosystem CSPs belong to is not waiting to capitalize on these new technologies and market opportunities, nor is it waiting for CSPs.

Impact and Opportunities

Large Enterprises Will Show the Way to Digital Transformation and Industry 4.0

Large enterprises will be among the earliest adopters of new technologies and business models, showing the world what digital transformation and Industry 4.0 look like. BMW, Pepsi (Nasdaq: PEP), Micron (Nasdaq: MU), Intel (Nasdaq: INTC), Amazon (Nasdaq: AMZN) and others are among these early adopters, implementing cutting-edge technology solutions such as digital twin and computer vision to drive business outcomes. In most cases, these entities are sourcing their ICT solutions either directly from the vendor or via partners such as systems integrators. CSPs either are not present or are assuming a relatively minor role in the value chain in these implementations.

Digital Twin Is the Initial Gateway Into the Industrial Metaverse

Though a broad range of use cases are being implemented in private network environments, digital twin has emerged as one of the most pervasively considered use cases for private networks, especially for 5G. Digital twin involves cyber-physical immersion, which is a key tenet of the metaverse, and represents a foundational building block of and gateway into the industrial metaverse. Though most digital twins today are rendered in 2D, the jump to 3D will occur this decade.

One of the most advanced digital twin examples presented at the event was BMW’s “factory of the future,” where the company digitally replicated an entire physical factory located in Regensburg, Germany. BMW will leverage the blueprints and learnings from that factory as it builds net-new factories. Digital twin technology is helping BMW achieve a variety of business outcomes ranging from improved worker safety to design and factory planning optimization and a reduction in downtime.

Sales and Compensation Models at Most Companies in the Telecom Sector Need to Evolve

Companies that continue to focus on selling SIM cards, point products and disparate solutions (and compensate employees based on these metrics) are at a competitive disadvantage versus companies that sell (and compensate based on) outcome-based solutions.

Partnerships are becoming more important in selling motions, and end customers increasingly want to see a direct path to business outcomes to justify spend. Companies primarily want technology solutions that produce business outcomes such as increased revenue and/or reduced costs. TBR notes that systems integrators (SIs) have generally been doing a good job on this front, evidenced by the high-value digital transformation contracts they are winning.

Telecom Industry Hopes 5G-Advanced Will (Finally) Deliver on the Promises of 5G

5G has been broadly underwhelming thus far, and CSPs remain behind in implementing the new network architecture and business model structures required to capitalize on 5G-related opportunities, especially those in the B2B domain. Many in the industry view 5G-Advanced (which is typically thought of as 3GPP Release 17- and Release 18-compliant technology) as a key catalyst that will finally enable CSPs to begin realizing the benefits of 5G.

CSPs Should be Careful Pushing for Hyperscalers to Pay for Networks

Especially in Europe, CSPs continue to insist that hyperscalers should pick up some of the bill for networks, which could include paying CSPs a fee for traffic carriage. CSPs should be careful what they wish for because it could provide justification for hyperscalers to build their own end-to-end networks, which could marginalize CSPs or disintermediate them from their role in the value chain. Hyperscalers already own and operate the largest networks in the world when considering their metro and backbone assets, and if they were to build out their own access layer networks (especially the last mile) that would remove one of the last major competitive advantages CSPs have in the market.

Open RAN Is Not Ready for Mainstream Adoption

Despite a lot of marketing by vendors around open RAN, the reality is that the technology remains immature. Open RAN gear has been implemented successfully and is running live traffic in a few commercial networks (mostly in greenfield environments) in various parts of the world, but significant gaps still need to be closed in terms of feature parity, performance parity and implementation cost parity with traditional RAN before open RAN can truly be seen as a replacement, or augmentative, to traditional RAN. It was evident at MWC that this inflection point remains at least a couple of years away.

Once-in-a-generation Talent Acquisition Opportunity Is Here

Workforce right-sizing in the tech sector (mostly due to over-hiring during the pandemic) has created a once-in-a-generation opportunity for companies that are willing and able to take on more workers. Many of the estimated 200,000-plus tech workers who have been laid off since the beginning of 2022 have valuable skills that CSPs and their vendors could leverage to assist with technology transformation, application development and the transition to becoming digital service providers.

Conclusion

Opportunities resulting from new technologies promise to unlock trillions of dollars in new economic value globally. The big question is: Who will capture this opportunity? Given significant structural challenges endemic to CSPs, it is becoming increasingly likely that other players will step up to the plate, including hyperscalers, proactive ICT vendors, non-telecom enterprises and other new entrants. CSPs still have a chance to be relevant in these nascent areas, but it will require significant changes in their cultures, ways of working, ways of thinking and execution. 5G-Advanced may provide the spark that helps CSPs catch up in adopting technologies that will enable them to bring new value into the market. But in the interim, other players in the ecosystem will continue moving forward.

 

 

Our most-read analysis, free in your inbox each week — Subscribe today!


2023 Market Trends & Business Changes Series

HAMPTON, N.H. (March 10, 2023) — Technology Business Research, Inc. (TBR) announces on-demand availability of all webinars for the 2023 Predictions series. Predictions is an annual TBR series examining market trends and business changes in key markets. 2023 covered segments include cloud & software, devices, digital transformation, IT infrastructure, professional services, federal IT services, and telecom. Click on any of the links below to start watching now.

 

The bull market in federal IT will continue in 2023

Learn what TBR expects to see in the federal IT market in 2023, including our expectation for a surge in spend to new highs on the back of digital modernization and cybersecurity investment; the key market dynamics driving federal technology investment in the year; and market acquisition activity expectations for 2023

 

Telecom industry will face an unprecedented level of uncertainty and risk in 2023

Learn how inflation, rising interest rates and the impending global recession will impact the telecom industry; what post-peak communication service provider spend on 5G infrastructure means for the vendor community; and why and how certain U.S.-based cablecos are building their own cellular networks

 

Cloud vendors will use predictable strategies for unprecedented times in 2023

Learn how cost will come back in vogue; why both big and small vendors will get bigger; the reason we believe all growth in the cloud market will come through partnerships; the ways hyperscalers will invest in PaaS and infringe on partners; and why SaaS vendors will pursue solution upsell and cross-sell tactics to weather economic pressures

 

Transparency, consistency, quality: Winning formulas for IT services, digital transformation and consulting in 2023

Learn why IT services and consulting clients have moved on from exploring data and now expect faster ROI on their emerging tech investments; how the breakups of various IT services vendors and consultancies will, and will not, impact the competitive landscape; which IT services vendors and consultancies have been winning the war for talent; what is compelling some IT services vendors and consultancies to build metaverse capabilities; why AI enables transformation and automation fosters cost containment; and how hyperscalers flipped the vendor selection switch on IT services and consulting

 

After rapid pandemic-related growth, the PC market will shrink in 2023

Learn how PC companies are preparing for a slower, more price-competitive market; how the role and perception of PCs have changed; and what changes to expect in PCs in 2023 and beyond

 

 

TBR webinars are held typically on Thursdays at 1 p.m. ET and include a 15-minute Q&A session following the main presentation. A recording of the webinar is sent to all registrants the day after the live airing. Previous webinars can be viewed anytime on TBR’s Webinar Portal.

 

Subscribe today and be the first to hear about our next webinar!


State of Technology, Telecom and Professional Services Competitive Intelligence in 2023

Technology markets are more competitive and evolving more rapidly than ever before. At the same time, technology, telecommunications and professional services companies are resetting from the technology investment boom of the COVID-19 pandemic and establishing leaner operations to navigate potential recessionary conditions in 2023.
Join Senior Director Bryan Belanger Thursday, April 6, 2023, for a webinar and Q&A on the current challenging dual mandate for competitive intelligence (CI) and market intelligence (MI) teams and professionals, who are increasingly being asked to do more — deliver more insights, with higher quality and faster — with less (e.g., budget, resources, time).

 

In this FREE webinar related to competitive and market intelligence you’ll learn:

  • Which megatrends TBR is seeing across clients’ CI and MI organizations so far in 2023
  • Benchmarks on CI and MI function structure, size, growth, reporting, deliverables and tools
  • How to optimize your CI and/or MI functions for success in 2023 and beyond h

 

 

 

Previous TBR webinars can be viewed anytime on TBR’s Webinar Portal. For additional information or to arrange a briefing with our analysts, please contact TBR at [email protected].

Analytics, AI and digital transformation reach tipping point in acceleration

Gimme 3 — Insight Interview with TBR’s Subject-matter Experts

In TBR’s new blog series, “Gimme 3 — Insight Interview with TBR’s Subject-matter Experts,” Principal Analyst Patrick M. Heffernan discusses our latest and most popular research with our analyst team. This month Patrick chats with Principal Analyst Boz Hristov, who leads TBR’s Digital Transformation (DT) research portfolio and is the primary author of the Digital Transformation: Analytics Professional Services Benchmark. They discuss innovation-centric investments and vendor-specific changes in the analytics and AI space.

 
Patrick: In TBR’s January 2023 Digital Transformation: Analytics Professional Services Benchmark, you wrote, “We believe many of the innovation-centric investments vendors pursued over the past 12 to 18 months have paved the way for growth in the A&I segment, particularly as buyers seek to automate processes from knowledge work to cloud and enterprise applications.” Can you explain that connection between the vendors’ innovation-centric investments and the buyers’ desire to for more automation?
 

Boz Hristov: Innovation and cost optimization often go in opposite directions in terms of budgets and cycle adoption. Automation and analytics, on the other hand, are centered on vendors’ ability to gain trust within their analytics models and algorithms. Given the maturity of the DT market, buyers often demonstrate a willingness to experiment if new technologies provide business outcomes without disrupting ongoing operations, which has led ecosystem participants to invest in developing solutions.
 
Meanwhile, there are two main forces shaping TBR’s outlook. First, the constant nudging from technology vendors with new solution ideas has forced incumbent vendors to stay abreast of innovating their portfolios, thus helping them capture analytics and insights opportunities, provided each party in the alliance establishes relationship governance guardrails. Second, the need for reducing and managing expenses to weather macroeconomic headwinds will further necessitate the adoption of AI and analytics tools, allowing buyers to gain visibility into process inefficiencies.

 

 

Patrick: You also wrote that, “While virtually every vendor we cover touts a technology-agnostic go-to-market strategy, we expect buyer sentiment and the need for developing pointed solutions to drive a shift in behavior and messaging among services vendors.” What are some examples of IT services vendors or consultancies that have started that pivot in behavior and messaging?

 
Boz: Each vendor maintains a strong value proposition, demonstrated by steady performance at the corporate level, largely fueled by cloud. Thus, opportunities are ripe for vendors to demonstrate the value of their algorithms when it comes to managing enterprises’ DT programs from IT operations to finance and HR processes. All vendors, though, must remain mindful of the impending macroeconomic slowdown and how they demonstrate the value of their analytics solutions. To remain successful, vendors will need to manage their partner ecosystems differently, as no vendor can do it alone. As services vendors retune their partner messaging and go-to-market efforts, analytics provides a strong use case, helping vendors pivot from being vendor agnostic to capability aligned.
 
For example, Deloitte has pursued significant portfolio expansion with Amazon Web Services (AWS), Google Cloud and Salesforce as the firm strives to compete for AI-enabled, enterprisewide DT opportunities. Deloitte launched cyber cloud-managed services for AWS. The two also are co-investing in enhancing Deloitte’s recently launched ConvergePROSPERITY banking suite, making it available on AWS using Amazon Connect for contact center support and Amazon Connect Cases for call center case management, Amazon Pinpoint for customer engagement management, and Amazon Cognito for end-user security. With Google Cloud, the two recently announced a significant partnership expansion, which will include Deloitte training and certifying staff on the Google Cloud Platform (GCP) tech stack; codeveloping industry offerings for retail, consumer packaged goods (CPG), financial services and the public sector; and offering specialization around SAP in Google Cloud, AI/machine learning (ML) and security capabilities.
 
At the EY Global Data and AI Summit, EY demonstrated its willingness and readiness to partner better and differently. During one of the panel discussions, EY brought six of its data and AI partner companies ranging in size and portfolio offerings to present on stage: Databricks, IBM, Microsoft, RelationalAI, Snowflake and UiPath. The companies presented in alphabetical order so EY could avoid being accused of favoritism, a smart move further confirming EY’s willingness to partner better and bring parties together not just in a press release but also to clients. EY’s approach to partners is different from many of its peers’ as the firm does not go to market with a particular vendor unless EY uses that vendor internally. Adopting a customer-zero approach to its alliance partners elevates EY’s trustworthiness, a key element in the firm’s efforts to act as an ecosystem enabler.
 
Patrick: Stepping back from the specifics in the report, what’s something you’ve seen change over the last few years in the analytics, AI and automation space that either you didn’t expect or maybe changed faster than anticipated?
 
Boz: The role of cybersecurity remains invaluable, especially as DT programs mature and the volume of customer and enterprise data increases exponentially with the implementation of new technologies such as cloud, the edge, 5G, IoT and the metaverse. This evolution has created a federated environment for DT programs, compelling ecosystem participants to adopt more accountability and a collaboration mindset, rather than pushing the next technology from their sales toolboxes. Recent developments — such as the formal launch of OpenAI’s ChatGPT bot, which provides sophisticated responses to users’ queries, based off a large amount of data — present a strong use case for how AI can be both useful and harmful when it comes to cybersecurity. From writing phishing emails to trying to bypass OpenAI’s cybersecurity guardrails in order to develop malware attacks, malicious actors could use the technology to explore customers’ and enterprises’ vulnerabilities enabled by AI.
 
TBR believes AI and automation adoption have reached an inflection point and are ripe for further acceleration, especially as the former provides insights into business transformation revenue growth opportunities and the latter enables cost-efficiency optimization, both necessary tools in helping enterprises weather macroeconomic headwinds. Misusing AI, automation and analytics in managing cybersecurity could backfire and jeopardize clients’ trust in vendors’ models and algorithms, something they have worked for a while to establish, necessitating better ecosystem collaboration to improve processes integration and standardization.
 
Patrick: Summing up, then, Boz, I think you said “ecosystem” or “alliance partners” about 10 times, reinforcing what we’re hearing across the IT services professional services and digital transformation space. It’s all about playing nicely in the sandbox. Of course, others have to want to play with you, but sounds like the vendors you’re covering aren’t questioning their own capabilities, just trying to work better across the ecosystem.
 

Fill out the form below to receive weekly free resources and upcoming webinar invitations


Top 5 Questions To Ask When Creating Market And Competitive KIQs

Creating market and competitive KQIs

Simply gathering data and details as they come doesn’t help you move from information to intelligence in market and competitor research. Market and competitive KIQs (key intelligence questions) should always guide your discussions, and developing and deploying these KIQs require creativity and precision, mixed with experience.
At TBR we speak with people across the technology space, from partners in the Big Four consulting firms to CIOs migrating their company’s workloads to cloud and everyone in between. Captured by over 20 years in the business, check out our top tips for creating market and competitive KIQs.

Top 5 Tips for Creating Market and Competitive KIQs



  1. Top 5 tips for creating market and competitive intelligence KQIs

    1. Know why you’re asking the question: With every market and competitive KIQ, you should be able to identify what you don’t understand and why you need an answer. You’re fishing to eat, not to throw the fish back. Why are you asking this person this KIQ? What do you expect the answer will be, and how do you follow up? What would surprise you? What if this person doesn’t know the answer? What will you know once you’re done asking the question? The more you focus on why you’re asking the question, the better prepared your question will be and the more useful the answers will be. How you frame the question — “Tell me about” or “In your experience” or “I’ve heard” — doesn’t matter if you’ve fully prepared on why you’re asking.
    2. Make a plan, follow the plan, then throw out the plan: Well-prepared KIQs follow a logical progression, building on each other and allowing follow-up questions that lead to another specific KIQ. The best market and competitive KIQs interlace and don’t need to be asked in any specific order. You can follow the natural path of the conversation and still tick through your KIQ checklist because you know precisely why you’re asking each question and exactly what you’re going to know at the end. In either case (and there is no “just wing it” option), accept that your intel gathering will not always go as planned. What worthwhile discussion ever does? If you spent time figuring out why you’re asking the question, you don’t need to worry about a script or checking KIQ boxes — the discussion will happen naturally.
    3. Never say “or”: Don’t lead into your questions with options, asking “is it this or that?” because the answer will almost always be “a little bit of both,” which is useless. It’s hard advice to adhere to—I don’t follow it myself half the time. You don’t want to sound foolish by leaving out an obvious option, but you do want to demonstrate that you know what you’re talking about. If you give two options, the response almost always leaves you guessing what really matters. Instead, just state the strongest case and get a reaction. For example, instead of asking, “Which impacts retention more, leadership or compensation?” say, “Retention challenges stem directly from bad leadership, right?” Again, this is hard advice to follow because it cuts against the natural flow of conversation and how we normally ask questions. But KIQs aren’t normal questions.
    4. Not all who wander are lost: You’ve got your finely honed questions, the perfect person to answer them and a good rapport—and you’re gathering up intel like a whale eating plankton. And then your source starts wandering, using your question to launch down a path so divergent you couldn’t even call it a tangent. This is on another plane, another planet. Wander with them, and quiet the voice in your head that’s trying to get back to the KIQs. Listen even more intently. And when you hear something that pops, that resonates with all you’ve been talking about or just piques your curiosity, ask them to go further. If they started down the tangent, they’re already invested in it. Demonstrate that you’re paying attention, as showing that you understand why they brought it up (even if you don’t) will simply open the source up further, potentially surfacing issues and intel you hadn’t considered or expected. More hard advice to follow, but consider that your preparation for the answers you expected around the KIQs means you don’t have to listen as intently, don’t necessarily have to draw connections and see different versions of the same picture. Now you need to work harder to put what you’re hearing and learning into context, and that effort should produce better, maybe even unexpected results.
    5. Pass around your KIQs, to anyone and everyone: Most likely you’re not the only one asking questions, and you’re not the only one who wants answers. Share your KIQs frequently, inside and outside your organization (if appropriate), and solicit feedback. A colleague having a casual conversation with some of your KIQs in the back of his or her mind might just help you do your job, uncovering something you might not have. And I’ve found, colleagues often challenge my thinking on the first tip — know why you’re asking the question — helping me refine my KIQs by asking my reasons and what I’m hoping to learn. You don’t need to put “Key Intelligence Questions: Go Ask These” in an email subject; just share them freely and listen to the feedback and answers.

Bonus tip — Make something up: Sometimes the best prepared KIQs and smoothest plan bring you straight into quicksand, leading your discussion to a series of “yes and no,” “on the other hand,” and “a little bit of both” answers. When this happens, make something up. “We’re seeing a huge uptick in interest around Brazil right now, not sure why.” If your fiction falls flat, you move on. In my experience, people love to talk, and when presented with something they hadn’t heard, disagree with, or have a strong opinion about, they’ll talk, regardless of the starting point. Should your creativity link to your KIQs? Or course, and wicked good preparation includes imagining what your source might not expect you to ask.

After all this, you might be thinking, “But what about structuring leading questions and selecting the right sources and understanding bias and all of those other basics of intelligence collection?” To quote the great British diplomat Harold Nicolson, “I have not forgotten them. I have taken them for granted.”

Ensuring Competitive & Market Intelligence Models Suit Your Needs

Do your CI/MI models fit your business needs?

The goal of competitive intelligence analysis is to identify strengths and weaknesses of competitors, as well as potential threats and opportunities in the marketplace, to gain a competitive advantage. With market intelligence research we aim to better understand the market overall and make more informed decisions about product development, marketing, and other areas of operation.

A competitive intelligence (CI) or market intelligence (MI) model is a quantitative model of competitive and/or market performance, typically updated on a regular cadence (monthly, quarterly, semiannually, or annually). CI/MI models are built to provide data-centric insight into relative competitive performance and/or market dynamics.

Models can be as broad or specific as a CI/MI practitioner requires. You might have a model that tracks overall top-line quarterly and annual revenue and margin performance of a set of competitors that is used for reporting to your executive team. You may also have a detailed revenue and market sizing model that breaks down competitor revenue and estimated market size by industry vertical, geography, business line, and intersection of each, which is used by local market teams for competitive benchmarking and to set sales territory targets and AE quotas.

Models can be based on public data or non-public data. Models may be rooted in hard facts from 10-Qs and 10-Ks or extrapolated and estimated based on aggregation of multiple sources such as secondary research, macroeconomic data, unit data, interviews, and surveys (just to name a few).

That’s the beauty of models – they can expand and contract in scope and sourcing to accommodate the need of the moment.

What are competitive intelligence and market intelligence models?

When we think of models, we often think of financial performance and the tried-and-true P&L statement. This is undoubtedly one really important type of model. However, in practice, there are a number of different types of models that are used by CI / MI practitioners for different purposes. A deep dive on each type of model is beyond the scope of this post, but here’s a list of common models that we build for our research and/or are asked to build on a custom basis for our clients:

As-reported quarterly / annual competitive income statement and balance sheet models

  • Industry-specific financial performance metrics (for example, in SaaS, CAC, CAC payback period, churn, expansion revenue, etc.)
  • Line-of-business (reported and/or normalized) revenue and profit models
  • Vertical and/or geographic revenue and profit models
  • Attach and penetration rate models
  • Product performance and reliability models
  • Customer profiling models (number of customers, customers by account type, trajectory of customer growth and churn by customer type over time)
  • Resource management models (headcount, onshore/offshore delivery leverage, utilization, attrition, pyramid structure, delivery process and operations, management span of control)
  • Sales and GTM efficiency and productivity models (revenue per sales employee, sales coverage and pyramids, quota and territory modeling)
  • Sales and GTM structure models (sales span of control, accounts per rep, reps per account, sales headcount)
  • Price and discounting models
  • Vendor revenue and profit forecasting models
  • Total Addressable Market (TAM), SAM (Serviceable Available Market), and SOM (Serviceable Obtainable Market) Models
  • Vendor market share models


Nothing Found

Sorry, no posts matched your criteria

Why build CI/MI models?

My colleague Allan Krans, leader of our cloud practice at TBR and expert practitioner in building models, wrote a great blog answering this question, so there’s no need to go deep on that question here. Models are critical for many reasons, and those reasons can vary with each and every type of model, as well as the specifics of a given project.

Overall, however, models are critical tools to help quantify an objective basis for competitive and market performance measurement. Models provide a fact-based orientation to align executives and stakeholders around when considering recurring and/or pressing strategic questions.

The ‘business need’ imperative

There’s a common saying in the world of statistics, usually attributed to statistician George Box, that says “all models are wrong, but some are useful”. Over my decade or so building financial models and delivering market research to large technology companies, I’ve heard versions of the same thing – “anybody can build a model and make assumptions in a spreadsheet” is a common refrain.

If we accept that models are by definition wrong to some degree, what makes any model “useful”? For us, that comes down nearly completely to how well the model is bult to support a business need. If a model can be used effectively to solve the business challenge and answer the questions it was designed to answer, it is successful and valuable. Otherwise, a model is just a bunch of numbers and assumptions in an Excel spreadsheet.

How to make your CI/MI models fit your business needs

There’s no one playbook or set of “hacks” that can help you build models that are actionable for addressing your business challenges. For that, only collaboration and iteration (read: hard work) will do. However, there are a number of key success factors that we believe can help ensure that a CI/MI modeling effort is aligned to your business needs. We explore each of those factors below.

  • Don’t skimp on getting to the “why”: At the risk of stating the obvious, before any model is designed or built, you should spend as much time as is needed to deeply understand the business challenge or question at hand from multiple stakeholder perspectives. Ensure that all parties, including those building the model as well as those that will consume the outputs, can articulate, and agree on, the challenge that requires modeling insights, as well as the decisions that will be made based on those outputs. Define desired outcomes individually and align those to a single collective and holistic outcome for the exercise.
  • Decompose the “why” into its key elements: The outcome of defining the “why” might be a complex and multi-faceted question statement – something like “Why is XYZ business unit gross margin declining?”. To translate that into an actionable project that could be addressed with a model or other solution, it’s important to decompose that question into its various sub-questions and scoping elements. A key part of this consideration is the level of granularity and validation that is needed in an answer to the question posed. Using our example, you need to decide on which competitors you are going to include in your benchmark, and how you will include them. Perhaps you need to evaluate the question and competitors you’re planning to study at a global level, or perhaps it’s a more granular investigation that involves five or seven key geographic markets, vertical and customer segment breakouts, and additional metrics. Maybe you need a quick answer for the past two calendar years, or perhaps you need a full quarterly breakdown for five years of historical data and two years of projected future data. Aim to take your high-level “why” and break it down into its fundamental elements and get agreement on those elements in addition to the top-level goal.
  • Make sure a model is the right solution: Sometimes, a model can be a solution in search of a problem. It’s critical to pressure test the business challenge to ensure there is a true need for a modeling effort. Perhaps a set of customer quotes or pulling a PDF from a recent competitive presentation is all that a situation requires. As noted above, a key element of this is determining the level of validation and granularity that is needed to answer the question. Considerations to factor in at this stage are the audience that is consuming the modeling, importance and urgency of the question(s) posed, timeline (is it a one-time project need or something that should be tracked quarterly), and available budget and resources to deploy to answer the question.
  • Establish an owner/SME: Lean on a RACI matrix here, or whatever version you use within your organization. There should be a single individual or team that is responsible for the modeling effort that you’ve designed. This person needs to serve as the SME for the modeling outputs, as well as the champion that ensures the model and accompanying insights are effectively and efficiently disseminated to those within the organization that need them to make decisions. Collaboration and ownership are critical to success.
  • Define parameters and limitations: Behind every good question is another 100 questions. It’s important to set proper parameters on what will and won’t be delivered by the model you are creating, and what questions the model will and won’t answer. It’s equally important to set the context on how you are collecting the modeling information, and what level of validation the model corresponds to. For example, are you running a global survey of customers to inform an attach model? Or are you making top-down estimates based on publicly available 10-Q and 10-K data on services revenues and unit sales? This will clarify the business need and questions that are being addressed with your CI/MI modeling effort. This will also help condition stakeholders to proactively identify opportunities for new future CI/MI models when they arise, versus trying to shoehorn questions into existing models and processes.
  • Socialize a framework before starting: Before you launch any modeling, start by building an empty model template in Excel. Populate with dummy data if you like. Create something that visualizes exactly what will be delivered as the output of your modeling effort. Now socialize that framework with the stakeholders that will consume and act on the modeling outputs and insights. This step will help align your team around business need and the outputs that will be generated to address that business need before the work starts, potentially saving you hours and hours of rework down the line.
  • Start with an MVP to get the ball rolling: Let’s go back to our example company that is considering a competitive modeling effort to understand gross margin in a particular business line. If building for the first time, that company has a few options – they can build the “dream house” version of their model with tens of competitors, vertical, geographic, and customer segmentation, and multiple bottom-up sub-metrics. Or they could start with a leaner approach that aims to establish initial answers on competitive gross margins at a global level for the business unit in question. In most cases, the leaner approach is a better place to start. Why? The nature of business needs changes all the time, and hypotheses that inform the development of models change as a result. It’s often better to get something shipped first, answer initial questions, refine hypotheses, and build to greater complexity over time, versus taking on everything at once before building coalition and refining use cases for your model outputs.
  • Purpose-build for iteration: Once you actually get started, don’t just dump a set of models on your busy stakeholders after six or eight weeks of data collection and building. Deliver results as quickly and iteratively as you can and seek feedback at each stage. This goes hand-in-hand with an MVP approach. Building a set of gross margin models on 10 competitors? Pick one or two to start with and ship initial models for those competitors in the first week or two. Present, distribute via multiple channels, gather feedback, and adjust the process for the rest of the program.
  • Normalize at every stage of the process: This is a key foundation of all the CI/MI modeling that we do at TBR. To fit models to business needs, you need models that are easily compared to your business. The most obvious and apparent need for normalization is when designing a model structure. Let’s say, for example, that you are building a competitive line-of-business model for a particular business unit. It’s likely that you don’t exactly report revenues for that business unit the same exact way as your competitors. Before the first numbers are crunched in any modeling effort, great care must be taken to establish a strategy for normalizing results into your company’s view of the world (your business unit taxonomies, your definitions, etc.). Specific tactics for normalization are beyond the scope of this post, but are a foundational success factor for designing models that are consumable and actionable.
  • Measure, debrief, and restart: Nothing is going to be a slam dunk out of the gate. To fit CI/MI models to business needs, you need to treat modeling as a continual process that ebbs and flows with the changing needs of your business. Define KPIs for your modeling effort and make sure to measure them frequently. Was the data used? How was it used? What decisions were made based off of the model and were they effective? Use this information to revisit your modeling program design, identify and implement optimizations, and restart the process for the next month, quarter, half-year, or year, depending on your chosen cadence.

Interested in learning more about how we build CI/MI models at TBR? Have a question about the approaches and methodologies we use to help our clients implement modeling programs that embody the above foundations? Contact us today to learn more!


The Top Metrics You Should Be Modeling In Competitive/Market Intelligence (CI/MI)

TBR dives into the top categories of metrics and specific metrics that we typically see as part of a foundational CI/MI modeling program