Key findings from TBR’s upcoming HCI customer research

Hyperconverged infrastructure (HCI) is a growing market ripe with opportunity for vendors. TBR forecasts the market will reach $11.7 billion by 2022. Although TBR research indicates that incumbent vendors with a strong presence in the converged infrastructure (CI) market, such as Dell EMC and Cisco, have an advantage in the space, findings also indicate that a growing number of smaller vendors are rising in popularity. Add to that the approximately one-quarter of existing customers who indicated that brand is not a key factor in their decision making, and it becomes clear that the opportunity to take share from existing vendors is high. Further, with nearly three-quarters of respondents indicating they have not yet taken the plunge into the HCI space, there is massive opportunity, through strategic marketing and support, for vendors to encourage new adopters to be their customers.

HCI has a significant place in the cloud market

Eighty-four percent of respondents indicated they are leveraging HCI for either hybrid or private cloud installations. TBR believes this suggests that cloud is not necessarily an inhibitor to HCI adoption, as some vendors may perceive. Further, we believe this signals that consumption-based pricing options, which 81% of respondents indicated they would be interested in considering in the future, will encourage more HCI adoption. Consumption-based pricing enables customers to select HCI for a capex solution as well as for public cloud if they choose, and they can simply compare performance and other features between the two to make purchasing decisions. Vendors can capitalize on this flexibility with strategic marketing.

IT leaders play a crucial role in the HCI decision-making process

HCI remains a strategic purchase, as evidenced by the fact that 74% of respondents indicated IT directors and managers were one of the decision makers. TBR believes that as customers become more familiar with HCI and their HCI vendor, they will be more likely to make repeat purchases and will be less likely to demand direct-from-vendor sales.

To learn more about TBR’s Hyperconverged Platforms Customer Research, contact Stanley Stevens ([email protected]) or your account executive.

 

Democratization now: It’s good for business

Data democratization is a hot topic now. Spokespeople from Google, SAP, Capgemini and other tech companies have spoken and written about how making data available to as many people as possible will both unleash the power of technology and prevent abuse of closely held data. Microsoft CEO Satya Nadella sprinkles his talks and interviews with references to democratization. TBR agrees that data access is critical to achieving artificial intelligence’s (AI) considerable potential, but access is not enough. For AI to do what it can do, business people with domain knowledge, who are regular users, must be able to work directly with data, without intervening layers of developers and data scientists.

Data access is a conundrum. Ensuring appropriate privacy and security while making data available to as many people as possible is a challenge, one that is inhibiting the growth of widespread AI-driven data analysis. This post will not address that challenge, however. It focuses on one of the other growth inhibitors: the current need for data experts, scientists, engineers and janitors, as well as developers, to extract the value from data.

Business users might see the hierarchy of data experts as a priesthood or a bureaucracy, standing between them and the data, but that is not really what is happening. Currently, there are no tools with which business users can conduct their own analyses, at least not without a lot of preparation by the data experts. Better tools are coming; there are R&D efforts worldwide to make data more directly accessible, which is part of what Nadella and other spokespeople are talking about.

Before these democratic tools are made available, there is strong growth in AI and the utilization of data analytics, because the value is there. But the need for experts greatly increases the cost of analysis, so only analyses with the highest potential value are performed. As more democratic tools become available, many more analytic projects will be worthwhile and the use of analytics will grow much faster.

The impact of democratized analytics tools will be huge because the costs associated with the data expert hierarchy are great. Those costs go beyond just personnel. Communication between business users and data experts is time-consuming and expensive, and it lowers the quality and value of the analyses. Business users and data experts live in different worlds and have different vocabularies; misunderstandings are common. Misunderstandings are expensive, but what is worse, working through intermediaries slows the iterative process by orders of magnitude. The potential value of data lies in insights, and finding insight is an iterative process.

The history of business technology is a progress propelled by increasing democratization of tools. The PC itself is prime example, making computing directly available to business users. The internet rode a wave of disintermediation and self-service to its current global saturation. In terms of democratization of AI analytics, the best parallel is the PC spreadsheet, which made it possible for business people to create and tune their own quantitative models of business activities. Before the spreadsheet, creating those models required coding.

“Spreadsheets for AI,” one of which may well be a version of Microsoft’s Excel, will accelerate growth in analytics, data access, storage, cloud services and the Internet of Things. AI spreadsheets will not retard growth in the use of data experts; they serve a different market. Even with very good first versions, broad adoption will take years, so the acceleration of growth will not be sudden. Over the years, however, the ability of business users to directly analyze their data will contribute substantially to the revenue of IT vendors and to that of their customers.

 

Critical success factors for successful pricing research

In my day-to-day life at TBR, I regularly interact with clients seeking to undertake pricing research. Their needs are varied. Some want to understand pricing for a new product or service or sustain their competitive position for an existing offering, while others seek to design an overarching commercial strategy or to increase the effectiveness of their sales teams by arming them with tactical data and insights — and nearly all are focused on influencing revenue and margin.

Capturing pricing data that can be utilized defensibly for decision making is challenging. All pricing is situational and can be influenced by any number of factors. Pricing decisions influence, and are influenced by, nearly all organizational departments, from sales and finance to product management and business strategy, and thus are often highly politicized within ICT enterprises.

Based on our regular experience in serving the pricing research and consulting needs of our client base across ICT industry segments, we have identified five critical success factors that can help clients navigate these challenges:

  • Start with outcomes: We often find that our customers come to us with a research concept in mind, but not a defined goal or set of operational plans for how the research will be deployed in their organization. Sometimes the request is: “We need to know what vendors like us are charging.” But the real goal of the team may be to answer the question: How can we be more efficient in resourcing deals? By starting with the end goal and use case in mind, we find that we often explore areas adjacent to pricing, and that insights on those topics, in concert with pricing data, unlock business value for our client base.
  • Focus on business impact: For all the research we do at TBR, including in pricing, we advise our clients to frame all research needs around the underlying business impact. We design projects, including the questions we propose to cover in primary research and the data that we seek to capture, to ensure that the recommendations we deliver around pricing aim directly at influencing business strategy, revenue and profitability.
  • Focus on context: Our pricing research methodology relies on interviews with vendors and customers. This approach allows us to capture not only pricing data but also contextual data and insights on topics such as discounting, commercial incentives, pricing structures and portfolios. When paired with core quantitative pricing data, these types of interview-driven insights provide predictive value focused on vendor and customer pricing and consumption behavior.
  • Build market constructs: To normalize against deal-specific influencers that can impact a true view of market pricing, we design our research to focus on deal constructs. These constructs are used in all interviews to ensure apples-to-apples comparisons and that we are characterizing a full spectrum of potential price points. Context on topics such as discounting is addressed through qualitative conversations.
  • Consider adjacent markets: Many times, particularly with clients seeking to stand up pricing models and price levels for new offerings, we find that the direct peer landscape may not be the best basis of comparison. By looking at adjacent offerings and considering how similar-yet-adjacent offerings are packaged and delivered, clients are able to gain a broader foothold in their peer landscape in its entirety, and often identify areas to elevate value proposition and raise prices accordingly.

 

The next 5 years: A successful strategy for Infosys

Updated available: Click here to read about Infosys’ 2025 strategy in this new TBR blog, Infosys’ Future: Scaling GenAI and SLM Innovation to Drive Growth and Stakeholder Trust.

 

In July, after resuming his role as executive chairman, N.R. Narayana Murthy said the following about Infosys’ future: “The strategy is to focus on opportunities from consulting-led end-to-end solutions, leveraging technology for higher margins, developing intellectual property-based solutions to delink revenues from effort.” Murthy set three broad goals — improving sales efficiency, increasing automation and boosting employee productivity, and rationalizing cost — but early indications show Infosys making the third goal its priority as the company has been moving to a substantial onshore/offshore ratio shift. Currently at a 35-to-65 ratio, Infosys’ goal is a 10-to-90 ratio weighted to low-cost resources, ultimately to preserve margins as the company refocuses on large low-cost outsourcing engagements.

 

After setting policy, Murthy oversaw executive-level personnel changes, letting go the leaders who had been in charge while Infosys’ India-centric peers outpaced the company (see following chart). Murthy kept some key initiatives, including Infosys 3.0, which could determine how close Infosys moves to market leaders Accenture and IBM. Launched in 2011, Infosys 3.0 is a long-term growth accelerator, especially as it melds transformational consulting with emerging technologies. However, Murthy and his new team must provide time and support, both in building the 3.0 engine and focusing on low-end commoditized engagements. 

 

TBR believes Infosys must take three strategic steps to achieve its long-term goals in current market conditions:

  • Build up nearshore Americas capacity and capabilities
    Infosys needs to serve the U.S. market better, either with resources on the ground in the U.S. or nearshore in Latin America. The potential growth for any IT company in the U.S., Canada, Mexico and Brazil demands a substantial investment, and India-centric firms cannot rely on the vagaries of the U.S. visa system. Infosys tried to hire mid- to senior level, U.S.-based consultants in the 2000s, but the effort stalled when the company could not find the right people or receive permission from clients to engage in higher-level consulting work. Infosys opened a 200-person BPO center in Atlanta and a 100-person delivery center in Costa Rica in 2013; however, the company still lags in this critical market relative to peers.

  • Acquire consulting capacity in Europe
    Infosys can continue to serve European clients with outsourcing services based nearshore (in lower-cost European countries such as the Czech Republic and Poland) and offshore, but if Infosys wants to shift its consulting/outsourcing revenue ratio from 35-to-65 to closer to 50-to-50, the company must gain more wallet share from EU clients. Infosys recognized the need to move upstream in Europe when it purchased Lodestone in 3Q12 and committed to reorganization on the continent in 2013, but the company must continue acquiring talent that buys permission to play in the management and technology consulting space.

  • Invest in IP
    Global leaders Accenture and IBM separate themselves from Infosys and its peers with IT innovation, bringing together strategy and emerging technologies to create tech-enabled solutions specific to customers’ needs. Infosys started down this path through the development of its Edge Platform suite, including BigData Edge, a comprehensive cloud-based offering for aggregating, analyzing and processing analytics data from internal and external sources; but absent a sustained strategic approach through customer-centric, acquisition-enabled or research-driven IP, the company risks seeing commoditization strip out every difference between Infosys and its India-centric peers.