The tech industry is at a seminal moment. The combination of executive and board level interest, clearly defined outcomes, and the sheer speed of adoption makes Generative AI unlike anything we have seen before.

In this blog, we will shed light on the rapid rise of Generative AI (GenAI), its impact on tech companies, and fundamental questions related to AI technology.

The rapid adoption of Generative AI moves AI from an emerging software segment in the stack to a lynch-pin technology at the center of a platform transition.

Meredith Whalen – Chief Research Officer

GenAI – A Seminal Moment in Technology

In seven short months, GenAI has simultaneously captured the attention, imagination, and trepidation of tech and business leaders across the world.

Attention. Executives easily see how this technology will impact productivity levels and margins. The Brookings Institution forecasts GenAI will raise productivity and output by 18% over the next 10 years.
Imagination. GenAI has a wide range of applications – from horizontal use cases such as software development and marketing content creation to industry-specific use cases such as drug discovery and manufacturing design. The business benefits of the use cases are obvious, and enterprises aren’t waiting around for a business case to be developed to start experimenting. IDC’s research shows that knowledge management, marketing, and code generation are the top use cases being considered.
Trepidation. Executives see how this technology can rapidly disrupt their business model. The 20-year journey for the cloud to represent 50% of core IT spending and the 10-year journey to become a digital business will look colossally slow in comparison to the accelerated timeframes it will take for enterprises to implement Generative AI use cases at scale. The well-founded concerns around ethics, regulatory compliance, and governance will also need to be embedded in this new business model.  

Hiding in Plain Sight

How did technology with this much impact creep up on most business leaders? It didn’t. The foundational elements were being developed throughout the past decade.

Era of Multiplied Innovation. What IDC refers to as the Era of Multiplied Innovation was primarily fueled by the cloud, mobility, and the Internet. Low-cost semiconductors and virtualization enabled the cloud, which made computing elastic and plentiful. Mobility made computing ubiquitous. And the internet dropped the costs of distributing those computing bits to almost zero.
Platforms and Communities. With abundant, ubiquitous, and elastic infrastructure in place, platforms, communities, and digital ecosystems emerged. These platforms triggered a massive data consolidation process and the birth of the transformer model architecture which enabled the creation of foundational artificial intelligence models, including large language models (LLMs).
Era of AI Everywhere. Generative AI, which utilizes unsupervised and semi-supervised algorithms to generate content from previously created content such as text, audio, video, images, and code, is a trigger technology that will usher in a new era of computing – the Era of AI Everywhere. This new era will include the journey from narrow AI to widening AI and will completely change our relationship with data and how we extract value from both structured and unstructured data.

Generative AI triggers the dawn of this new era because it will drastically reduce the time and costs associated with developing solutions for a wide range of use cases associated with automation and intelligence. The rapid adoption of Generative AI moves AI from an emerging software segment in the stack to a lynch-pin technology at the center of a platform transition.  The market generally assumes that this type of platform transition requires a shift in hardware, similar to the move to client-server from mainframes, or to the cloud from client-server.  However, IDC believes that this time it will be different. This platform transition will focus more on data. This time it will be about how we use data as an input (to train, fine tune and infer foundational models) and as a business outcome (as part of the development of new use cases).

GenAI and Tech Industry Market Disruption

As Generative AI will impact most tech markets from semiconductors to professional services, tech suppliers are rapidly revising their product roadmaps and rethinking their business, pricing, and customer service models.

Infrastructure. Today, much of the value is being captured by semiconductor vendors, most notably NVIDIA, as running the training and inference workloads for the foundation models demands significant GPUs. Semiconductor providers need to have chips specifically designed for AI workloads, which is creating an opportunity for new challengers. Training AI models will also drive storage and networking investments, putting public and hybrid cloud providers in a solid position to capture share since dedicated on-prem training of foundation models is expensive.

Software. In the medium-term, well-entrenched platform and application vendors stand to benefit if they can pivot their offerings and business models fast enough. They must decide which Generative AI use cases can support direct monetization, and which will be important to implement from a defensive point of view.  For example, generative AI could transform the way we interact with enterprise software. It is potentially the biggest shift in UX design since point and click and poised for disruption by GenAI native applications startups.

As it looks like many of the costs associated with managing Generative AI models for scale, security, and privacy will fall on the shoulders of the software provider, the following key decisions are being evaluated to protect their margins:

Should they train their own foundation models or partner with model providers?
What is the new pricing model to support Generative AI capabilities?
Will SLAs need to include grounding for some use cases? And if so, should levels of support be added to deal with context and data drift?
Will getting access to customer data to train models be a part of a new set of licensing terms and conditions?
Do they need to provide indemnification on AI-generated assets?

Services. While service firms are busy helping their clients identify GenAI use cases, they are simultaneously investigating how GenAI will impact the demand for their services over the long term and how their delivery models around software development, accounting, and legal services will be automated.  Increasingly, services firms are bringing their own AI software platforms to engagements which is blurring the lines between software and services.

Security and Trust. Due to its ability to generate fake code, data, and images closely resembling the real thing, Generative AI is likely to increase identity theft, fraud, and counterfeiting cases. The LLMs are also vulnerable and could be a source of attack and manipulation. Security vendors have a ripe opportunity to develop new solutions to address these emerging challenges.

New Markets. Of course, with any disruptive technology, new technology markets will spawn. Start-ups are already emerging to provide tools to personalize models, provide contextualization for the model, increase the speed of training LLMs, and orchestrate the process. There are huge opportunities for software companies to meet the market where it stands. It may mean offering a full-stack translation service rather than translation software.

Despite all the unknowns facing the tech industry, what is clear is the need to quickly get your arms around the fundamental questions related to Generative AI and how it will drive your business model in the future.

If your organization is interested in partnering with IDC to better understand how Generative AI will impact the markets most critical to your success contact us.

We also recommend you take advantage of these recent resources from our thought leaders and tech market experts:

IDC Webinar: Unlocking Business Success With Generative AI

IDC Blog: Generative AI: Mitigating Data Security and Privacy Risks

IDC eBook: Unlocking the Power of Generative AI

IDC Blog: Can ChatGPT Transform the Customer Experience?

IDC’s Future Consumer team just released the latest version of the Consumer Market Model (CMM). The CMM is a unique dataset that provides insight into the size of the consumer market and opportunities in individual market segments.

The data set quantifies the future consumer by providing the following data points: socioeconomic profile, internet users, home internet access, devices used to access the internet, hours spent online, internet user online activities of dozens of digital services and experiences, internet buyers of the same digital services and experiences, and B2C ecommerce spending.

This research also quantifies consumer engagement with dozens of online activities and ecommerce categories. For online activities, engagement is measured across total users, those users that spend, and aggregate spend for each activity across 51 countries with 7 years of historic data and 5-year forecasts.

The world population is now roughly 8 billion, with nearly 5.5 billion being between the ages of 15 and 64. There are over 2.3 billion households. Each individual and household is a potential customer of consumer goods and services.

With nearly 5.5 billion internet users worldwide, the overall addressable market for online, or digital, consumer goods and services is massive. Moreover, the addressable market continues to grow with internet users forecast to reach 6.2 billion in 2027 as roughly 800 million net new users come online through the 2022-2027 forecast period.

Growth in Mature and Emerging Market Opportunities

Consumer engagement is growing across mature and emerging digital experiences. Among the mature user experiences, video streaming (4.7% CAGR), music streaming (8.0% CAGR), e-books (8.5% CAGR), gaming (6.7% CAGR), podcasts (5.8% CAGR) and cloud backup (10.8% CAGR), hundreds of millions of net new users will be added to the worldwide market during the 2022-2027 forecast period.

Tremendous growth is forecasted for emerging consumer market opportunities as well. Telehealth (12.0% CAGR), online fitness (6.3% CAGR), smart home services (7.5% CAGR), and micro mobility (9.3% CAGR) all are forecast to post strong growth in terms of worldwide users. Not all these users will be paying users, but this speaks to the need for strategies and technologies to support content, service, and experience monetization inclusive of paid a la carte, paid subscription, ad-supported, and hybrid models.

Consumer Trends to Watch

Beyond the continued growth of consumer market segments and monetization models, other key trends to watch include:

Content creation. Consumers as content creators and consumer engagement with independently created content is a key transformative digital experience. This represents a risk not just to legacy news platforms such as digital newspapers but also high-engagement digital services such as streaming video subscriptions. As individuals continue to engage as creators and consumers of content, overall time spent on social and content sharing platforms and share of advertising dollars will shift from other services.
Impact of artificial intelligence (AI). AI’s potential impact on the future world can hardly be overstated at this point. Its impact on the consumer market will be felt across everything from optimized customer segmentation and recommendations to content creation. AI-assisted creator solutions will surely come into play as will the continued growth of content created entirely by AI.
Generational shifts. IDC’s consumer team keeps an eye on how younger generations engage with technology in ways different from older generations. The behaviors of Gen Z and younger Millennials appear likely to be transformative and drivers of new opportunity growth and legacy behavior decline.
Economic uncertainty. While the outlook for the economy remains uncertain, this does not necessarily mean the growth of digital consumer service engagement will decline. Some may prove to be relatively recession-proof just as legacy pay TV generally was. Shifts in consumer spending to home health monitoring, online fitness, less expensive banking and financial services are among the key areas to watch.

Next Steps

Opportunities in the consumer market range from B2C to B2B2C. Of course, there are opportunities for companies that sell direct to consumers, whether content, applications, experiences, goods, and services. While the consumer market for digital applications and experiences can sometimes appear to be dominated by large companies, scores of smaller ones actively drive innovation and achieve success.

IDC is beginning to map out the extent to which these large companies offer products and services in the various segments of the consumer market to show their relative strength and their weaknesses or gaps. Opportunities also exist for vendors to provide the enabling technologies, in a B2B2C context, that support consumer services. For these companies, understanding emerging trends in the consumer market is critical to staying ahead of demand and creating innovative solutions that enable B2C companies.

For example, winning opportunities associated with the growth of consumer content creation range from providing tools (devices, software, and services) used by creators to enabling content distribution and monetization.

IDC can help you identify opportunities in the consumer market. The CMM quantifies consumer engagement and spending across dozens of opportunities, and engagement with the analyst team can help you target these opportunities through custom segmentations, competitive analysis, and consumer needs assessments.

It’s no secret…generative AI offers immense potential in a multitude of ways in the tech world. And we’ve only begun to scratch the surface when it comes to digital commerce.

The internet has been full of buzz about the newest high-profile AI-based tool on the block, ChatGPT.  If you believe the hype, it’s the latest technology publicly poised to disrupt content marketing, customer service, creative jobs, digital commerce, and even skilled labor jobs.

However, ChatGPT was not the first product, nor is it the only product, with the potential to disrupt the paid search and knowledge work industries. While ChatGPT may dominate the airwaves, assistive authoring and search technology has been around since 2020.

The future of ecommerce customer services is here but is not a replacement for human operators.

Heather Hershey – Research Director, Worldwide Digital Commerce

GPT-3, or Generative Pretrained Transformer 3 from OpenAI, is the backbone for Jasper.ai and other intelligent cloud-based content writing applications. GPT-3 was first publicly released by OpenAI on June 11, 2020. Since then, it has been widely adopted by chatbot developers, content writers, and machine learning researchers for a variety of natural language processing (NLP) tasks, such as summarization and translation.

GPT-3 is based on the concept of “generative pretraining”, which involves predicting the next token in a context of up to 2,048 tokens. This means that it can learn from a huge amount of data and produce results at scale, making it a powerful tool for businesses that rely on content marketing and sales to drive their digital commerce success.

However, GPT-3 still struggles with long forms of content and is derivative of content that is already published on the public web. With time and larger language models, this problem will likely be ameliorated, but right now, it is still in essence an elevated form of autocomplete.

When it comes to digital commerce and customer experience (CX) the big question is, “can ChatGPT provide customer service, write blog posts and personalize eCommerce shopping for customers?”

In IDC’s 2022 AI Path Survey, 224 respondents who use AI applications for digital commerce indicated that predictive analytics (67.4%), product recommendations (59.4%), and commerce website personalization (58.5%) were poised to bring the most value to their commerce operations. This is an indication of the strength in using these emerging customer experience (CX) technologies.

ChatGPT and other generative AI technologies offer a unique ecommerce experience that may allow customers to benefit from the convenience of personalized shopping and fully automated 24 x 7 customer service on-demand. By leveraging browsing history, purchase records, and other metrics related to a user’s behavior, these chatbots may soon become an integral component of personalization engines for ecommerce sites, enabling more precise product suggestions as well as improving customer service through automated support channels.

While these technologies are designed to disrupt the customer service industry, they are still in beta form, cost prohibitive for smaller companies and can produce incorrect or biased information. It’s only a matter of time before these technologies evolve far enough to improve the overall customer experience of online shopping by streamlining the search process and increasing the chance of successful conversions with automatically sales-optimized conversational commerce. The future of ecommerce customer services is here but is not a replacement for human operators.

If your company wants to leverage generative AI for personalized shopping experiences, proceed with a critical eye on longtail keyword strings shoppers use when searching for specific products. AI needs to overcome this known technological performance constraint of complex queries to be useful as a personal shopping assistant.

Close hits may not be good enough for modern shoppers to act upon the recommendation.
Customers demand satisfaction when shopping for specific products online and often use long strings of keywords to formulate complex queries when searching for what they desire.
Technically speaking, overcoming the known limits of longtail search is much easier said than done. Most keyword strings are only about three to five words in length. Strings that exceed these limits can frustrate customers and push them into the weeds as they search.
Customers are not trained on how to “talk to the bot” to get the best search results when shopping online. Therefore, the bots need to learn how to recognize various competency levels and meet the customer where they are the most comfortable. This will also ensure optimal user accessibility when these technologies are deployed for digital commerce.

Even with these limitations, the prospects for the future are quite tantalizing. GPT-3 and ChatGPT could represent powerful tools for enhancing personalized product, search, and shopping experiences. By analyzing customer data such as browsing history, purchase history, and other behavioral metrics, AI-driven technology like ChatGPT can provide more accurate recommendations and product suggestions based on an individual’s preferences and needs.

After a year of disruptions like high inflation, war, geopolitical tension, energy shocks, and the anticipation of recession in major countries, it’s no surprise that IT leaders entered 2023 with a mission to minimize technology investments and develop plans for executing spending cuts if conditions worsened. Despite the uncertainty, their teams were running full tilt, filling open positions and “catching up” with the business.

Then along came ChatGPT. Suddenly, IT leaders find themselves planning for the coming Artificial Intelligence (AI) onslaught and asking, “Are we prepared?”

The Threat of IT Malaise

For the first few months of 2023, IDC noted that economic and IT spending outlooks of IT leaders in our monthly Future Enterprise Resiliency & Spending surveys began to improve. IT supply chains loosened, China reopened, energy shocks failed to develop, and the recession continued to be a worry for the future, not a reality of today.

In March, the Silicon Valley Bank failure, a series of banking problems, and concerns about a US debt default canceled out much of the growing economic optimism in the US and Europe, but not in Asia Pacific countries. A more troubling new concern that IDC heard from IT leaders starting in May was that the continued “waiting for recession” is starting to affect economic and IT investment assumptions for 2024, not just 2023.

It became easy to conclude that CIOs and IT leaders should be hunkering down to ride out an extended period of economic uncertainty and IT malaise, focusing on constraining new expenditures and optimizing the use of existing assets. While sustaining efforts to establish cloud economic practices is important, it’s no longer the top priority. Now is the time to start preparing for AI Everywhere.

Innovation Beyond IT Is a Rejuvenator, but Creates Disruption

Leveraging technology to drive innovation in our daily lives has always been a key expansion driver for the entire IT industry since the start of the computer and digital communications eras of the 1950s. The most significant technology driven transformations, such as the advent of the Internet/Web and the launch of the smart phone/cloud era, occurred at times when economic conditions were uncertain, and questions were being raised about the marginal utility of new IT investments.

In both cases, individual consumers and business leaders “got ahead” of IT leaders, driving long term fundamental changes in IT architectures and the role of IT organizations. Because IT leaders were unprepared, most organizations found themselves following a “Fire, Aim, Ready” pattern resulting in unnecessary duplication of work and data/application fragmentation. Those IT organizations that were prepared in advance, executing a “Ready, Aim, Fire” strategy, emerged as the leaders in the new wave.

Generative AI Is the New Trigger but Requires Preparation Now

In this time of “perceived” IT malaise, the emergence of generative AI exemplified by ChatGPT and Dall-E with all their possibilities and shortcomings, has captured the attention of individuals, educators, businesses, and governments around the world. As IDC found in conversations with CIOs and IT leaders, the assessment and use of AI is starting to dominate the planning and long-term investment agendas of businesses across many industries, triggering what IDC anticipates will be a period of extending AI Everywhere.

The semi-good news for most CIOs and CTOs is that generative AI products and services are still limited in availability and will be relatively immature for the rest of 2023 and early 2024. Making hard decisions about commitments of significant treasure in a period of economic uncertainty will remain limited for all but a few organizations.

Every CIO and CTO, however, needs to start committing time and intellectual capital right now to ensure their organization is prepared, avoiding missteps and capitalizing quickly on the potential of AI across both IT and the business. The keys to ensuring your organization’s AI preparedness are assessing your level of AI awareness and determining your state of AI readiness.

AI Awareness: Take Stock and Aim for Consistency

Generative AI services like Jasper and Microsoft 365 Copilot, as well as all the buzz around foundation models, are the “bright shiny objects” right now. Everyone in the organization wants to talk about how they can transform everything from customer service to code and product design, but AI-enhanced capabilities in the areas of prediction (e.g., threat detection and digital twins) and interpretation (e.g., machine vision) are also likely to be well underway in selected parts of the organization.

Now is the time to conduct a comprehensive view of where in the organization AI initiatives of all types are underway. Asking, “What do we think AI can do and not do?” Use this effort to identify early areas where duplication threatens, or collaboration beckons. It can also help you identify gaps where business leaders may be missing critical opportunities because they are distracted by one shiny object.

A key next step is to develop a series of persona-based AI awareness education activities that span from the C-Suite and business/IT leaders to front line employees and even critical customers and partners. The goal isn’t to make everyone an AI expert. It’s to ensure that your organization is consistently “AI aware” as readiness assessments start, and commitment decisions are made.

AI Readiness: Focus on Cloud Native, Hybrid Cloud, and Control

As with many innovations, the ability to quickly adopt a transformational technology is determined by the existing level of technical sophistication and IT operational maturity of the organization. For example, companies that aggressively adopted virtualization as a technology for deploying and managing workloads on their own systems were able to more effectively adopt early public cloud infrastructure solutions that leveraged similar foundational technologies.

Cloud providers will play a significant role in the early introduction of generative AI enablement services and agile DevOps teams will play an equally important role in translating AI capabilities into useful business outcomes. Cloud pioneers and pacesetters with mature cloud operations and architecture models along with well managed DevOps processes will be better prepared to leverage AI than cloud laggards.

Beyond the cloud-native maturity noted above, IDC believes that companies with mature “hybrid-by-design” cloud strategies will be well positioned to take full advantage of AI innovation across many different cloud environments as well as across many different locations, core, and network to edge.

Now is also the time to ask, “Are we ready for AI Everywhere?” The key areas to conduct a critical AI readiness assessment will center on control.  How consistent/inconsistent and open/siloed are data management and data use practices/guidelines? How standardized/fragmented and trustworthy/unreliable are code creation and life cycle systems and standards? How mature are FinOps and Cloud Cost Optimization practices?

Addressing the data questions will accelerate the need to address responsible AI governance and ethics with forethought and readiness. Mature cost and ROI tracking will be critical since “cost” will remain one of the most unpredictable elements of generative AI rollouts for the next several years.

The tech industry is thrilled by the possibilities of AI! This includes silicon designers, cloud providers, software and services clients, and even your own IT teams. The sense of anticipation and even giddiness is palatable, signaling a renewed focus on innovation as the driver of technology. Success, however, depends upon you having confidence in the ability to accurately track and link near and long-term costs with desired business benefits.

Cost/benefit readiness is the key skill required when it’s time to commit to AI, especially in this time of economic uncertainty and the threat of succumbing to IT malaise.

As the old adage goes, “A smooth sea never made a skilled sailor.” Nowhere is this more evident than in today’s IT landscape. CIOs across the globe are grappling with a new, unexpected wave in their voyage – inflation. What makes this wave particularly unsettling is that it’s blowing up the cost of all IT services without offering additional value. This paradigm shift has put cost-efficiency on every IT leader’s radar.

However, a leaner IT function doesn’t necessarily equate to a downgrade. It means that IT must now be savvy – not just technologically, but also financially. This requires a strategic reevaluation and a sharper toolkit. With this in mind, let’s dive into a robust discussion on navigating the cost tide as it stands to meet the needs of the current business environment.

Acknowledging the Storm: Current Economic Climate

Globaly business revenue is set to decline due to macroeconomic factors and constricted consumer spending. IT budgets, which are often proportional to business revenue, will undoubtedly feel the pinch. The pressure will be on IT departments to ensure every dollar is spent wisely.

Meanwhile, staffing and labor shortages for IT talent have escalated due to the digital skills gap, an evolving job market and pandemic-related disruptions. This has further complicated the IT budgeting equation, causing CIOs to rethink their talent strategy.

On the supply front, IT hardware, often sourced globally, has been affected by supply chain difficulties. The resultant unpredictability in both cost and availability requires us to reframe our IT sourcing and inventory strategy.

These challenges are multi-faceted, but they’re not insurmountable. The need of the hour is to act decisively, recalibrating our approach to ensure cost-efficiency and value delivery.

Taking the Helm: Practical Steps for CIOs

The current inflation-driven wave can’t be ridden out by simply releasing water. Instead, it requires us to take decisive actions and steer the ship in a new direction. Below are some of the key steps that CIOs and IT managers can consider.

Committing to Clear Technical Debt

In the world of IT, technical debt can accumulate much like financial debt in the real world. It is the cost that companies pay for short-term technological fixes that, over time, require an increasing amount of work just to keep the systems running. When unaddressed, it can lead to increased costs, inefficiencies and ultimately reduced agility and innovation.

Today, more than ever, we need to start chipping away at these debts. In this challenging economic environment, the cost of servicing this debt becomes even more burdensome. Paying down technical debt isn’t an easy task – it requires a well-thought-out plan, which might involve revising outdated code, rearchitecting inefficient systems, or even investing in new technologies. However, the benefit lies in streamlined processes, reduced costs and increased operational efficiency, all crucial in the inflation-impacted business climate.

Right-Sizing Staffing: A Delicate Dance

In an inflation-driven world, staffing becomes a high-wire act. The goal here isn’t merely about finding the balance between overstaffing and understaffing, but about making strategic decisions on how to most efficiently deploy human resources.

Firstly, consider which skills are most needed for your department’s strategic initiatives and day-to-day operations. Are these skills available in-house, or do you need to recruit? Then, evaluate the cost-benefit of full-time employees, contract workers, outsourced teams, and automation solutions. Implementing automation for repetitive tasks, for example, can not only cut costs but also free up your talented IT professionals to focus on more value-added activities.

The labor shortages in the IT industry only amplify the need for a thoughtful and strategic approach to staffing. By right-sizing your team, you can maximize output while keeping costs under control.

For more on this, please see the earlier blog post, Winning The War For Talent With IT Service Cost Management.

Adopting a Mature IT Budgeting Approach

Now more than ever, a mature and nimble IT budgeting process is crucial. Traditionally, IT budgets have been a once-a-year event, often rigid and slow to respond to changing business needs. However, the current economic climate calls for a more agile approach.

Incorporate frequent budget reviews, allowing adjustments in response to changing business conditions and IT demands. Cultivate transparency and communication about the budget within your team and across departments. Moreover, every line item on the budget should clearly tie back to the value it delivers. This means moving beyond the cost-center mindset and communicating IT’s contribution to business goals.

Regular Benchmarking: Keeping a Finger on the Pulse

Regular benchmarking of your IT costs against industry standards is a critical part of maintaining cost efficiency. It allows you to identify areas where costs may have inflated beyond the norm and provides a basis for understanding whether your spending aligns with the value you’re providing.

A good sailor knows the importance of regular checks on the ship’s position. In the world of IT, this is similar to benchmarking. Regular benchmarking of your IT costs against industry standards can serve as a navigational beacon, helping you chart the course towards cost efficiency and maximum value delivery.

At its core, benchmarking is a method of comparing your costs, processes and performance metrics to those of other businesses, for example the industry leaders or direct competitors. But it’s not just about numbers. It’s about understanding what the best practices are, what strategies are yielding results and how you can adapt these insights to your own organization’s context.

The fast-paced and dynamic nature of the IT sector makes regular benchmarking a necessity. It’s not enough to benchmark once and then forget about it. IT costs, influenced by factors such as new technological developments, market competition and regulatory changes, can fluctuate. Regular benchmarking ensures you’re  steering your ship by current coordinates.

While cost is a significant element in benchmarking, it’s essential to remember that it’s not only about finding the cheapest way to do things. The ultimate goal is to maximize the value your IT department delivers. This means benchmarking should also cover aspects like service quality, process efficiency and innovation capability. This comprehensive approach provides a fuller picture, guiding the effective allocation of resources.

Benchmarking in Practice

Benchmarking can take different forms, each offering unique insights. Cost benchmarking allows you to identify the cost level of your IT department. Price benchmarking helps you understand how competitive and healthy your key contracts are. Functional benchmarking compares your operations with those of industry leaders, even from different sectors.

Moreover, strategic benchmarking allows you to examine how other organizations achieve their business success. It’s about analyzing the big-picture strategies and the long-term vision. Given the integral role IT plays in business success, strategic benchmarking can offer invaluable insights.

Embracing benchmarking requires a certain mindset. It’s about acknowledging that there are lessons to be learned from others, about being open to change and about striving for continuous improvement. Developing this mindset within your team and promoting a culture of learning can truly harness the power of benchmarking.

In conclusion, benchmarking, when done regularly and comprehensively, provides a realistic and fact-based perspective on your IT costs and performance. It’s an essential tool in your arsenal to navigate the inflation-induced wave, keeping your IT department not just afloat, but sailing smoothly towards its destination.

Navigating the Waters Ahead

These strategies are not just about surviving the wave of inflation. They are about adapting to new realities, steering the ship in a new direction and ultimately coming out stronger on the other side. Yes, cost-efficiency is critical, but let’s not forget the value that IT brings to the table. The role of IT leaders now is not only to control the costs but also to emphasize and enhance this value. Embrace the challenge and navigate the seas of change with confidence and foresight.

Interested to learn how the cost efficiencies of your internal technology services stack up against peer organizations? Visit our website for more information on our IT benchmarking service, IT Service Cost Management.

Over the past few years, a growing number of organizations around the world have made bold pledges – and set specific targets – to achieve environmental and social sustainability goals. However, many organizations continue to struggle to make progress toward achieving these goals. This is often due to a lack of a clear technology strategy that is aligned with corporate sustainability missions.

For most organizations, strategies for achieving these goals are typically driven by the Board of Director and/or C-suite. The challenge with this approach is:

Effectively communicating the importance of sustainability to the business
How the strategy will be executed
What role team and individuals must play in helping achieve goals

This is particularly true in IT, where lack of communication and guidance from executive management on the role IT, and IT technologies, can slow progress. While there are a variety of personas and functional leads who are responsible for contributing to corporate sustainability goals, IT must work cross-functionally to support its own objectives, while supporting the technology needs of departmental and corporate leads. When it comes to supporting corporate sustainability initiatives, IT has two primary responsibilities:

Reducing the sustainability impact of its own IT infrastructure
Leveraging technology solutions that allow the organization to visualize and improve performance

Sustainable IT Infrastructure

For many organizations, IT accounts for a sizable portion of an organization’s overall carbon emissions. For companies that have made aggressive commitments to reducing greenhouse gas emissions, IT will be an obvious area of priority.

Over the past few years, digital transformation has been a recurring theme in IT as organizations increasingly rely on digital technologies to run their business. As organizations move beyond digital transformation initiatives and look for growth built on digital-first strategies, they will need to focus on purposeful long-term goals like sustainability.

More organizations are starting to view their IT strategy through the lens of sustainability. We are seeing an increasing number of request for proposals (RFPs) with specific sustainability requirements for areas such as energy efficiency and carbon emissions. Companies are also looking at the full lifecycle of their IT assets and embedding sustainability data into asset lifecycle management. This allows leadership to make informed decisions about asset utilization, asset maintenance and repair, and end-of-life/reuse/recycle.

For their part, IT vendors recognize the importance that customers are placing on sustainability and are incorporating it into their solutions portfolios. Across the IT landscape, IT vendors are developing more energy efficient infrastructure and designing and manufacturing equipment for recycle/reuse. Cloud service providers, meanwhile, are increasing their use of renewable energy sources, while data center operators are driving energy efficiency through better resource utilization and cooling solutions.

Driving Improvement Through IT Sustainability Solutions

IT will also play an important role in supporting corporate sustainability missions by leveraging existing technologies and investing in new solutions that can help organizations track, report, manage, and improve sustainability performance.

Gaining access to the data needed to effectively manage sustainability performance is essential for establishing performance baselines and devising strategies for achieving future goals and targets. However, this can be challenging as sustainability data typically resides in different repositories, These repositories can be scattered throughout the organization and fall under the control of different functional leads.

Without visibility into sustainability data, the ability to effectively report on milestones and metrics for compliance purposes and meet established goals is compromised. IT needs to aggregate internal data and provide platforms for sharing data across the organization.

In the software area alone, there has been an explosion of sustainability solutions that give organizations greater visibility and awareness of performance.

IDC’s ESG Perception Survey revealed that most organizations are using multiple tools to manage sustainability, with nearly three-quarters of survey respondents citing data and performance management as the key features they are using.

IDC expects to see increased spending in software solutions for sustainability performance management as organizations look for greater observability of their impact across the organization, as well as the partner/supplier ecosystem.

It should be noted that greater awareness of an organization’s sustainability footprint has led forward-looking organizations to use sustainability as a lever for driving innovations in areas such as supply chain, distribution/shipping, and manufacturing processes. IDC believes that the shift from compliance-driven to business value-driven sustainability initiatives is taking place. Technology will play an even greater role in helping organizations identify the opportunities for leveraging sustainability to drive business innovation.

Conclusion

Technology will play a critically important role in helping organizations meet their sustainability targets and goals. Developing an IT strategy that aligns with corporate sustainability strategy is critical to identifying these technologies. New technologies will be needed to track performance, report progress to internal and external stakeholder, meet compliance and regulatory demands, and integrate sustainability data into existing business operations. Ultimately, greater visibility will allow organizations to expand from compliance-driven strategies to strategies that are focused on leveraging sustainability to drive business value.

For more insight and information on trends and market dynamics driving technology purchases for sustainability, please see the IDC eBook entitled “Driving Business Value Through Sustainable Transformation“.