Technology Report

Thriving as the Software Cycle Slows

After a period of strong investment, software vendors can reset with a disciplined portfolio strategy.

By Simon Heap, Greg Fiore, Greg Callahan, Dan Levy, and Jay Bhatnagar

First published on Σεπτεμβρίου 25, 2024
min read


At a Glance Growth has slowed in the software market, so software companies must be more deliberate in their product portfolio strategy. Software companies have cut spending on sales and marketing, but spending on product and engineering has been more resilient. Efficiency in product and engineering is critical in order to free up capacity for investment in important products and features. This article is part of Bain's 2024 Technology Report. Explore the report Since 2021, software companies have been on a spending spree. Flush with cash from investors in a low-interest-rate environment and motivated by the rich budgets of their customers, software companies made huge investments in R&D and sales and marketing. They believed their engineering teams could add endless features to their products and enter adjacent markets that their sales teams and product-led growth initiatives could easily sell into. That is, until recently. Over the past year, while tech budgets remain healthy, CIOs are now much more disciplined in how they buy. Purchases are put under a microscope with competitive requests for proposals, and buying processes have lengthened. Companies are reducing the number of seats (or software licenses) based on their actual need and consolidating spending to strategic vendors. Employees find they need to make a business case to IT to justify buying a standalone product instead of one that comes bundled in another package. The one bright spot has been AI, where companies have been willing to spend aggressively. The result has been a deceleration of growth: We saw a 16-percentage-point decline in the median annual revenue growth for a group of about 90 publicly traded software-as-a-service (SaaS) companies over the past two years (see Figure 1). Figure 1 As growth slowed, SaaS companies significantly scaled back spending on sales and marketing Consequently, software companies have tightened their own budgets. Sales and marketing budgets have shrunk from 41% of revenue to 33% of revenue. Despite budget pressure and the promise of generative AI co-pilots for developers, spending on engineering has been much more resilient: Spending on research and development has only declined 3 percentage points as a percentage of revenue (see Figure 2). Figure 2 Spending on research and development has proved more robust CEOs and CFOs often lack visibility on spending. They may not know how much is being spent on innovation and new product development compared to the costs of maintenance for existing products. Often, they can’t see when work is being duplicated, which can add up to a surprisingly large amount of spending. Disciplined portfolio strategy Customers are not likely to return to an era of ambitious investment beyond AI anytime soon, so software companies will need to ensure they’re producing what customers need, make the most of their research and development spend, and rein in operating expenses that may have inflated beyond optimal ranges. Software vendors will need to become more disciplined in deciding what to build and sell, and be clearer about which product strategy they are pursuing. Our benchmarks indicate that companies typically spend about 25% of engineering resources on fixing defects in existing products, 25% on maintenance and technical debt remediation, and 50% on new features and new products. Of course, this ratio should vary based on product maturity. To better allocate resources in pursuit of this optimal mix, leading companies follow a disciplined product portfolio strategy. Set the strategic vision for the business, defining which verticals and customer segments to focus on and with what products and sales motions. This requires a clear view of the size of the addressable market, the customers’ needs, and the product’s competitive edge. When targeting adjacent markets, it’s critical to identify synergies with the core product and the extent to which buying cycles coincide. Develop a business case for each product initiative, clearly articulating the roadmap, resources required, and expected return on investment. Evaluate progress periodically and test product market fit. Coordinate between product, engineering, and go-to-market teams to align on the product strategy and the plan to create value. Take a hard line on end-of-service and end-of-life policies for products that are being deprecated and reinvest those resources in more productive efforts. Efficient R&D Dismantling the silos between product, research and development, sales and marketing, and customer success and support functions can help improve the efficiency of operations. An integrated operating model helps ensure that the right products are built (that is, products that fit well into the market) and are built right (supported by the most efficient architecture, development, and release programs). For example, selling directly to customers allows frontline staff to gather feedback, which can help continuous development of a product according to buyers’ needs. In other cases, vendors will allow customers or customer-facing functions like sales or customer success to vote on the product roadmap. Organizational structure also plays a critical role in improving efficiency. Getting the right ratios of managers to developers and other staff helps maintain the right levels of experience. Outsourcing and offshoring are also key factors in efficiency, although some vendors paid less attention to these during the last boom period. Software organizations can thrive by offshoring work on products in maintenance mode to low-cost geographies while investing more resources in development of new products closer to the center. Valuation rewards The software market is now in a slower growth part of the cycle, although the generative AI “gold rush” is distorting the maturation of underlying products. Productive growth and margin delivery are what matters now to drive valuation. These require a much more careful balance of growth investment and cost management than software companies have exercised in recent years. Product strategy, including AI, and product portfolio spending provide the foundation for achieving this balance. Investing in AI technologies doesn’t preclude careful assessment of the rest of the portfolio. These decisions then set the direction for how to efficiently deploy research and development spending and how to achieve productivity in sales, marketing, and services. Managing overhead costs efficiently helps free up budget dollars for investment in other areas. This is a difficult balancing act, but the leaders who are able to perform it may yet see the valuation rewards of previous highs. Read the Next Chapter How Generative AI Changes the Game in Tech Services Read our 2024 Technology Report Download the PDF Explore the report More from the report Commercializing Innovation Investing in a Shifting Market Scope M&A Sovereign AI Top AI Functions The AI Opportunity Big and Small Computing The AI Chip Shortage The Software Cycle AI in Tech Services Deploying Generative AI Software Development Efficiency Customer Success AI Everywhere

At a Glance

Growth has slowed in the software market, so software companies must be more deliberate in their product portfolio strategy.
Software companies have cut spending on sales and marketing, but spending on product and engineering has been more resilient.
Efficiency in product and engineering is critical in order to free up capacity for investment in important products and features.

Since 2021, software companies have been on a spending spree. Flush with cash from investors in a low-interest-rate environment and motivated by the rich budgets of their customers, software companies made huge investments in R&D and sales and marketing. They believed their engineering teams could add endless features to their products and enter adjacent markets that their sales teams and product-led growth initiatives could easily sell into.

That is, until recently. Over the past year, while tech budgets remain healthy, CIOs are now much more disciplined in how they buy. Purchases are put under a microscope with competitive requests for proposals, and buying processes have lengthened. Companies are reducing the number of seats (or software licenses) based on their actual need and consolidating spending to strategic vendors. Employees find they need to make a business case to IT to justify buying a standalone product instead of one that comes bundled in another package. The one bright spot has been AI, where companies have been willing to spend aggressively. The result has been a deceleration of growth: We saw a 16-percentage-point decline in the median annual revenue growth for a group of about 90 publicly traded software-as-a-service (SaaS) companies over the past two years (see Figure 1).

As growth slowed, SaaS companies significantly scaled back spending on sales and marketing

Consequently, software companies have tightened their own budgets. Sales and marketing budgets have shrunk from 41% of revenue to 33% of revenue. Despite budget pressure and the promise of generative AI co-pilots for developers, spending on engineering has been much more resilient: Spending on research and development has only declined 3 percentage points as a percentage of revenue (see Figure 2).

Spending on research and development has proved more robust

CEOs and CFOs often lack visibility on spending. They may not know how much is being spent on innovation and new product development compared to the costs of maintenance for existing products. Often, they can’t see when work is being duplicated, which can add up to a surprisingly large amount of spending.

Disciplined portfolio strategy

Customers are not likely to return to an era of ambitious investment beyond AI anytime soon, so software companies will need to ensure they’re producing what customers need, make the most of their research and development spend, and rein in operating expenses that may have inflated beyond optimal ranges.

Software vendors will need to become more disciplined in deciding what to build and sell, and be clearer about which product strategy they are pursuing. Our benchmarks indicate that companies typically spend about 25% of engineering resources on fixing defects in existing products, 25% on maintenance and technical debt remediation, and 50% on new features and new products. Of course, this ratio should vary based on product maturity.

To better allocate resources in pursuit of this optimal mix, leading companies follow a disciplined product portfolio strategy.

Set the strategic vision for the business, defining which verticals and customer segments to focus on and with what products and sales motions. This requires a clear view of the size of the addressable market, the customers’ needs, and the product’s competitive edge. When targeting adjacent markets, it’s critical to identify synergies with the core product and the extent to which buying cycles coincide.
Develop a business case for each product initiative, clearly articulating the roadmap, resources required, and expected return on investment.
Evaluate progress periodically and test product market fit.
Coordinate between product, engineering, and go-to-market teams to align on the product strategy and the plan to create value.
Take a hard line on end-of-service and end-of-life policies for products that are being deprecated and reinvest those resources in more productive efforts.

Efficient R&D

Dismantling the silos between product, research and development, sales and marketing, and customer success and support functions can help improve the efficiency of operations. An integrated operating model helps ensure that the right products are built (that is, products that fit well into the market) and are built right (supported by the most efficient architecture, development, and release programs). For example, selling directly to customers allows frontline staff to gather feedback, which can help continuous development of a product according to buyers’ needs. In other cases, vendors will allow customers or customer-facing functions like sales or customer success to vote on the product roadmap.

Organizational structure also plays a critical role in improving efficiency. Getting the right ratios of managers to developers and other staff helps maintain the right levels of experience. Outsourcing and offshoring are also key factors in efficiency, although some vendors paid less attention to these during the last boom period. Software organizations can thrive by offshoring work on products in maintenance mode to low-cost geographies while investing more resources in development of new products closer to the center.

Valuation rewards

The software market is now in a slower growth part of the cycle, although the generative AI “gold rush” is distorting the maturation of underlying products. Productive growth and margin delivery are what matters now to drive valuation. These require a much more careful balance of growth investment and cost management than software companies have exercised in recent years. Product strategy, including AI, and product portfolio spending provide the foundation for achieving this balance. Investing in AI technologies doesn’t preclude careful assessment of the rest of the portfolio.

These decisions then set the direction for how to efficiently deploy research and development spending and how to achieve productivity in sales, marketing, and services. Managing overhead costs efficiently helps free up budget dollars for investment in other areas. This is a difficult balancing act, but the leaders who are able to perform it may yet see the valuation rewards of previous highs.

Read the Next Chapter

How Generative AI Changes the Game in Tech Services