My last blog post, focused on how AI is changing faster than businesses (and the world) can adapt. This blog post focuses on how we got here. Specifically, why do large companies struggle to innovate quickly. One reason is that companies were build to be sustainable vs. adaptable. The speed of innovation is forcing organizations to react more quickly than ever in history. By looking back at the past and understanding how we got here, we hope to lay the foundation for a path forward.
Several key players make and influence key buying decisions. Key players include software companies, Venture Capital firms (who fund new innovative software companies), the enterprise companies who buy the software, and the consultants (or System Integrators) who influence strategy and buying decisions. A key point before we go deeper – this is not about bad actors. Ironically, the reason we are where we are is because each of these constituents are very good at achieving their business goals. The interplay of each of these key players helps explain why large companies struggle to innovate faster. Let’s look at the players below.
The Software Industry
As the software industry has matured, software companies have developed good sales techniques to maximize Total Contract Value (TCV). Going back in time, in 1990-2000, we had the Internet bubble. We also saw the rise of ERP. From 2000-2010, we saw massive consumer innovation including mobile, and social apps. From 2010-2020, key evolutions in technology included mobile apps, cloud, AI, Open source, and more of a focus on agile development. Through this all, software companies developed masterful techniques to optimize software revenue.
To recognize revenue, software companies need a commitment to buy. Software companies primarily look for either an annual commitment (ARR) or a longer commitment (total contract value or TCV). Most software companies put a premium on multi-year deals. Some software companies offer subscription models, but they are the minority, and they are generally not selling very large deals. Software companies continue to look for a commitment to recognize revenue for at least one year (ARR), and ideally more than one year. A large reason, which has become more important recently is pressure from VC firms.
Venture Capital Influence
Let’s start with the changes of last three years. The number of software companies has grown dramatically over the past three years. According to CBInsights, we now have 1205 pre-IPO unicorns (pre-IPO firms valued at over $1B). And from 2020-2022 we had six quarters in a row where we added over 80 new tech unicorns. The reason this is important is because, based on the success in the past including ServiceNow, Snowflake, and recently UiPath, sales teams were built to optimize selling capacity and win TCV.
VC-backed Unicorn sales teams are very proficient at selling maximum capacity thereby driving maximum revenue. Put another way, the most “successful” software companies are very good at getting enterprise companies to agree to commit to pay them piles of money for software they may, or may not use. While the number of unicorns dropped recently, the fact remains: there are a lot of software companies selling a lot of software. VC firms drive sales teams to focus more on selling software, and less on delivering value.
Consultants and System Integrators
The formula for profit for consultants and SI’s is to drive utilization. These firms hire thousands (or tens of thousands) of people and bill them at a rate above their salary. For the sake of simplicity, let’s assume the break-even number for a firm is 65% utilization. If the total utilization is greater than 65%, the firm makes money. The consulting model encourages maximal billable hours (same model as law firms and accounting firms). These deals consume the most billable hours. The rainmakers (Partners) sell big ideas to the top of the enterprise hierarchy for a lot of money.
Consulting firms solve problems by using the people and skills that they have in house, or on the bench. In other words, in almost all consulting firms, you find highly skilled people with specific software skills including SAP, AWS cloud, Azure, ServiceNow, etc.…. The consulting model rewards big, long, repeatable projects. Generally, consulting firms and SI’s are not at the forefront of innovation; rather they optimize on solving big problems that are repeatable. If a firm can do the same $20M project across 10 customers, this is a big win. This leads to a GTM approach to repeat what works, which leads to a focus on solving a general problem instead of solving for a unique business problem.
A focus on big, slow top down programs
The consulting firms influence businesses to buy large projects. When they sell a large project, they focus on their unique approach or insights, and often the technology is secondary. Many believe consulting firms reduce risk and provide a shield to the purchasing executive. (If the project fails, the consulting company will be blamed). The technology deployed is often a dependent on the skills the consulting company has in house. The enterprise buying company does not buy the best technology. Instead, the enterprise buys a low-risk solution or a long-term vision to solve for a business problem. The problem will take a long time and a lot of money to solve. For the enterprise, focusing on big problems means the company is not paying attention to new technologies. This also means the company is solving for problems with a top down mindset. Both are reasons why large companies struggle to innovate faster.
What happens in the Enterprise?
First, let’s look at how the enterprise has reacted to software. Over the past decades, most enterprise companies have purchased too much software. Some of this software is redundant, and some becomes shelf ware. To combat this, large companies created processes to protect themselves, and avoid wasting money. Meanwhile, the number of software companies, cloud providers, and open-source options has grown. Fueled by VC capital, the AI-based alternatives have created a big uptick in requests for new vendors in enterprise companies. In response, more enterprise companies have added more controls. I.T. and procurement are tasked with adhering to these controls. For many companies, it takes 12 months and cost ~ $1M to go through the process of buying software from a new vendor. To protect themselves from an onslaught of new vendors, the enterprise has created more rigorous processes. These processes make it difficult to introduce innovative technologies.
Now, let’s look at the impact of consultants and SI’s on the enterprise. Because consultants and SI’s are looking to solve large problems, they promote the idea that a single application or platform should be used across the enterprise. Two decades ago, it was SAP, a decade ago it was Salesforce, now it’s ServiceNow. Implementing these large systems or programs is time consuming, cumbersome, and complex. These programs require a lot of focus from the enterprise , and a lot of manual labor (billable hours) from the consultants. The programs are not optimized to be the most innovative. The programs are not fast.
Friction for the business
Faced with new competitors and rapidly shifting market dynamics, the business side of the enterprise is looking for faster results. More and more, innovation is being driven by the business, and often by tech-savvy business users. The goal is to use innovation quickly to improve a business outcome. However, to buy a new solution, the innovative business leader has to fight the gravity of the software buying process, and the headwind of consultants and SI’s. This is a long arduous battle, usually supported by a change agent. This battle can take years, and require building a broad coalition for change.
One More Hurdle
Even when the change agent starts to gain traction for a new innovation, there is one more important impediment to rapid innovation. The final hurdle of innovation is “build vs. buy”. I.T. is almost always part of a buying decision, and they play an important role. However, for various reasons, sometimes I.T. makes a recommendation to build vs. buy. Often the internal I.T organization feels “out of position” with respect to new, innovative technology, and they choose “build” as a way to get educated. For example, let’s consider a data science project to improve customer engagement. I.T. may recommend doing the work in house, justifying the decision based on a risk factor such as external vendor immaturity, or data risk. In some cases, the justification is valid. However, often a build vs. buy often slows innovation.
Summary
In summary, the industry is at a point where most enterprises are not adapting new AI-based technology fast enough. In response to more software companies, and good selling tactics, enterprise buying processes have become more stringent. These processes helps protect the business but elongate the buying cycle. Consulting companies and SI’s sell large repeatable top-down programs that often take a long time to deliver value, and consume massive resources. This creates additional friction for businesses looking to move quickly. Finally, internal I.T. teams often look to build vs. buy, further slowing the businesses ability to innovate quickly. While AI-led innovation is accelerating, current market conditions are misaligned.
