What Business School Teaches Us About IT Projects

So what did I learn in my business classes about IT projects anyway? A lot actually.

In his famous paper, IT Doesn’t Matter, Nicholas Carr eloquently opens with a description of his major point regarding IT technologies.

“Their very power and presence have begun to transform them from potentially strategic resources into commodity factors of production.” (2003)

I would tend to agree, and this principle is applied in varying degrees to different types of IT projects. Some IT setups provide more competitive advantage than others, but all essential infrastructural technologies become available as utilities. One of Carr’s major points is that any competitive advantage brought upon by IT breakthroughs will be short lived, because key advantages will be quickly adopted by the industry at large. For this reason it's not a bad idea to hold out when planning large IT projects, given the complexity, cost, and dire consequences of failure. However at a certain point, the lack of IT infrastructure in a company will be detrimental and expensive to correct.

Numerous case studies point to the importance of in house expertise and upper management buy-in for large IT projects. Look no further than Robert Muller's infamous failure at upgrading the FBI's IT system during his time as director. Business school tells us that upper management needs to be serious about hiring adequate expertise in house, make crucial decisions that affect workflows, and dedicate as much resources as it takes to make the project happen effectively. Given the simple fact that almost every single process in a modern firm relies on IT functionality, this makes sense why so much diligence is required on behalf of highest levels in management.

Infrastructural vs Proprietary Technology

Carr goes on in hi paper to point out the difference between infrastructural and proprietary

technologies. Since IT generally falls more into the infrastructure category, usage will

explode. However, the companies that are coming up with the major innovations, like currently in

AI and automation, will likely be able to capitalize on proprietary tech while IP holds or until someone else finds a better way.

Carr uses railroad analogy is powerful here as a demonstration of massive infrastructural change that started slow, and eventually transformed entire industries operated. This technology ultimately made mass production for consumers around the country feasible and lead to industry consolidation and domination. This is a pattern that we should continue to expect to see as new infrastructural technologies become available.

Tech companies are still going to pushing infrastructural technologies to the edge,

although most will not. However, those who continue to capitalize on this innovation will

need to remain innovative to stay alive as the industry adjusts to their breakthroughs.

An example that is modern (and classic) that I divert to for illustrating this is Netflix, who has done this multiple times since they innovated the movie rental industry. After seemingly serendipitous innovation upon the next big way to consume media, membership based streaming. Even by the time video rental industry had been forever changed, streaming was just a side feature available for select titles in the Netflix app.

Now Netflix is a full blown video streaming company, but the innovation wasn't able to stop there. Netflix most recently has innovating their model by making major investments in production of their own media content to stream. As competition is closing in on stream their own content, Netflix has found a way to secure their own competitive advantage that way. It’s interesting that in this shift towards creating content, Netflix is gaining their advantage through proprietary tech, rather than infrastructural techs that they pioneered on the path to success. This newfound advantage is much more sustainable if we agree with Nicholas Carr.

Following this logic, we can expect that this same pattern of forced continuous innovation is going to be true for a lot of infrastructural innovators out three, like AI and automation companies. Should this principle drive companies away from investing in these technologies given the fleeting nature of the competitive advantage that comes with the territory? Elon Musk sure doesn't seem to think so.

Artificial Intelligence companies race now to develop technologies that will readily be replicated and expanded upon by the entire industry, so it’s safe to assume that a before too long a variety commercial products will be readily available to businesses to support a wide array of highly intelligent data processing. The innovators will continue to innovate if they want to remain relevant.

OK tech innovation happens quickly, but is it really smart to delay crucial IT upgrades?

Sure, delaying IT upgrades can be smart given the rapid rate of technology evolution. Since experts in tech companies are figuring it out, why should smaller players invest? We commonly see large companies taking the strategy in slow adoption of new infrastructural technologies. In fact for a lot of infrastructural IT, because this hesitance to upgrade is proven to be wise time and time again. Developing and managing IT projects requires adequate expertise and management support in house, otherwise they can quickly become expensive and problematic.

But look back at the quote above from Carr; he is also telling us that as these technologies shift from a means of strategic advantage for the innovator to a widely available utility industry wide, the concept of competitive advantage changes. Companies who lack the IT infrastructure tools that are widely available are at a competitive disadvantage compared to all rival firms that probably do utilize the best available infrastructure tech.

Rather than hiring on large numbers of IT developers and experienced project managers, it's not uncommon for large companies to run slimmer, and outsource their IT needs using off the shelf solutions that are commercially available. This is certainly the case in the biotechnology industry where I work. There are tons of options for infrastructural software platforms that labs need to function. So service contracts can be maintained with vendors to keep things functional. This has clear advantages and disadvantages. If you are going to outsource something, it's done most effectively when you have the expertise in house to understand and guide the process.

Even for large companies that don't want to specialize is developing and maintaining software systems, outsourcing is the smart call. Infrastructural software products may be developed by teams of engineers, but that doesn't always mean that the industry specific usage potential has been thoroughly vetted out. It's still possible to develop systems that provide a competitive advantage by developing workflow solutions from using commercially available products. However, we can still expect those advantages to be short-lived unless that innovation is a primary focus.

How does any of this apply to lab automation?

In the lab automation world everything discussed above is totally applicable. More and more labs are catching on to the technology, and several players are now at a point of being able to match each other's engineering save for proprietary aspects. Labs have more vendor options, and the opportunity cost of not investing in some sort of automated lab technology is quite uncommon because labs generally far less productive without high tech equipment. In other words, the whole industry isn't relying on the that new railroad yet, but it's in progress.

Bigger firms are already seeing the value, so consolidation of brands and business has began to pick up steam in the past several years. Automation companies like Labcyte, who focus on innovating new technology, get acquired by larger companies looking to more widely apply and distribute the tech for a nice profit. The industry is already mid-shift, but many companies are still wisely taking their time to adjust.

Scientists and lab managers must walk that line between investing too quickly into technology that isn't flushed out, and causing themselves harm by lacking crucial technology implemented by the successful competitors. Some labs, like the one that I work for, are not scared to invest in development of novel automation systems, and those who persevere will enjoy a fleeting competitive advantage in their research and development until our competitors catch on. I find solace in the idea that the work that I do will eventually make it's way to the entire industry, hopefully making drugs cheaper and more readily available for people that need them.