The latest insights from your peers on the latest in Enterprise IT, straight to your inbox.
Thorough analysis can help improve integration, automation and innovation.
By Andrew L. Goldberg, Head of Enterprise Technology Development, AbbVie
My business card says Head of Enterprise Technology Development at AbbVie, a research-based global pharmaceutical company. But I think of myself as the chief architect. My job is to make sure our IT processes are designed to support our business as efficiently and effectively as they can.
With our acquisition of Allergan in 2020, AbbVie significantly increased in size, geography and number of employees. With 47,000 employees globally, streamlining our IT processes was critical and will help bring us closer to developing new medicines and treatments that can help improve people’s lives.
I often think about my sister-in-law, who died of pancreatic cancer in 2014. They call it the silent killer—by the time the cancer is detected, it’s usually past the stages when it’s treatable. But it doesn’t have to stay that way, and my personal experiences fuel my work at AbbVie. The more we can automate our systems to drive cost efficiencies, the more “at-bats” we can get – the more clinical trials we can run, the more medicines we can get out to the market – the better are the odds of finding new treatments that can help people survive terrible diseases like the one that took her.
Although my experience at AbbVie is specific to health care, I’ve learned several lessons throughout my career that are relevant to IT leaders in any industry.
Constant Change, Unchanging Principles
One reason I find my job fascinating is because it constantly changes. The technology improves, the scale of the business grows, and problems that I used to face in certain situations are eliminated. For instance, post-merger integration used to be filled with technical headaches. But now the capacity we have to expand networks in the cloud, for example, makes that easier. Today, the challenge is more business complexity than technical complexity – in our current situation, for example, which of two systems to be used by 47,000 employees does it make more sense to adopt?
On the other hand, even though the technology changes and the business challenges change, some of the analytical approaches stay the same. For example, at the beginning of our integration with Allergan, we took a step back and mapped the business and technical capability of every business unit. We looked at our application architecture and our acquisition’s architecture, considered the applications’ common capabilities, and then noted where they overlap.
This might sound like architectural jargon, but it can actually yield major benefits. Mapping the capabilities lets you see across different business divisions and understand where you do and don’t need more help. When you start comparing the actual capabilities, people start asking, “What are we arguing over, anyway?” Often, it turns out there isn’t really a debate.
Once you can reduce technical issues to their essentials, business leaders are able to make rapid choices. You may still need to make some tough decisions, but a good analysis gives you a way to look at the issues with more perspective.
Mapping for Automation
Every company today is experiencing digital transformation, and automation is usually one important element they are wrestling with. My team addresses our automation program using a methodology similar to the one we use for merger integration.
The first step is to understand the process you are trying to automate. This is crucial because automating a process without taking a close look at it can be dangerous. They say to err is human; to really mess things up requires a computer. If you take a really bad process, and you automate it, you can do really bad things at scale. For any project that involves taking more than just take a few steps out of a process, we often end up reengineering the entire process first.
Of course, this is not always necessary. I tend to think of automation in two different categories: little automation and big automation. Little automation involves removing just a few steps from a process. It doesn’t fundamentally change the process itself, but it eliminates a lot of the heavy lifting and if you do it right, improves accuracy. Often, we can also reuse the algorithms as templates in other processes as well. Big automation, on the other hand, involves redesigning an end-to-end process as a machine-run process, so that the human is only there in the event the process can’t go straight through on its own.
In either case, the goal is less cost-savings than it is scalability. Any time we automate a process, we can grow a little faster. If a CPU hits capacity and needs to be rebooted, for example, I don’t need to wait for a user to report a problem, have a bridge call, then wait 45 minutes for everybody to assemble and declare that we need to go ahead and reboot. Setting the machine to reboot itself enables people to work on tasks that matter more.
But the automated process doesn’t have to be 100 percent effective to be worth pursuing. Reducing workloads by 10 or 20 percent yields savings. At the volume and scale of the business we do, even small wins can be big.
Beyond Winning and Losing
My final lesson critical to a productive working environment is the importance of finding ways to exchange points of view without turning the discussion into a conflict.
Passion is an important driver of employee engagement and motivation. As I mentioned, passion drives my desire to achieve technology efficiencies that can speed the development of life-saving drugs and therapies – ones that might have saved my sister-in-law. But passion can also lead to enormous mistakes. In the heat of a debate, for example, it’s easy for the parties to care more about winning the argument than making the right decision for the enterprise.
The best career advice I ever received was to assume that at the end of the day, no matter what another person is telling you, they have the best intentions, they have an interest in the best outcome. At the same time, they believe passionately in what they know.
When we become very passionate about certain issues, we sometimes lose sight of the fact that there is another human being at the other end of the table. If you walk into every discussion thinking that you are right, it’s not going to go well for you long-term in your career. You need to listen with positive intent.
Assuming positive intent will allow you to set your passion aside when you need to undertake the kind of dispassionate analysis that is required during merger integration or plotting your course in automating parts of the business. That interplay between passion and analysis is what makes someone a true professional – and the world a better place.
To choose between applications during post-merger integration, map their capabilities and compare what they cover.
The most important gains of automation are not cost savings but the ability to grow more quickly.
Maintaining a balance between passionate feeling and dispassionate analysis will make you a more effective professional.