As systems grow and change, subjective and biased decisions can lead to chaos and confusion, negatively impacting organizations.
By developing an automated operational decision system that relies on objective data, your organization can become more informed, efficient, and profitable.
What is automated operations management?
At its base level, automated operations are day-to-day execution decisions becoming more automated and data-driven in their design. It is based on the principles of systems engineering and neural networks.
What are the benefits?
Removing the silos between teams — Various teams can be too disparate in the strategies they employ. These different methodologies lead to inefficiencies and conflicting work that impact the organization's overall success.
Removes subjective bias — Sometimes, problems become too complex and multidimensional for our instincts. Automated operations can provide helpful context and make recommendations based on the data.
Consistency over time — An organization is comprised of people who come and go, but the company’s goals continue. An individual solely responsible for the reasoning behind a specific strategy becomes the nexus for that strategy; their reasoning may become confused when a new person takes over. However, if that strategy is based on specific metrics connected to the entire organization's work, it becomes less disruptive when people shift through positions.
How would automated operations work?
Automated operations would function like a tool that suggests optimal strategies for the team and the organization as a whole. These recommendations would be based on specific systems designed for the company that keep in mind organizational goals, company structure, and team scopes to help design strategies. It will also allow you to understand better the effects making one decision may have on other teams.
What does it look like in action?
If a Saas organization wants to increase the number of contracted clients by 10% at the end of the next year, which teams need to do what? How do their different strategies work with each other? How many more leads do the lead gen team need to acquire, what is the increase in sales that needs to occur, and what is the maximum churn the customer success team can allow?
Normally, an organization would supply goals to each team: the lead gen team must acquire X leads a quarter, the sales team must close Y% of those leads, and the customer success team must retain Z% of all clients. Although this is a start, it inherently leads to inefficient teamwork.
Instead of making the goal for lead gen X leads, the goal could be broken down by lead type. What clients tend to retain better? What clients do sales have an easier time closing deals on?
What you see above is a mess of questions that may feel impossible to answer when all together, but that is exactly what we will do. Instead of finding answers to all of the questions individually, we begin to search for answers to all of the questions that, when put together, give us the company-wide goal. Find questions that, when answered, positively affect all teams.
We can also optimize within each team itself. Where are sales not optimally utilizing all the leads? Perhaps they are closing high-quality leads very well, but even low-quality leads, when you gather enough of them, should produce some number of signed deals.
What is this blog about?
Now, we finally get to the purpose of Automated Operations Management. At the end of the day, few organizations will be willing, let alone able, to invest the necessary resources needed to fully develop the systems that could lead to truly automated and informed organization-wide decisions. Instead, we will focus on the individual “neurons” that comprise that system. Individual changes teams can make to not only improve their own internal systems but that, when placed together, will perform better than the sum of their parts.
Our articles will focus on individual concepts, with theoretical use cases, to show where adding simple algorithmic methodologies can improve their current systems with the hope that as an organization implements more concepts, they will slowly connect the individual pieces to develop advanced, agile systems that can fundamentally alter how an organization makes its decisions.