Today’s businesses are more dependent on software than ever before. However, many entrepreneurs are wondering whether it is a wise decision. While computers are yielding better and more efficient outputs for companies, there’s still a trust issue. Doesn’t human instinct play a role?
Fortunately, this post has some answers. It looks at the situations when you should rely on software, when you should use instinct, and when a combination of both is likely to serve you best.
When To Rely On Business Software
Here are some situations where it absolutely makes sense to rely on business software (and you should never do anything else).
Real-Time Monitoring
First and foremost, software makes sense when real-time monitoring is critical. Machines can crunch data signals faster than human operators and send you notifications and alerts if you encounter issues.
Of course, such systems aren’t perfect. Sometimes they alert you when they shouldn’t, or fail to alert you when they should. But by and large, they do the job well.
For example, software is ideal when you want to monitor customer feedback and key performance indicators. It’s also useful for checking on IT network health (i.e. detecting unwanted intruders).
Furthermore, all this action gives you peace of mind. You know if something is about to go wrong, you have the jump on it.
Efficiency And Accuracy
Software also comes in handy when you want to be efficient and accurate. (Nothing beats computers on this front!)
For this reason, you often see disposal companies using waste management software. They could still operate beforehand, but they made mistakes. Relying on computers reduces errors and helps them do business better.
The same is true of facilities managers. They don’t have to use software, but most do because the benefits are immediate and obvious.
Complex Calculations
Given the rise of AI, there’s also an argument to be made that software can improve complex calculations. Machines can evaluate data in ways that traditional statistical techniques can’t.
Part of this has to do with the algorithms they use. Statistics require assumptions to work, but approaches like random forests aren’t so reliant on these. Instead, computers and software can use brute-force approaches to extract valuable information from datasets without the risk of spurious results.
This might all sound quite academic, but the applications of complex calculations in business are extensive. For example, companies often require multi-input models for things like budgeting, route planning, and process optimization. (You’d be surprised how much it comes up).
Making Data-Driven Decisions
Finally, software is useful for companies wanting to make more data-driven decisions. It helps them come to better conclusions about what to do next or how to approach specific problems.
Again, it’s not a foolproof method. But it can make decisions more objective and help with long-term planning. It also allows firms to say that they made their choices based on the best available evidence instead of listening to instinct or hearsay.
What’s more, many data-driven tools are responsive to new data. If something changes in the underlying information, the recommendations they offer also change, without any human emotions involved.
When To Use Instinct
At the same time, it is valuable to ask when to use instinct. After all, the world isn’t a machine.
Strategic Vision
One area where using instinct makes sense is in strategic vision. Software isn’t very good at coming up with brand-new concepts and ideas, whereas people with years of experience are.
For example, you might use your instinct to decide on a direction for the firm based on your observations of what your customers will like. You could, for instance, focus on a new line of products that fit in with an emerging trend you think will take off in the future to get ahead of the market. Or you could fire someone because you have a bad feeling about them.
These small decisions to do with developing your products and thinking creatively can have a vast effect on your success later on. Machines don’t always understand the wider context, so when they try to offer strategic vision or clever insights, they don’t always work.
As such, a lot of software is a means to an end. It’s something that allows you to deliver on your objectives instead of setting them for you.
Customer Interactions
These days, you can get software to interact with customers for you, but it’s a bad idea in general. Despite the advances in AI, most people want to know they are communicating with a real soul, not just random electrons in computer circuits.
Therefore, it’s usually better to rely on instinct when interacting with people (especially if you run an offline business). Getting to know them helps to create rapport and can forge a closer connection with your brand. It can also build loyalty in a way that even the best machines can’t.
Focus on using more human interactions in sales and customer service. Give people someone competent on the other end of the line, not a piece of software that has to operate within a straightjacket.
Ethical Considerations
Sometimes, you might also want to rely on instinct for ethical reasons. Yes, you could get a machine to perform tasks, but you know you shouldn’t.
These cases usually show up in jobs where you need to make value judgments. Sure, a machine could weigh up the pros and cons, but often that responsibility is better left to workers.
You may sometimes benefit from human judgment and values in other ways. For example, software might make decisions that make sense in one context, but not another.
Dealing With Uncertainty
Lastly, it often makes sense to use people when dealing with uncertainty. Machines will usually revert to what the data says, but people will think ahead and ask whether a solution is best overall.
Unfortunately, information is often incomplete in business. Machines may understand the underlying data, but they don’t know what specific actors might do, preventing them from making accurate predictions.
How To Combine Software And Instinct
Of course, the best business leaders combine software with instinct. They know that the two are complementary and you can’t have one without the other.
One clever option is to validate your instincts with data. Here, you come up with a hypothesis and wait to see if it plays out in reality. Sometimes it will, but sometimes it won’t. Then, you can use this information to decide if you want to go ahead or not.
Say, for example, you have a gut feeling about a new product but you aren’t sure whether it’s going to work out in practice. In these situations, you could use market analysis software to test your ideas and get a better sense of the possible opportunity size.
Another option is to set up some sort of feedback loop. Here, you make a decision based on instinct and then use data to evaluate it. For example, you might start a new marketing campaign using PPC but then realize that using influencers is the best option.
Ultimately, most companies wind up developing a balanced approach. Humans help machines in some ways, while the machines help workers in others.
Once you have a system set up, working with software becomes more enjoyable. You understand its capabilities and limits, letting you use it more effectively.
AI is advancing and getting better and making recommendations. But it still didn’t understand human structures and how they work. For this reason, a combination of the two approaches is probably still best for companies. We still don’t have bona fide AI CEOs.
