Trust the Power of the Robots - When Tech Beats Human Analysis

For all the jokes about our robot overlords, the age of Artificial Intelligence (AI) is upon us and looks little like the movies. Turns out, our relationship with robots has a lot more to do with data and business processes than great wars between humans and machines. But while the tech now exists to make the lives of employees around the world easier, not all businesses have been quick to adopt tools to help automate manual tasks for greater efficiency.

Sometimes it’s due to concerns about cost. But at this point, the technology’s become much more affordable, and when you factor in the time it can save, the costs start looking a lot smaller. Other times, it’s due to the allure of the way things work now—embracing change takes time and work, and oftentimes businesses find maintaining the status quo more comfortable than branching into a better way of doing things. Yet that kind of thinking is dangerous for any business that wants to stay competitive.

But at least some of the time, the issue is that nagging sense that, surely, machines can’t be trusted to do a job as well as humans. Technology lacks the lived experiences we bring to work, the ability to understand the emotions behind decision making, and the creative thinking that drives the “aha” moments that play such an important role in business. But when you refuse to trust AI, you lose out on some of its most powerful and valuable uses.

 

5 Tasks to Trust Tech to Perform

Certainly there are tasks you shouldn’t trust AI with—leaving a newborn baby in the care of a piece of software wouldn’t make a whole lot of a sense. But the tasks that technology excels at, it does better than humans can. For these types of jobs, you’re better off handing the reins to AI-driven software than hiring a human to tackle them.

 

1. Data collection

Data is powerful. A business based on data-driven decision making removes a lot of guesswork that makes running a business risky. But for data to be valuable, you have to have enough of it to properly analyze trends and patterns. If you’re working from too small of a sample size, you could fail to see the big picture and may draw the wrong conclusions.

But without tech, collecting enough data to gain valuable information is time consuming, tedious, and prone to error. Plus, in the fast-moving world we live in, the slow process of collecting and organizing data manually means much of what you have will be out of date before you get far into the process.

By contrast, tech can automate data collection. Smart software can monitor thousands of sources within moments, pull the most important bits of information from each one of them, and serve up the data you need nearly in real time. Forcing the tedious task of data collection onto humans in your business simply makes no sense when data can do a faster, better, and more trustworthy job of it.

 

2. Sifting through data

Once businesses realized how easy technology makes data collection, many went all in on it. For years, big data has been a trending topic in businesses of all sizes. But the quantity of data collection possible using technology presents its own problem. You need a lot of data to gain a useful sample size, but you can quickly reach a point of data overload where you have too much to effectively process.

Drowning in so much data that you can’t wrap your head around the information in front of you is almost as bad as not having any to start with. But this is another uniquely human problem. A person facing down a spreadsheet with thousands of data points will be at a loss to make sense of it, but a software with AI functionality can much more easily sift through and organize the information into logical categories to find the bits most important to a company’s business goals.

 

3. Data analysis

Those first two categories probably didn’t feel too controversial. It feels intuitive enough that technology would be more adept at collecting massive amounts of data and organizing it more efficiently than a person would. But analysis? That requires the kind of thinking only a human brain can do, right?

While a human will always play some role in the process of making sense of the data you have, a solid software product can actually do a lot of the preliminary work for you. A business that notices a steep drop in new sales may struggle to understand the reason behind it. But a smart piece of software that monitors many channels at once may be able to spot a correlation between when sales dropped and mentions of a competitor’s new product on social media. And as more data is collected, an AI engine with a properly configured model will continually learn what is strategically relevant and what is simply market “noise,” making the insights analyzed much more and more effective over time.

Having a faster way to identify notable trends that affect your business allows your team the space to react and adapt in the moments when it matters most.

 

4. Data visualization

A lot of numbers packed into a spreadsheet could potentially contain important insights. But most people won’t be able to look at it and make much sense of what they’re seeing. When tech can help you put that information into a visual format, it makes it much easier for your team to absorb.

Technology is generally better than humans at taking data and seamlessly turning it into accurate charts and graphs that help people better understand what they’re looking at. In order to take the information you have and turn it into actionable insights that will inform your strategy, data visualization is a useful step in the process, and one that you’re best off leaving to the machines.

 

5. Information distribution

The first four tasks are all about collecting and understanding information, but too many businesses complete that first part of the process and fail to put what they’ve learned to use. A final step that technology can help you with is making sure that the insights you learn can be distributed throughout your organization to everyone that needs the information. The marketing adage about getting “the right content, to the right audience, at the right time, in the right format” is more true today than ever before, and it is critical to do it in an efficient and easy manner for your teams to adopt it.

Manually handing out pieces of paper with information on it may have worked a couple decades ago. And more recently, sending information to each person via email has been the most common method of disseminating information. But that takes time, and with inboxes overwhelmed, it’s no longer the best way to actually get information in front of a person. A good tech solution can now help you create a centralized platform that everyone in your organization can access to find the most up-to-date information they need, when they need it, to do their jobs effectively.

 

How AI Can Help with Competitive Analysis

Each of these tasks can be applied in a number of different business realms. But one crucial area where AI can help you improve your business strategy is competitive analysis.

Tracking who your competitors are, the meaningful updates they make to their messaging and product strategy and what they’re doing across a number of channels would be a ton of work to manage manually. Your team can’t reasonably stay on top of it all without help. And if you try to solve that problem by hiring it out to someone outside of your business, they won’t know how to see the data in front of them with the level of knowledge your own team can.

The best way to make sure you have all the competitive insights you need to run your business effectively in real time is to trust the technology. Find a competitive analysis product that takes care of all the stuff AI is best at for you, so your team is left to take the insights the tech reveals and run with them to win in your market.

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