If you watch CNBC’s business sections, you’ll often hear the pundits talking about the “tech sector” and what’s happening to the share price of firms that they classify as tech companies. These include all the usual suspects: Facebook, Microsoft, Cisco, and so on. But what’s interesting is that even companies in the retail space, like Amazon, are also now considered “tech.”
The fact of the matter is that in today’s economy practically every company, when you think about it, is a tech company. Firms are using technology more than ever before and, arguably, are just as digitalized as the Apples and Googles of the world. Technology is pervasive and is finding its way into every industry, not just those that make tech-related products.
Tech Makes Its Way Into Supply Chain Management
An excellent example of the infiltration of technology into the general marketplace is no more apparent than in supply chain management. Practically every company has a supply chain of one description or another. Companies need to arrange the stages of production, delivering parts to their facilities at the right time. It’s a data intensive task.
In the past, all of this was done by hand. A manager would stand with a clipboard checking off items as they arrived at company premises. But in today’s tech-driven world, this process seems hopelessly inefficient. Not only is it slow, but you also have to pay the manager for their time to perform the action. It’s a nightmare.
Artificial intelligence, however, has now developed to the point where companies can harness the power of synthetic brains to manage mundane tasks like managing their supply chain. When you think about it, supply chain management is ideally suited to computers. There’s no need for creative, original, out-of-the-box thinking: just a high information throughput and attention to detail.
The confectionary company Nestle is already using artificial intelligence to a significant degree to predict future supply needs, forecast demand for its 447 factories, and determine whether it’s prone to under or overstocking using data. What Nestle is doing is AI in a sense because it’s taking data from a vast array of sources and then crunching the numbers to come up with plausible predictions.
Comprehensive Customer Profiles
Imagine if you could predict what your customers were going to do before even they knew what they were going to do next. It would allow you to find new sales opportunities and present customers with buying opportunities at the opportune time. It’d be an incredible tool to boost company revenues and beat out the competitions.
The incredible thing is that such technology now exists. Salesforce, the world’s leading CRM makes, is currently implementing data-driven customer profiles to make suggestions to sales reps who they should contact and when. The program, like all machine learning solutions, relies on collecting a bunch of disparate data and then comparing it to the population to make suggestions. It’s kind of like a super advanced version of statistics, helping companies arrive at rational decisions for whom they should target and with which messages.
Automatic Document Creation
We’re still a few years away from the day where an AI will be able to create original prose on a subject of your choice. But that doesn’t mean that machine learning isn’t involved in the document creation process itself. Google’s auto-suggest feature in emails is an excellent example of a first push into using machines to create responses to emails based on the content. But we are entering a world where it’s not just content, but formatting, that is becoming automated.
Imagine if you could create a consistent set of documents in the cloud that your entire team could use to represent your business and that you could change them at any time to update all the records in your folders. That’s precisely what a dynamic template system does. You specify the layout that you want and the respective themes, and AI software will do the rest, creating accessible formats that your team can immediately use, without having to ensure compliance with company presentation standards manually.
Natural Language Processing For Employee Morale
Natural language processing is where machines listen to and understand language as spoken or written by people. It’s how tools like Amazon Alexa or Google Home understand what you’re saying when you give a voice command.
The potential for natural language processing to transform the workplace is extraordinary. The applications are potentially limitless, and it’s the sort of technology that could lead to a productivity boom. A financial services company called First Horizon National Corporation is looking at how it can use natural language processing to improve employee morale – a significant issue in the financial sector. It’s using software to listen to conversations between workers across the firm and then using special AI techniques which draw not only insights from the content of their discussions, but also their tone. The software can, for instance, tell whether a person is feeling stressed, angry, or cheery simply from the tone of their voice and their choice of words. The program then feeds all of this information back to a central processing facility for interpretation, giving managers unbiased information about the current state of their team.
Natural Language Processing To Improve Document Processing
Natural language processing is also being increasingly used to read and interpret documents. Gone are the days where an employee would have to sit down and spend hour after hour poring over text to extract relevant information: we now live in a world where computers can extract meaning and highlight it for further investigation.
Deloitte recently partnered with Kira Systems to find a way to process the information contained within documents faster. If the project is successful, it will have profound ramifications for practically every enterprise that processes contracts and other long documents, speeding up administration and, hopefully, lowering costs.
Using Blockchain To Discourage Tampering With Goods
Blockchain is a technology that has been around for some time now. But it’s only recently that managers and company execs have learned about how powerful it can be. Blockchain allows firms to create immutable ledgers – records of transactions – which nobody can tamper with.
The international shipping company Maersk is using blockchain to prevent people in foreign ports from falsifying goods manifests and other documents and to check the point at which goods were tampered with or went missing. The technology makes it so that the shipping company always knows the point at which products were present in its containers and can identify patterns when they go missing.
It’s not just shipping companies that are benefiting though. Imagine you’re a diamond seller and you want to prove that you sold a genuine diamond at the point of transaction. Diamond sellers can now eliminate counterfeit diamond records by registering the diamonds they sell on the blockchain for all to see.
It’s clear, therefore, that companies are increasingly having to adapt to digitization in new and exciting ways. How technology develops remains a mystery. The speed at which things are changing is likely the thing that will limit the impact on established companies in the short term. Few firms have the expertise to implement new technological solutions. It takes time to train people to put natural language processing or blockchain technologies into place.
The time will come, however, when it’s not just a few companies on the New York Stock Exchange which we call “tech” but practically every firm in the world. At that point, the term “tech” will cease to have significance.