Fuel Innovation to Improve Results

fuel innovation
AI & Machine Learning, base

What does innovation mean to you? A new design? A new product?

To me – for something to be truly innovative, it needs to improve upon something we already have or do. Therefore, it can be a product or could be an idea or a way of doing something. Look at the world around us and what we use, not that long ago a phone was something for making and receiving calls, then we sent and received messages and that has evolved into the smart phones we are now all fully reliant on (maybe too reliant sometimes!!) The point is, someone took something we used for conversation and thought – how do we improve on that?

Innovation is viewing something differently from the way others view it

Technology over the last 20 years has evolved at an exponential rate and keeping up can sometimes be difficult. Business has embraced technology at varying rates and can always look at ways to use technology to improve ways of working. The latest technology being applied to business settings is AI and Machine Learning and although this might at the moment sound like a step too far for some people – this is having a major impact on the way we do business and in a lot of cases is taking customer service to a new level.  

Let’s look at some practical examples:

Chatbots to improve customer service

What is they key to excellent customer service? I believe it is being available when the customer wants to speak to you and not when you want to speak to the customer. Having that availability 24-7 is convenient to a customer but is it practical for you trying to run a business? Should you have customer support agents work shift patterns to ensure availability when it is needed most? Artificial Intelligence (AI) applications are making this possible and ensuring businesses stay ahead in terms of providing seamless, always on customer service. They key is in making sure the customer doesn’t know if a person or a programme is answering their query.

Take the example of a potential customer who has a product, pricing, delivery or support question out of your normal office operating hours. Should they wait until the next day or will you offer them support when they need it and not when your team are available?

The chatbot is the way to do this. Yes – someone can be behind the online chat function to answer customer questions but out of hours, a programme can be trained to recognise key words in a question to offer a response in real time.

Of course, there is no replacement for human interaction and in some cases it is necessary and where needed a chatbot can answer initial questions and can escalate to an agent if intervention is required.

“By utilising AI we can train the system to recognise a question and respond appropriately”

Analysis to extract key information

Analysing a vast amount of data across multiple documents can be a long, laborious task and takes a lot of manual effort. Our example is one where you have a huge amount of information gathered from various sources and you want to pin-point one item or topic from each of those sources. What do you do? You could have a team read the full document set or you could train a data analytics using machine learning to scrape the documents, recognise the topic you are looking for and extract the key information.

That’s exactly what data analysis utilising AI can do for you. It’s not only about reducing the time spent on finding the relevant information, it’s about ensuring staff spend time analysing and working with the data you need instead of spending their time finding the data, meaning they get to spend more time on meaningful tasks.

“Utilising the machine learning algorithm has resulted in a 75% reduction in manual effort”

Read data to eliminate duplication of work

There are other ways AI and machine learning can be applied to data to reduce manual effort. An Optical Character Recognition (OCR) tool can scan paper documents to add data to a system, replacing the need to manual re-enter data that has been captured on paper.

Take for example, situations or locations where a device cannot be used to capture information electronically and therefore needs to be captured on paper but then has to be transferred into a system. Staff capture details and then spend their time re-typing the information. With OCR this is avoided as the system has learned to recognise and translate text, removing the manual duplication of effort from the process. The initial scan allows for a final check to ensure information has been picked up correctly and put in the right place in the system. Even when corrections are needed, it is still a much quicker process than manual typing in the information.

“Since implementing an OCR tool we have seen an 80% reduction in time spent on administrative duties”

Predict to improve scheduling

In any aspect of life prevention is much better than the cure and in an equipment maintenance schedule, this is very true. Within an inspection and maintenance schedule, equipment will often run until it breaks down or the routine inspection may pick up an indicator which will say that something is not working quite as it should. In those cases, equipment will be taken offline at short notice and as a result will impact production timescales.

Utilising AI tools enables predictive maintenance. Being able to analyse and pick up on trends on the performance of equipment over time highlights where things are likely to go wrong enabling you to schedule repairs and maintenance at appropriate and convenient times before they break down.

“Predictive maintenance has the potential to reduce maintenance costs by up to 25%”

Do those practical examples make you think about how you could improve things in your business with these tools? Then speak to us for a no obligation, completely free consultation with one of our team and see where this innovation could lead you.

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