We’ve all heard a lot of theories about companies going the digital way, or people using digitalization as a way forward, or even “digital transformation” being mentioned.
But what does the term “digital” really mean?
For some, digital is a new and revolutionary way to connect with your customers; for others it’s just about technology or just a new approach to doing business. These are all accurate.
“Digital” in essence is about using the technological transformations of the last two decades to do business — and do customer satisfaction, or CSAT metrics — in a more effective way. You can look at a “smart refrigerator” that tells you when you’re low on milk as one example of a digital transformation. You can also look at a chatbot that handles customer returns as another example. The umbrella is pretty wide, and there are different interactions with tech and digital in terms of one’s personal life and one’s professional life.
At Conectys, we’ve worked with about a dozen clients on digital transformation efforts. The main thing we’ve learned so far is that you shouldn’t reinvent the wheel when it comes to digital transformation. Too much change and too many shifting processes at once confuses people and leads to inaction in the long term, but if new processes can be slowly baked into existing models and the company can become more efficient as that happens, all the better! Companies need a deliberate approach to “digital transformation” to reduce the pain of rapid change.
Here are a couple of core terms that come up as companies begin to transform their processes for the modern age.
Robotics process automation (RPA)
This stands out as the most used term when it comes to a digital approach in a company. Why? Because it is highly efficient, very accurate and really cost effective with minimum implementation time.
RPA bots are a really safe, non-invasive technology that provides perfect consistency when performing activities across multiple systems each and every time.
Think of RPA bots as a Digital Workforce that can interact with any system or application. For example, bots are able to copy-paste, scrape web data, make calculations, open and move files, parse emails, log into programs, connect to APIs, and extract unstructured data.
And because bots can adapt to any interface or workflow, there’s no need to change business systems, applications, or existing processes in order to automate.
The core benefits:
· Cost-effective — We know that the most important thing for a business is money-wise implementations, and that’s of course the honest truth. So, what makes RPA so cost-effective?
Robots can operate 24/7 and take no vacation when compared to humans. Having robots take over some of the manually intensive work from humans could result in visible gains for business.
· Accuracy & Efficiency — RPA offers improved services to processes that have a high probability of human error, thereby increasing accuracy. The best part here is that robots follow all rules to the dot, thereby producing 100% accuracy in the process results.
· Increases employee productivity — RPA ultimately facilitates humans and robots to do just what they excel at. As RPA frees the employees from their mundane tasks, they can focus more on client and customer interaction, relationship management and other such activities where humans naturally excel at. Thus, leading us to the next benefit.
· Increases customer satisfaction by delivering better quality of work with high accuracy and improved customer/client interaction leads to increased customer and client satisfaction
How do you identify what processes to target for automation?
1. Highly manual and repetitive processes — This means activities that have to be done on a daily, weekly or even monthly basis which involve a lot of manual work and are prone to human error.
2. High volume processes — There are always those activities which take a lot of time due to their volumes.
3. Rule-based processes — It’s not that the robot cannot take decisions on its own, but they strive the most on activities where the rules of processing are clear and follow a template-driven set of instructions.
Chatbots
Chatbots are also robots, but they are the ones that usually are more visible to our end customer. They are artificial intelligence (AI) programs that simulate human conversation through voice commands, or text chats, or both and can be embedded in and used throughout any major messaging application.
There are multiple types of chatbots with different roles and brought value to a company, so let’s quickly mention some of them.
Support chatbots — perform one main function, like help answer common questions or walk a user through a website on what the offered services are
Skills chatbots — follow commands, don’t require that much context and can usually be integrated with other technologies like an RPA bot which will take over the process from a point forward.
Assistant chatbots — know a little about a lot of things. They’re usually conversational and entertaining to use. Like Siri from Apple or Alexa from Amazon.
Every chatbot is different, but they do have some benefits in common.
· Availability — as you can imagine, a chatbot doesn’t work in shifts. It is present where we want it 24/7/365.
· Peak management — it can also handle multiple chats at the same time. Think about a scenario where 10 clients ask “what time is it” to the same person every day. That would get really frustrating at a point.
· Customer experience improvement through analytics — Wow! That sounds like my information is being used. Not exactly. A chatbot will simply identify the patterns of questions it gets asked and will flag the ones that weren’t in its scope from the beginning. This will mean that once the development team codes this part of the chatbot as well, future enquiries with the chatbot won’t have a missing answer, thus improving the overall customer experience.
You can integrate a chatbot on your landing page that will mostly deal with the issues or the frequently asked questions from your customers or you can also aim into designing an internal chatbot which its role is to keep the employees informed about several topics.
Either way you think of implementing a chatbot solution for your company, it is always the right answer for improving the customer or the employee experience in your business.
Adding an AI teammate is a fast way to kickstart the digital transformation process that gives employees a taste for the future of work.
Machine Learning & AI
Artificial intelligence is the simulation of human intelligence processes by machines, especially computer systems. Specific applications of AI include expert systems, natural language processing or speech recognition.
Machine learning is when algorithms use statistical techniques to spot patterns and take necessary action are used to iteratively learn, describe, and improve data in order to produce better outcomes.
Some examples where machine learning makes the most sense:
Customer relationship management — CRM software can use machine learning models to analyze email and prompt sales team members to respond to the most important messages first. More advanced systems can even recommend potentially effective responses.
Business intelligence — BI and analytics vendors use machine learning in their software to identify potentially important data points, patterns of data points and anomalies.
Human resource information systems — HRIS systems can use machine learning models to filter through applications and identify the best candidates for an open position.
Overall benefits include:
· Faster and Better Data Entry — Data duplication and inaccuracy are the major impediments that can be significantly improved by predictive modeling and machine learning algorithms. Machines can perform time-intensive data entry tasks, leaving humans with their skilled resources free to focus on other value-adding duties
· Keeps Improving Over Time — Because of the constant input of new data being processed and evaluated, the system becomes more accurate and predictive over time. The closer to 100% accuracy rate the algorithm becomes, you’re able to make more accurate and better business decisions.
· Interpret Past Customer Behaviors — Machine Learning will let you analyze the data related to past behaviors or outcomes and make better predictions of future customer behaviors.
When a machine learning algorithm is being designed, it will only learn what you “feed” it. It won’t go over the top unless you program it to do that.
An example: a business gets multiple emails about whether a product is in stock. Why emails? Because there’s not an interface within the e-commerce platform to show if something is currently available. Hence, customers need to email and check.
Machine learning can be brought in here to understand the most common type of customer query (what’s in stock), and then can be taught where to go to find the answer, and how to respond to the customer. Now the customers’ needs are met quickly — at the same time that the company is hopefully improving their online interface.
The Digital Transformation Journey
An implementation based on the complexity levels can take from 2 weeks to 8 weeks for an RPA solution, to even 10 weeks or more if we were to combine the technologies as a hyper-automation solution.
In order for the digital team to provide an accurate estimation of how much a project will take, we would have to go through a transformation journey. This means that there are of course stages of phases of a digital implementation to be taken into consideration, so, let’s go through them below:
· Phase I — Discovery: This is where we review the client requirements and need to determine if the process is indeed right for automation
· Phase II — Analysis: The complexity of the process is analyzed, and a timeline of implementation is provided
· Phase III — Solution Design: The process architect develops a process definition document (PDD), where we record each process/step/conversational flow in detail
· Phase IV — Development: This is where the magic happens. A developer, or a team of developers based on the complexity of the project, starts creating robots based on the solution design.
· Phase V — User acceptance testing: Every solution needs to be tested, so this will be done in a pre-production environment.
· Phase VI — Go Live: Now, the robot is ready to roll! The solution is ready to be pushed live and it will be done at the clients’ signal.
· Phase VII — Maintenance: The solution is supervised for a brief period of time, just to make sure everything goes as we planned
· Phase VII — Improvements: The final phase of the projects, where together with the business team, the Digital team works on how we can adapt, improve or change the solution based on the tracking records.
Unlock your company’s potential
Digital mainly is the key to unlocking many ways in which a company can grow.
We hope that this article gave you an insight into that, and we hope you have already created a vision on how you want to do things in the future.
We will be more than happy to assist you with any questions you might have regarding automations, and maybe we can start looking together on how we can transform your business.
Visit our website, and check some of the other use cases which we have developed for internal use, or external clients to help them with some of the repetitive tasks.
