7 Ways A Little Automation Can Make You A Big Hero
Digital Transformation isn’t all about the front-end user experience, it is also about accelerating the pace, effectiveness, and efficiency of your back end operations. It is the process of adapting or overhauling current business processes to incorporate digital strategies and technology into your company. This includes transforming your company to become fast, nimble and bold; using big data analytics to produce smart insights; and adopting infrastructures and devices that support and enable your team.
A simple way to start is with scaled automation. The advantages of automation allow employees to focus their attention on more skilled tasks, and on activities that will bring in more revenue or lower operating costs.
So where can your business start to implement scaled automation?
At K2 Digital, we have found that there are some quick-win solutions:
- STP (Straight-Through-Process) / Real-Time Processes — Many customer experiences start beautifully in the front-end with awesome mobile or desktop experiences. The trouble is that they break-down when submissions (i.e. forms, et al.) enter traditional and manual back-end operations. We have worked with many clients who have had beautiful user-interfaces, but haven’t developed the end-to-end experience. (I like to say digital transformation is much more than putting lipstick on a pig.) While implementing STP used to be cost prohibitive, and had a reputation for leading to highly inflexible systems, this is no longer the case. What’s more, organizations that are adopting STP are actually able to disrupt competitors by delivering solutions to clients in real-time, that are more accurate, and fulfilled immediately. These companies are leveraging decisioning systems, rules engines, machine learning, and AI (artificial intelligence). These tools can be integrated into existing legacy systems (instead of replacing them) to give instant results; providing a truly improved customer experience, and massive operational efficiency to the organization.
- Real-Time Micro Customer Segmentation and Customer Interaction Management — Traditional customer segmentation has been dead for decades. In its place, analytics teams are running constant custom reports, lists, etal. on their customers by specific criteria. These lists and reports are then fed into predictive models that help companies understand what their customers are likely to do next. This works, but it is incredibly time consuming, difficult to operationalize beyond a highly-targeted marketing campaign, and usually ignores a customer’s most recent interaction and typical behaviour. Whereas through data automation, organizations are able to track interactions across every channel, creating real-time micro-customer segments based on specific behaviors that are then fed back into all channels. This process enables unique and relevant offers, and personalized customer experiences. Adding to real-time analytics, is the ability to provide real-time customer interaction management, whereby every channel is updated on client actions in real-time. This allows channels to respond appropriately regardless of the channel the client is interacting with.
- Intelligent Application Monitoring — Typical application monitoring platforms often churn out dozens, hundreds, even thousands of issue alerts each month. Such high volume is difficult to parse and extract critical issues from. Fortunately, intelligent application monitoring is now possible, reducing the volume of alerts raised by resolving certain issues automatically, reducing “noise”, and only sending alerts for human-actionable items. Another benefit of intelligent monitoring is reduced downtime when an actionable, critical event is detected, since the pool of system issues is greatly reduced. These benefits are attained by leveraging machine learning twice — once to train the monitoring platform to understand the difference between expected behaviour and actual issues, and again on how to resolve issues once identified.
- Data loss prevention — An ongoing concern of organizations is the protection of intellectual property. If malicious users gain access to a system using stolen credentials, it’s nearly impossible to flag the online behaviour of the malicious user as being suspect and prevent the unauthorized access of IP. There are AI-based platforms that use intelligent user and entity behaviour analytics to identify, in real time, non-standard data access patterns. Using previous access history from valid users, AI can quickly and accurately flag anomalies and mitigate risks of potential data loss.
- Natural language generation — Most people have heard of natural language processing, but natural language generation is a relatively new concept. Where NLP can be used to analyze unstructured data and identify patterns and anomalies in text, NLG enables the automatic identification of the most interesting and important pieces in structured data, and produces a narrative with custom context and language for several audiences at once. Imagine performance reports that require customization for specific audiences (e.g. investors, advisors, website). NLG can automatically generate natural language reports that highlight the most relevant details for each group, increasing accuracy and efficiency.
- Smart contract review — Those who have ever had to review a large contract, agreement, or statement of work, understand how tedious it can be to read through and ensure all required clauses are present. Not only is this method time consuming, but the process is exasperated by tiredness and human error. Computers have stronger abilities than humans to identify these types of anomalies, but humans still play an important role in revision processes. Using a combination of natural language processing and machine learning, computers can identify missing content, which can then be actioned by humans.
- Chatbots . While early adopters of chatbot technology typically ended up with clunky rules based, search engine type interfaces, newer iterations of chatbots when implemented properly, are delivering amazing customer experiences and aiding in significant cost reductions.
If you are interested in learning more about what makes K2 Digital different from any other technology strategy and execution shop, please feel free to contact me at firstname.lastname@example.org.
I look forward to hearing from you.
About the author: Lawrence Tepperman is the Founder and Managing Director of K2 Digital, a leading digital transformation services and solutions firm. He has more than 20 years of experience building companies through marketing, software solutions, and management consulting. He founded K2 Digital in 2012 in order to help companies realize the tremendous benefits of digital transformation before they are disrupted.