Enterprise Adoption of Conversational Technologies
Published on : Saturday 01-08-2020
Chatbots can transform the entire process of Supply Chain Management and provide improved visibility, transparency and customer engagement, says Sasirekha Rameshkumar.
We have all now used to conversing (talk or type) with bots – be it Alexa, Siri or Google Home – for playing music, checking weather, getting sports update, reading news, finding out about traffic or even controlling devices at home. In Enterprises, currently Chatbots are heavily implemented in the areas of HR, IT Operations and Customer Self Service. Enterprises adoption of chatbots is growing exponentially thanks to rapid technology advancements in AI, customer demand for 24x7 omnichannel connects with business and the significant and tangible business values accrued by the early adopters. Conversational technologies – powered by Artificial Intelligence, Cloud computing, Analytics – make it possible for Enterprises to have meaningful conversations with its customers, suppliers, employees and other stakeholders. Conversational technologies cover a wide landscape of technology including Natural Language Processing (NLP), Speech-to-text, Text-to-speech, Language translation, Voice Biometrics, Sentiment Analysis, Emotion Recognition, Computer Vision and Extended Reality.
Conversational experiences is a major paradigm shift where machines (or systems) adopt to humans and continuously learns and improves with usage. Chatbots that are available 24x7, accessible in consumer devices and their preferred channels (be it Facebook, WhatsApp, Alexa, Siri, SMS), integrated with traditional channels (website, Mobile apps, Live chat) are impacting the brand image and the revenue growth of companies.
Today most chatbots use guided conversations with UI Widgets (if you observe you will recognise that most bots have natural language only from the bot side and the user response is mostly about choosing an option or typing the response) and still serve the purpose and bringing in benefits. In the near future, with the technology advancements in terms of deep learning and more processing power of smart phones, NLP is expected to advance to a stage where chatbots will truly be able to communicate with humans.
Chatbots in Supply Chain Management
Providing the right information at the right time, anytime, anywhere, in the channel of consumer choice brings in a whole new gamut of opportunities of transforming the business model and interactions. Supply Chain Management is one major area where use of Conversational Technologies can effectively simply, modernise and transform the entire value chain. With today’s technology it is easy to build a chatbot within a few weeks and the seeming easiness of this process is the key reason behind most heartburns after a chatbot implementation. It is essential to understand that effective integration with enterprise systems (ERP, CRM, SCM) and data (structured as well as unstructured) is what gives the Chatbots the real edge – to have meaningful conversations. Treating chatbots as yet another form of user interface would be a grave mistake. While it is easy to implement a simple chatbot, you have to go the whole nine yards to reap real business value in using conversational technologies for Supply Chain Management.
Where can we use Chatbots in Supply Chain Management? The simple answer is everywhere! Whenever there is an interaction with a user, chatbots are an effective alternative to traditional form of interactions. Realtime information updates, increased visibility and transparency, improved communication leading to collaboration are the key benefits of using conversational technologies. Most organisations have investment on Supply Chain Analytics that enables them to react to changes in real-world and making choices that minimise risks. Chatbots can be used to communicate these dynamic decisions taken in real-time to appropriate stakeholders in their channel of choice improves visibility and eliminates the traditional SCM problem of miscommunication or delay in communication. Order Management, Inventory Management, Fleet Management, Logistics, Employee Management and other areas of SCM can benefit from the usage of chatbots. In this article, let us explore deeper on the specific example of using chatbots in order management.
Chatbots in Order Management
Order Management or Order-to-Cash (OTC) process typically touches the entire supply chain – and involves multiple stakeholders including part suppliers, component assemblers, packaging services, distribution and logistics. While the process itself is complex and ensuring visibility and control a key challenge, the customers demand seamless experience and timely information. One bad experience could result in losing a customer forever and interestingly when the experience is good, customers – especially millennials go out of their way to recommend the company to others. Replacing the traditional channels and interface with the chatbots in the customer preferred channel in OTC paves the way for customer delight.
Chatbots can be used for making it easy and engaging for customer to place new orders, changing orders, cancelling orders, tracking orders and giving feedbacks. The entire order placement process – from collecting details like delivery address, mode to printing the order receipt – can be completed handled by a chatbot. The process can end with the bot providing the customers links for tracing their delivery. The customer can now converse with the chatbot to get the details of their order, delivery status, 24x7, using their own natural language and converse with the bot any number of times without having to make multiple phone calls, answer the same questions, remember the complex order ID or wait for agents to answer.
To have a realistic human-like experience, the standard approach of one size fit all of building a website or mobile app doesn’t work for conversational experience. Design thinking – which is customer focused and uses customer personas to model the customer journey – lends itself well to the implementation of the chatbot, especially if you are addressing a global market. The chatbots can be better designed to handle various customer segments, taking local nuances into consideration and bring the full force of customer analytics to provide personalised experience.
Chatbots should be designed in such a way to handle delays or failures gracefully. For example, if the chatbot is not able to access the specific information the customer is looking for, it should communicate it clearly and also have a mechanism to update the customer as soon as it can access the information. Using conversational metrics and analytics, A/B Testing and explicit customer feedback you can continuously improve the effectiveness of your chatbots.
While implementing chatbots, it is important to note that there are times when customer needs to have human interaction and it can be facilitated by handoff to humans (during normal working hours) or trigger call-back (typically during non-working hours). When such handoffs happen, it is important that the human agent is aware of the customer current status and earlier conversations which is typically provided by ‘Agent-Assist’ feature of conversational platforms.
Reimagining Customer Journeys using Chatbots
While chatbots can definitely change the user interface and experience, it comes with a huge potential of reimagining the entire customer journey and improve engagement. Let us take the case of the inevitable delay in delivery problem. Chatbots allows you to inform the customer at the earliest on the expected delay and providing details on the expected delivery date is the least that can be done. But that is not enough! Depending on the customer, ordered item, value of the order and other parameters, consider providing customers with more options like cancelling the order/part of the order, picking up from the current location, redirecting the order to a different delivery address (within certain parameters), allow choosing an alternate product, providing them some incentives to compensate the delay, etc. All of these can be done programmatically and using chatbots, so that the customer gets a consistent experience – and not different answers from different customer service agents.
While most of these scenarios can be anticipated and programmed, chatbots can also help in exceptional scenarios where human-in-the-loop is needed. Instead of multiple customer service agents handling similar queries from a large number of customers, the chatbot can converse with a senior customer service agent who can teach the bot the various rules to be applied and the options to be given to the customer. As the chatbots have access to the latest information and knowledge, they provide a consistent and seamless omnichannel experience eliminating human errors.
Another key factor for success of chatbots is in effective real-time communication to relevant stakeholders. In addition to updating the Enterprise Database, Customer decisions – cancelling of order or change of delivery instructions – has to be communicated immediately to the appropriate stakeholders (delivery agent or warehouse personnel) to make the experience smooth and frictionless.
Conclusion
Chatbots can transform the entire process of Supply Chain Management and provide improved visibility, transparency and customer engagement. To reap significant benefits, it is essential to look at implementation of chatbot as a business process reimagination and not yet another channel or user interface. Coupled with other technology investments already made by the Enterprise in AI, Enterprise Integration, APIfication, Cloud computing, IoT and Analytics, Chatbots can open up new avenue of effectiveness, efficiency and growth. The good news is that it is okay to start small with a simple chatbot, test the waters and keep enhancing the scope and ability of the chatbots to achieve business value. Implementation of chatbots in transforming supply chain management is more of an ongoing journey rather than a huge one-time investment. Enterprises should adopt the learning paradigm, similar to a chatbot, and continuously improve.
Sasirekha Rameshkumar is a Transformation Consultant with over 25 years of experience in mainframes, J2EE, IT management, performance management, enterprise architecture and digital transformation. She has managed large projects and consulting engagements for clients in the USA, the UK, Switzerland, Malaysia, Singapore and India. She has published articles in the Xephon magazine, the IBM Data magazine and the ISSA Journal and over 100 blogs in www.techtarget.com. She is interested in tracking technology trends – AI, IoT, Blockchain – and applying them in solving business problems and reshaping the future of business. Sasirekha’s current focus is in the area of Enterprise Virtual Assistants – VCAs and VPAs – bringing Conversational Experience to consumers where they are – Home, Car, Office etc., – in Channels of their choice (Messaging Platforms, Smart speakers, displays, phones, wearables); Exploiting technology leaps in Natural Language Processing, Voice, Vision, Mixed Reality, ML and AI to redefine Enterprises with the goal of making ‘Conversations’ the primary means of Communication – be it with machines, things, humans! https://www.linkedin.com/in/sasirekha-rameshkumar-2b486723/
