It’s good to chat, but who to? The role of chatbots in digital transformation
Digital transformation, despite being an overused and over-hyped term, describes some of the operational change that some organisations have embarked upon, many had contemplated and planned, but now many more are suddenly having to deliver.
It is a time when the benefits of streamlining, automating and operationalising IT processes could be significant, but many may not want to take the risk of several radical changes to processes that have in the past worked “OK”.
While there is a lot of hype around the digital side of transformation, much of the critical effort tends to involve human changes. According to the insights report and survey conducted in April and May 2020 by Digital Transformation Expo, “people and culture transition” was the most-recognised element of digital transformation, and almost four in five respondents thought the biggest challenge and consideration would be adapting culture quickly to new ways of working.
Getting everyone on board with significant changes with working practices, at a time when they are dealing with so many other challenges, is going to take more effort than usual. However, IT teams are hard-pressed trying to cope in normal times, but now, not only is there more to do, but reliable IT and connectivity has taken on increased levels of importance and dependence.
The volume of helpful and/or important information, from third-party applications and services, to industry and government edicts, as well as changing organisational policies and procedures, is high, varied and rapidly evolving.
With time it could, in theory, be structured and curated, but in reality, few organisations have the time, resources or skills. And yet better access and discovery of pertinent guidance could significantly ease the people and culture transition, especially when individual focus and attention is being deflected elsewhere.
The result can be failures to discover information users require and more online support requests. At a time when much larger numbers of employees are suddenly working remotely or from home, this can result in costly waste of time. Could “virtual assistants” do more to help?
Innovation in artificial intelligence (AI) and machine learning (ML) continues to drive the chatbot space, and there has been a lot of attention focused on the external user experience, such as gathering leads and coping with customer service demands.
Smarter and tailored experiences may prove fruitful, and intelligently deflecting bad experiences will certainly help, but getting the right answer quickly to those inside an organisation could be a quick and effective cost saver, and perhaps reduce some of the frustrations of cultural shift.
While chatbot and machine-learning innovation and investment continues apace to build empathy and engagement, with companies such as Mindmeld, Nuance, Ubisend, Next IT and many others taking part, wouldn’t some of the perhaps mundane aspects of intelligent data ingestion would be really useful too?
Amid the recent announcement by Lucidworks of Smart Answers, a natural language-driven question-and-answer system for enhancing chatbots, there were some ideas to tackle this.
Most notable was the recognition of the importance of integrated and federated systems pulling together different elements from different vendors. To this end, Lucidworks offers a pluggable framework and flexible application programming interfaces (APIs) to aid integration to existing chatbot and assistant applications.
Smart knowledge bases need feeding with as much information as possible, with minimum effort. Smart Answers’ cold-start approach includes a connector software development kit to connect to knowledge bases from any source and build comprehensive responses whether existing FAQ are available or not. It also encourages those without data science expertise to train and deploy ML models using a low-code development environment.
If this can help direct users to useful existing, but hard to discover, insights to self-solve internal information issues and smooth cultural transitions, it might aid the shift to new ways of working without significantly affecting the hard-pressed and otherwise fully engaged IT team.
It might not be the glitzy sales-boosting side of exploiting new AI and ML technology, but there is nothing wrong with finding ways to reduce internal friction and frustration, and it may ultimately prove more beneficial to the long-term health of any digitally transforming organisation.
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