In many industries, products and services and the way they are delivered to customers have just not changed in many decades. Many industries still have cohort or group based pricing, and work in batch mode of manual operations. Companies in many industries still rely on manual process to collect, collate and analyse data. Many companies are prone to missed or delayed information, data integrity challenges, high turnaround time, and losse overs. With advent of new technologies like IoT, Chatbots companies in many industries can now personalize their services, design customer-specific pricing policies and engagement models. With chatbots and other technologies, companies can now involve customers in the service delivery process, DIY reducing the service costs and increasing customer engagement. Digitization and automation using technologies like RPA or bots drives companies to redistribute their employees to more productive work. Automation not only reduces costs, but also improves client experiences. Digital technologies like AI, ML and others offers companies an opportunity to accomplish more, enable people to be more productive, win back customers through better services at personalized price point.
In their rush to adopt AI, RPA and bots some of the companies seem to be missing the wood for the forest. Many seem to be pursuing “Chatbot at every interface without asking what tangible values can eb brought about in terms of product or service optimization, productivity and tacking operational efficiencies. Companies forget AI, ML & other digital technologies are not about wrapping a digital technology around an existing business, but more about how it alters the way the business will work across divisions and teams. AI, ML adoption must enable business transformation. Adoption of these technologies must help you rewire your business model, process and people engagement, rather than just tinkering with what is happening now.
We always recommend Boards and CEO’s considering adoption of AI, ML and other digital technologies evaluate the intervention using PCC-RIO framework. Adopting digital technologies is to build agile business, that is the key. Start asking what is the (P)urpose?. Does adoption of these tools improve customer experience, streamline supply chain or offer new insights to provide personalized services or even disrupt the business landscape. Next ask whether it is (C)omprehensive?. Does it cover depth and breadth of all workflows that could be replaced or still has a mix of legacy and new?. How does it use both company private and pubic data to collate and analyse information?. How much does it (c)ost, does it pay for itself, when and how? Next is what results it will deliver within teams and business units?. What are the (r)isks, how will this disturb the exiting business model, how will business as usual will be managed?. How these changes will (i)mpact the work and business rules?. Finally the (o)utcomes, some of which may be realized quickly, while some may happen in medium or long term. Define these measures and goal them appropriately.
Successful AI, ML, RPA or BOT interventions have few things in common.
· The first step in using any of these technologies is availability of data. Invest in capturing tons of data from your old records and from multiple files across departments.
· Select an intervention that is less risky, outcome are visible and can be easily advertised. Chatbots, and RPA score high on this count. It is better to start with customer facing interventions first, let them evolve and scale up rather than rewiring the whole organization.
· Based on business risk, use case scenarios that narrow down choices as opposed to completely machine led experience work best, even if they are less precise. Product recommendation or churn analysis are great options to pursue.
· While adopting these technologies, visualize the organization and industry 2-3 years ahead and break down all barriers. Crystal gaze into how smoothly work can be done and use mind maps to identify options that may emerge
· Have a mindset of disruption but roll out technology adoption in stages. Define Wave 1 with a shirt time period, this must yield tangible benefits. Follow Wave 2 and others keep the momentum of change.
· A separate office or a champion to drive technology innovation reporting to CEO or Board works best
· Instil teams that can experiment work at front end and redesign organization to be more outcome centric, high on adaptability and learning.
On a closing note, AI, BOTS and other technologies will find more application across organizations. Marketing, sales, operations and other departments will adopt these technologies to break down barriers and deliver Omnichannel and Omnicare customer experience. Like other digital technologies, AI, ML and RPA will not replace people, but take away boring and repetitive work and complement high level tasks.
Dr TR Madan Mohan and Nupoor Sinha