Business models in the hi-tech industry are undergoing a tectonic shift. The focus is on delivering supreme user experiences, and on launching new products and pricing models faster than competitors.
Hi-tech players also need to quickly integrate the products and services of newly acquired entities and offer an integrated suite of offerings to end customers. They need to deploy opex-based pricing models for service consumption, helping the end customer reduce upfront investments. For instance, instead of making the end customer incur upfront costs to buy network, storage, and compute infrastructure or high-end printers, can they be charged on a pay-per-use model? As the end customer priorities shift, the question for hi-tech companies is how to manage this change?
Digital operations: A necessity for digital business models
After strategies are crafted and roadmaps planned, it all comes down to the nitty-gritty of execution. To support new business models, a new set of operating models needs to be in place.
Let’s take the example of managed print services. When a company decides to move from selling printers to selling managed print services it needs to reconsider and redesign several of its processes. For instance:
Essentially the entire customer lifecycle management process has changed. From a one off engagement, it has become an ongoing engagement necessitating continuous monitoring, experience enhancement, and cross sell and upsell of products and services.
Existing systems and processes may not be able to handle these new demands.
Think before you leap
Some hi-tech providers are embarking on an enterprise wide transformation of processes to support new business models. For instance, we are helping a leading software major design, build and implement future state systems to easily offer subscription services. The architecture will also ensure rapid integration for future acquired entities. Our platform with a ‘fit for purpose’ approach will help the client simplify business processes, enable ease of doing business, and reduce the cost of doing business. In addition, we are helping them achieve optimal balance between product functionality and experience by defining processes through iterative pilots.
Most enterprises focus first on automation as a cure-it-all solution; however, there is a catch. In a rush to automate existing processes companies often forget to validate whether the process is even relevant in the new reality. And that is setting up for failure right there. It’s critical that companies focus on business transformation before they take up automation to avoid a ‘garbage in garbage out’ scenario.
Let me give you an example. A company wanted to automate their billing process. However, their existing process of invoicing the provided services was not able to provide a differentiated user experience. It was also repetitive, and effort intensive. Merely automating it would not solve the fundamental issue. To solve this, they first needed to reimagine the entire process, smoothen the journey, and then automate it for swifter execution and accuracy.
Process automation for accelerated advantage
With new business models, hi-tech is experiencing new levels of complexity, and companies want to quickly automate processes to bring in accuracy, speed, and economy. Robotic Process Automation and AI (Artificial Intelligence) are leading the charge in creating intelligent processes that require minimal human intervention.
Key business processes across the front office and back office are being transformed by combining RPA and AI. For instance, leveraging intelligent customer support could lead to 30% reduction in tickets, similarly automating marketing operations and campaign management could enable consistent and seamless product experience across the globe.
Making an informed choice
Let’s look at how a company can decide on which processes to automate based on current levels of automation and insights needed to execute that process (see Figure 1).
Figure 1: Process automation decision matrix
A process that needs no or limited insight (think order entry) can be done mechanically and is the easiest to automate – these are your low hanging fruit, if you need some quick wins. If such kind of data entry is already automated, take a look and see if AI can bring in more predictability into the process outcome.
On the other hand, processes that need cognitive decision-making are more difficult to automate. For instance, payment processes – these can have multiple different agreements and terms with various vendors. This is where AI based intelligent automation proves invaluable. For example, most hi-tech organizations provide a Market Development Fund (MDF) to their channel partners. AI could provide solution recommendations based on current sales and trends to help the channel partners improve their ROMI (return on marketing investment)
Once you have determined what can be and cannot be automated, we further break down the process and determine the extent of automation based on process complexity (see Figure 2).
Figure 2: Planning extent of automation based on process complexity
Harnessing data for maximum gains
Beyond delivering efficiency, the value of process automation lies in harnessing the data that is captured that can then be mined to unlock new advantages. Let’s take a typical plant production scenario. Plant downtime directly translates to loss. Usually downtime happens for maintenance scheduled that are traditionally prescribed by original equipment manufacturers (OEMs). These schedules do not consider peak production time and can lead to significant losses. What if we reimagine this process based on data that’s generated by plant operations? This data, with the help of solutions such as Wipro Looking Glass, can help identify assets that need maintenance and it can be scheduled in a suitable time window.
The move to subscription models has helped hi-tech companies get a 360° view of the customer – their usage patterns, SLA (service-level agreement) adherence, top support issues, etc.. This data can give invaluable insights on how the product or service can be improved upon and what are the crosssell/ upsell opportunities that you can leverage. A hi-tech major benefited from these insights when they were digitizing their contract management operations. Reimagining the contract management process, they automated it, and then harnessed the data to understand customer needs. This helped them to not only improve CSAT and reduce cost of operations by 20%, but in turn helped identify churn and improve renewals by 15%.
While data is definitely a game changer, it needs to be coupled with human insights and contextualized to the industry domain to give better meaning to the captured data. Even as hi-tech players dig into the goldmine of data, they need to use it wisely in a way that maximizes value for their business operations.
In a nutshell
Before you embark on your digital operations journey, remember that it revolves around three critical elements:
The ability to successfully incorporate each element in your transformation roadmap will ensure you are able to reap the much-touted benefits of becoming a digital business.
Finally, companies that are maximizing the benefits of AI use it not only to improve customer experiences but to also augment the human potential. Can you leverage it to enhance agent journeys in customer service? How would you compliment the data with domain understanding of a seasoned industry veteran? How do you make use of insights to help your people help your customers? These are some of the questions to consider before diving into a digitization roadmap.
David Ranjit William
Practice Head-Digital, Technology BU, Wipro Limited
David has over 20 years of IT experience working in the Communications & Hi-Tech industry. He is responsible for driving the Digital strategy for the Technology BU at Wipro. As part of this role he is responsible for demand generation, competency building, solution enablement and brand building initiatives for the Digital business within the Technology BU.