Optimizing It For Human Experience Makes For Good Business
Possessing three decades of experience, Jay is a leader with a conviction that learning, growing and inspired contribution are the basis for personal satisfaction, team and business effectiveness.
The iPhone dramatically improved human experience. The experience was so intuitive that it spawned the big smartphone industry. Apple became one of the most valued businesses in the world.
Should human experience be a big concern only for end user products and services?
Ultimately all scientific, technological and business activities are about improving human experience. All value delivery chains must result in better experience, for all humans engaged in that chain. So, even though it may not be obvious, Enterprise IT is no exception.
Motivations for using AI/ML
Business leaders usually make decisions with primary goals such as increasing revenue, profit and shareholder value. Products, solutions and services are developed, deployed and operated toward achieving the above goals. Improving human experience is not seen as a primary goal but as a desirable by-product. This missing alignment is a huge business opportunity.
The Internet, mobile networks and enterprise networks have become the fabric/platform for creating and delivering value through cloud architectures. Artificial Intelligence and Machine Learning are powerful tools accelerating the value delivery chain. In a recent Gartner report, it was found that more than growing revenue and reducing cost, the motivation for using AI/ML for Enterprises is to improve customer experience.
Through the lens of an Enterprise IT leader
Budgets are generally flat to down but the need for performance, capacity, security and agility is always increasing. Enterprise IT is the platform for business value creation and all departments are the demanding customers of IT. Business-created value, in terms of products and services, is either directly about improving end user experience or feeding the next business in the larger value chain.
IT leaders plan for improvements, deploy and operate (Day 0/1/2) to satisfy the increasing demands of customers of IT. Rapidly changing
technologies and evolving customer needs are big challenges, especially with constraints in budgets. The solution to this problem cannot be about managing expectations but must involve using technologies like AI/ML to convert this situation into opportunities for increasing value and improving human experience.
‘Artificial intelligence’ and ‘machine learning’ are buzzwords and used by many with different meanings. In the context of Enterprise IT, machine learning helps in finding patterns and relationships in large volumes of data about business operations and outcomes. Artificial intelligence takes advantage of such patterns and relationships to find answers to questions that IT operators or customers would have and also take automatic, remedial actions, should there be a degradation from expected performance.
Such an invisible infrastructure enables smooth delivery of services to customers which will dramatically improve their experience and propel business value delivery forward without friction
Here are a few typical questions that well-designed AI/ML systems would be able to answer and, in doing so, dramatically improve operator and end user experience:
(i)Even though all my servers, storage and net-work gear are all showing as ‘up’ on the dashboard, why are several customers complaining about slow access to all services? (ii)Which compute and storage nodes are likely to degrade in performance and by when requiring remedial plans? (iii) Why is Alice not able to access IT resources from her home office and how to fix the problem? (iv) Why was Bob’s video call with investors jittery? (v) How can IT infrastructure avoid such interruptions automatically?
Good AI/ML systems help in proactive planning for infrastructure expansion(day 0), fast and easy deployments(day 1) and efficient operation (day 2..n). Effective and efficient operations include proactive problem detection and automatic remedial actions. Such technologies get IT operators out of the need to be at red zone stress levels all the time. And, in addition to that they get customers to confidently rely on infrastructure to the point that they don’t even see the infrastructure.
With such emerging technologies, a healthy, well organized infrastructure becomes invisible and yet effective for end users, like electrical distribution systems. Such an invisible infrastructure enables smooth delivery of services to customers which will dramatically improve their experience and propel business value delivery forward without friction.
This is a recipe for growing customer delight, making more room for operators to innovate, accelerating creative and new services for customers, reducing costs, increasing profitable revenue and accumulating shareholder value.
Pace of change, uncertainty, and budget constraints, along with the need for ever increasing performance expectations are big challenges for IT leaders.
Vendors and partners who have embraced AI/ML in their products and services with “experience first” as their guiding principle can help in turning these challenging situations into opportunities.
Businesses that orient toward improving the long term experience of the human chain, using new technologies such as AI/ML, will also increase the value of the delivery chain and profitably grow revenue, as well as have a positive social impact.