For an enterprise of the future, it is prudent to match steps with the evolving times— innovate, adapt, and leverage new technologies. A critical difference between today’s enterprise and the future enterprise is the level of digital transformation. Businesses need to take that leap of faith. The enterprise of the future will look at high-end technology as an enabler, notwithstanding any impediments to its adoption.
Advanced digital technologies such as artificial intelligence, data analytics, and machine learning are propelling organisations to become intelligent enterprises. Insight-driven transformation is now a necessity, not an option, to advance business strategies and build competitive advantage. A recent survey found that nearly 80% of business leaders believe it will be important for organisations to become intelligent to achieve future success, but only 17% of companies consider themselves intelligent. How can an organisation evolve to become an intelligent enterprise of the future? Our work with leading global enterprises has uncovered several critical considerations.
Everything is changing fast in business and personal ecospheres, presenting both challenges and opportunities. An enterprise of the future should be in lockstep with these evolving times by innovating, adapting, and leveraging new technologies. A critical difference between today’s enterprise and the future enterprise is the level of digital transformation. Businesses need to take a leap of faith and accept that the innovation of today is only going to take an organisation so far. The enterprise of the future will look at high-end technology as an enabler. As challenges evolve, so will the technological solutions.
The first step to become an insightful enterprise is to break down silos and established processes and question the way things are done traditionally. Accept the need to pivot amid the disruption. For old establishments, the competitors are no longer established names; it is the shiny new start-ups causing huge disruptions. Some of these gamechangers can slash process time significantly based on AI-generated insights. For instance, a US-based insurance firm turned out to be a vanguard in the sector when it brought down claims processing times and payment for premiums to a few seconds, compared to a few days from traditional insurance companies.
Enterprises must also learn, unlearn and relearn—much like their employees, partners, and customers had to adapt to new digital behaviours even when they felt reluctant to change. In the past, customers would have to visit a physical outlet for any task like a bank to open an account or shop for clothes. In the new normal, many of these are now remote activities. Customers are now ready to adapt to a digital economy, making this a great opportunity for organisations to realign their mindset and processes to get closer to the customer by going digital.
Another key factor to becoming an insightful or intelligent enterprise is placing insight-led decision-making at the forefront. Every possible aspect of business is based on insights. However, it is the willingness of an organisation to adopt new technologies that drives success. Value insights as important assets, as integrated insights can help companies plan precisely and forecast demand. The current dynamic market economics compel organisations to become more agile and nimble in terms of planning and forecasting demand.
For example, a healthcare services company may greatly benefit from a predictive analytics solution that would enable them to forecast the upcoming demand for ventilators, beds, and other required medical equipment based on COVID-19 case trends. The forecast would help to optimise the current use of supplies and plan for future needs. In addition, the solution would also alert local authorities to make informed decisions like organising blood collection camps in areas of high demand and supplying excess resources to the nearest location in need.
At the risk of sounding cliche—data is the new oil. Data can be in the form of physical data or an inference. To make optimal use of it, one of the fundamental blocks is the right kind of integrated data. Organisations need to understand the best way to utilise available data to achieve desired outcomes. Some insight-driven organisations are currently using data to drill down for new opportunities. For example, food-delivery apps provide cuisine recommendations to customers based on prominent restaurants in the area. And, if a customer does not order for a while, promotional offers and discounts are sent to promote new activity.
Customers are partnering with service providers in their strategic initiatives to emerge as an insightful enterprise. For example, consumer analytics program can help a company with personalisation and customer journey tracking for all of its customer base. The program will provide insights into campaigns, behaviour, membership, retention, and other attributes that would enable the company to increase share of the consumers’ digital business spend.
Once an enterprise realises the power of insights, the next step is building the ability to make this data/insight beneficial to the company. A key factor here is having an insightful workforce. Upskilling the current workforce unlocks the full range of power for new technologies to provide faster, high-value outcomes. In fact, in a Wipro survey, 43% of organisations said that reskilling the workforce was one of the most important enabling factors to becoming an intelligent enterprise.
The knowledge worker will emerge with the advancement of an intelligent enterprise. A knowledge worker is an individual who will supplement machine insights with one’s own experience or judgement. Companies need to equip knowledge workers with an ability to separate the noise and the signal. Machines may only generate insights with a limited range of accuracy. A human is needed to interpret that insight to improve the accuracy. But the result will only be as good as the human analysis. Artificial intelligence aids the human mind in terms of making decisions faster. For instance, in Lean Six Sigma methodologies, insights help reduce waste by improving the accuracy of judgements, but the decision is still made by a human.
A futuristic organisation will have humans and machines performing complementary functions. For instance, in Singapore, certain trains are driverless. These trains are controlled via automated programs. However, there is still a human in the system, sitting in a control tower. That person may be controlling ten trains concurrently, but he or she is very much present to make a decision in case of emergency.
Given the enormous spectrum of advantages derived from AI and data, it is hard to imagine any roadblocks. But they definitely exist. The barriers to success come from within the organisation—resistance to change. The only way to cross this barrier is to get comfortable with the idea of making a difference to the company and its customers. Realise and accept that today’s competitors may not be the competitors of tomorrow. Tomorrow’s competition is predicated upon being more insight- and-AI-led, and more automation-driven.
The second barrier comes when an organisation is on the transformation path to embrace AI and data. With the far reach of data, privacy and data sharing are a concern. Organisations have been forever struggling to draw the line between ethical and unethical when it comes to data sharing/selling. Companies that have access to users’ personal data should use discretion. Strike a balance between leveraging the data for the benefit of the user and the organisation within the realms of ethics.
While change is the only constant in the world, it is often very difficult to execute. The culture of an intelligent enterprise evolves based on disruption happening in its industry and across sectors. As an organisation, embrace the opportunity to make a difference for the company and the customer. One of the biggest hurdles in successfully transitioning is a “top down” company culture. The drive for a culture of change should begin at the C-suite and set an example for peers and subordinates. The more the drive to change comes from the top of the ecosystem, the higher the chances of an organisation transforming into an intelligent enterprise. Look at functions and processes. Identify the low hanging fruit or where big gains can be made and start transforming and changing in those areas.
Building a culture of change is not an easy task, and business leaders need to take bold steps to make sure it percolates to every process and function within an enterprise. Organisations might need to take steps to cannibalise some of their own business to inflict the change, but this may be necessary to grow. Change takes time, and so will creating the right culture. Start small and gain big.
In the journey to be insightful, organisations need to seek external help wherever needed. External help brings an “outside-in” perspective, process and technical expertise, and relevant experiences from similar journeys. When aiming to be the leader, learn from the best practices across all sectors. Engage in cross-industry learning. Many companies do not ask what their direct competitors are doing; they watch and learn how other customer-facing companies are enhancing the user experience. Observe and absorb the disruption happening everywhere. To innovate, go beyond what others in the ecosystem are doing. By leveraging insights effectively, organisations can create a competitive advantage. Being insightful is not a choice, but a daily imperative that is needed to survive and thrive in this fast-changing environment.
Data, Analytics, Artificial Intelligence, Digital Transformation, Leadership, New Technologies, Intelligent Enterprise, Insightful Organisation, Automation, Wipro Technologies