Nurturing data-driven innovation: Opportunities and challenges
It has also been observed that with many small and medium firms where data is generated or gathered by the marketing or operations function, it is not always used by other departments to drive decisions and innovation.
Successful digital transformation initiatives undertaken by businesses are resulting in productivity gains, cost reduction, additional and new revenue opportunities and improvement in market shares. In addition to these benefits, the extensive data being generated from these initiatives, when tapped systematically and converted to useful analytics and knowledge throws up multitude of opportunities for innovation. The primary objective of innovation is to create value for the business. Innovation is a change that creates a new dimension of performance, says Peter Drucker. Organisations have recognised the importance of nurturing innovation in existing businesses and hence as a part of the digital transformation initiative, organisations are also undertaking restructuring of the businesses as required to support the innovation ecosystem.
Innovation in data-driven organisations is driving efficiency and growth in three possible ways-business process optimisation, enhanced customer intimacy or product or service innovation. Business process optimisation leads to opportunities in productivity gains and cost mitigation. Enhanced customer intimacy could result in brand loyalty and creating upsell/cross sell opportunities. Product and service innovation outcomes include reduced cost of servicing and new or enhanced income streams. Recognising the potential benefits, organisations are making significant investment in each of these areas in digital technologies and are harnessing knowledge and useful insights thus channelising them for fostering innovation in their businesses.
New knowledge is essential to produce distinctive products, processes or services to create customer delight. With the boundaries of knowledge having got redefined on account of the access to deep insights of customers’ expectations and buying behaviour, the potential for innovation has been dramatically enhanced. Data-driven innovation has the potential to generate economic value through a number of channels-internal as well as external to the business. Knowledge management can play a significant role in fostering innovation aimed at speed and competitive edge through a combination of approaches-building collaborative frameworks with various stakeholders, tapping and cataloguing knowledge with the objective to replace ‘push based approach’ with ‘pull based approach’ to accessing knowledge as and when required for effective decision-making.
The relevance of data driven innovation is applicable for citizens’ services as well. For example, by tapping and analysing the data to improve the well-being of the citizens through accurate profiling of the medical needs of the citizens and targeting the appropriate medical care to them, an enhanced health care system could be implemented. This could result in savings and most importantly, help in prioritising the services that are required to be delivered on the basis of available expertise in different healthcare centres, proximity to the community, criticality and affordability. Further, by sharing the data related to diseases, treatment and success rates with the citizens, not only is better awareness created and citizens are able to make informed decisions concerning their health, they would be able to make timely decisions regarding hospitalisation and access to the right experts without delays.
Farming is another segment that has huge opportunities for productivity gains through innovation. In New Zealand, farmers are using a product called Farmax to manage complex issues related to farming activities such as ideal time for buying stocks, grazing and prevention of diseases thus transitioning to more data driven decision making and actions rather than relying totally on intuition and experience. In India too, there are mobile based applications which many farmers are using to their benefit and with increased adoption of such systems, farmers would be able to adopt right farming techniques and take timely decisions which would deliver higher productivity. The Smart City projects being implemented in various cities are aimed at higher convenience and access to better quality public services and we have already seen some excellent examples such as land records digitisation.
Despite the several advantages that could emanate from data driven innovation, many organisations continue to face challenges in taking full advantage of the possibilities. The primary challenge is around the definition of data needs, lack of required processes to tap into the data pool and the linkage between various forms of data. Therefore, gathering and organising the data in the required formats is the necessary first step towards the later processes related to deriving insights from such data.
It has also been observed that with many small and medium firms where data is generated or gathered by the marketing or operations function, it is not always used by other departments to drive decisions and innovation. This could be on account of barriers to the adoption of data-related technologies and bringing about the necessary changes in the organisation structure. Resourcing the requisite talent with the right skills and putting in place a comprehensive change management programme, including facilitation of upskilling of the current employees to learn and adapt to the changing scenario, would be essential elements for heralding the environment that supports innovation.