Innovation is one of the components of productivity growth. It can be applied to both processes and products. In order to be innovative, companies need to guide themselves into an analytical path – it’s about the journey. Data is driving product innovation across the entire business spectrum, from startups to the biggest companies in the world.
Process vs Product Innovation
Process innovation enables an organisation to put its resources to the most efficient use, while product innovation is about developing new products or better customer experience. Innovative ideas have always emerged from our resourcefulness and creativity. Today, data and analytics techniques are adding to human ingenuity to discover patterns in huge amounts of diverse data and to generate hypotheses.
In the area of process innovation, data and analytics are helping organisations determine how to structure teams, resources, and workflows. Understanding this variance and how to build more effective collaboration is a huge opportunity for organisations. In order to build high-performing teams and generate a multiple in increased productivity, data and analytics can be used to generate hypotheses, reviewing the optimal team size, complementarity of skills, whether teams need to work together in person, what past experience or training is important, and even how their personalities may mesh. Unearthing patterns that managers may not have envisaged. Vast amounts of data can lead to new insights on improving performance; residing in email, calendar, locational, and other data sources.
In product innovation, data and analytics can transform research and development in areas such as drug discovery, materials science, synthetic biology, and life sciences. Data and analytics underpin several disruptive models. Hyperscale digital platforms can match buyers and sellers in real time, transforming inefficient markets. Granular data can be used to personalise products and services—and, most intriguingly, health care. New analytical techniques can fuel discovery and innovation. Data and analytics are enabling faster and more evidence-based decision making.
Converting the analytic environment into an operational process drives innovation. For example, If targeted customers do not respond as predicted – and based on their feedback and observed behaviour since the campaign could be a spur to communicate differently.
Simulation analytics uses data to model a product with slight variations in material, design or ingredients. This can then be tested without producing a prototype, saving money, time and ultimately creating a superior product. This process requires powerful modelling capabilities and comparatively powerful computing power, but ultimately helps create significant value for both brands and the customers.
In order to become a data-driven organisation, it’s important to understand how user requirements might change over time. This way, providers can continue offering services that are in line with the demand, At OM Data Consulting we help clients implement effective strategies to meet the demands of tomorrow – identify trends, explore influences, dig deeper and reveal problems or discover new opportunities, developing an enterprise-wide Data-driven strategy that delivers value, tangible reporting outcomes and insights from business data.