For businesses across sectors, the journey through the last 18 months has been nothing short of dramatic and unanticipated, if not downright adventurous. The socio-economic fallout of the pandemic and geopolitical unrest continues to test the resilience of business models and resolve of the functional leaders. However, as per Salesforce, at least 78% of the customers expect their brands to pace up innovation amidst the disruptions. So, at this juncture, how can institutions understand shifting market behaviors, fine-tune offerings and respond meaningfully to stand out?
It becomes easier to harness the chaos when companies have access to the right data and optimum visibility, empowering them to innovate confidently. HBR reports that 91% of the insiders acknowledge the centrality of data and analytics to successful business transformation. But how to generate the required momentum to stay relevant in a closely contested market? Interestingly, a recent Gartner insight, Accelerate Digital Business Through Data-Enhanced Innovation Process, lays down a complete data-driven innovation (DDI) roadmap. It implores CIOs, innovation leaders, and CDOs to collaborate and embrace a data-first culture, uncovering new opportunities for creating exponential business values.
The OECD defines DDI as applying data and analytics to elevate product development, business processes, organizational methods, or go-to-market (GTM) strategies. It can indeed help companies reconcile better to the unique business challenges of the time, mustering greater customer centricity and improved profitability. Some such use cases can be:
Product development: Data and analytics help identify gaps in the concepts and prototypes and point towards possible product and service innovation opportunities. A recent study by Business Wire found that companies that emphasize data and analytics in the product and service development lifecycle are likely to add 83% more revenue to their topline and improve profits by 66%. A case in point may be ZF Group that embeds KPIs early into its product development cycle. It drives the development journey by continuously assessing feedback against the stated goals. Also, Intuit monetized the usage data of its personal finance management (PFM) tool Quicken to seek out improved business opportunities, developing the QuickBooks accounting package for SMEs.
Business decisions: Over 90% of the businesses that prioritize data and analytics in their decision-making culture feel confident about assuming faster and relevant choices. Here organizations that leverage customer behavior insights are likely to outperform their peers by 85%, adding up to 25% into their profits. For instance, Netflix successfully predicted the popularity of its House of Cards, even before its launch. The OTT platform arrived at a conclusion by correlating customer behavior data sets around the popularity of the lead actor, the director, and the original British TV show.
Service response: Data and analytics platforms can ingest and collate the structured, semi-structured, or unstructured data from various sources. The Single Pane of Glass visibility allows the service line to understand the target audience's needs and respond with impact. For example, Dow Chemical leverages its business intelligence landscape to study and proactively identify pertinent pain points for its customers. The company pitches relevant solutions just in time (JIT) to deliver on their expectations. It maps its customers' consumption and value creation patterns using data and analytics to optimize its delivery practices.
Cognitive solutions: SEMRush says, 86% of CEOs consider AI to be a mainstream technology for their enterprise in 2021, and 79% of the executives feel that it will help them unlock efficiency. However, 93% of the automation engineers are still apprehensive about the challenges of the future. Indeed, the availability of high-quality data and analytics lies at the heart of disruptive AI and Machine learning technologies that can make innovation a reality. From complete service lifecycle automation, omni-channel customer experience delivery to deep personalization of offerings, they can help find answers to complex problems at the scale and speed of business.
Innovation at scale
The Gartner report recommends the CIO drive the necessary cohesion between the data and analytics and the innovation teams. It lays down a horizon of 90 days to make the DDI framework functional and orchestrate the desired outcomes. The scope should involve analytical modeling capabilities that can use data to construct models of complex situations and their feasible solutions. AI and ML can predict different scenarios and test them against the solution model to assess its business value. Once successful, the innovation can be amplified through a center of excellence (CoE) for its application in future initiatives.
Conclusion
While such an approach promises definite value for organizations, it can sometimes be overwhelming for companies with limited data and analytics bandwidth. Here partnering with a digital innovator like IGT can be a game-changer. IGT's Data and Analytics Practice combines a decade of experience, extensive domain knowledge, and proven technical caliber into objective offerings. It includes Strategy & Consulting, Customer Experience Analytics, Business Intelligence, AI/ML, and much more. With a repository of more than 100 ready-to-deploy use cases, IGT is well-positioned to bring data and analytics excellence at scale for businesses looking to innovate and grow amidst disruptions.
A single source of truth is a central and controlled source of data from which the entire organization can draw.
It is the master data.
When you lack such data and employee can pull down apparently the same metrics from disperse systems, unavoidably those systems will produce different numbers.
You get into a he-said-she-said situation, each player drawing and defending their position with their version of the ‘truth’.
Or even worse, some teams may naively leverage stale, low-quality, or otherwise incorrect data/metrics and make bad decisions, when they could have leveraged a better source.
