The nature of the supply chain is just one aspect of a data & analytics solution. The other aspect is where the solution is being utilized. The user and the layer are key deciders when it concerns the purpose of data and the lever for the outcome. Being one of the most advanced technologies as far as ‘Digital Transformation’ is concerned, it makes data & analytics an accelerator for the adoption of other technologies by acting not only as a multiplier within the transformation blueprint but also through an organization-wide presence. Data & Analytics can be utilized at every layer of the organization and across stakeholders for different purposes:
- Environment: The environment in which the overall technology stack sits is probably one of the most important aspects to drive overall organizational performance, and data & analytics facilitate scalability and performance
- Business Process and Applications: Organizations are continuously looking for ways to improve their business processes and applications efficacy
- Business Intelligence & Analytics: Business decisions are based on insights and insights are not only based on data but how it is processed, packaged, and presented which emphasizes the need for the right talent to process, package, and present the right insight to drive business decisions
- Customer Experience: Data holds the key for the customer when it concerns the interaction with the organization, thereby significantly affecting the stakeholder experience
As it might be observed in the product cycle for most of the new-age technologies, an overall IT/BPO transformation deal is more likely to have these technologies as parts of the overall transformation blueprint. Stand-alone deals are more likely to positively correlate to the maturity of the particular technology. The aggrieve push by service providers to mine existing accounts, especially when it concerns stand-alone deals, reflects the maturity of the market. Another aspect that is atypical for Data & Analytics is that the major revenue chunk lies in the FTE-based commercials rather than a fixed cost or outcome-based model. Data & Analytics has nearly reached its ultimate potential, and therefore, we expect a majority of the organization to have developed their own data, analytics, and insights capability. However, it simultaneously lacks the talent required for skills across both traditional and collapsed supply chains.