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Deriving tangible business outcomes for retail analytics investments


Deriving tangible business outcomes for retail analytics investments

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Each and every Retail business is at multiple levels of maturity with regard to leveraging their data assets for customer acquisition, customer experience and operational efficiency. However, a future-proof retail analytics ecosystem is needed to address the following challenges (boldfaced) with the adjoining solutions:

Absence of a data foundation for analytics – Delivering actionable insights across the enterprise is the key goal, but the ability to integrate packaged and homegrown data sources for a single view of it, needs to be honed. This can be done with having a resolute data foundation for retail analytics replete with good data governance, data cleansing processes and ultimately, optimal data quality in place.

Intangible business impact – Ongoing result-oriented data initiatives need to be dealt with continuously at a revenue oroperational metrics level, by laying emphasis on a sincere approach to reduce time-to-value complexities – the resultant effect being an upsurge in the ability to boost business and create a tangible impact, with the help of robust data analysis methods.

Dearth of re-usable assets – Successful AI/ML implementations in Retail mandates a plethora of re-usable assets that can prove to be powerful inside-out, with adequate availability. However, the life-breath of aggregating these re-usable assets is to ensure that even with the best of what is available, a sense of totality in incorporating the implementations can have a total reach as well.

Cognizance of Sub-vertical specifics – Data Analytics across grocery/fashion/apparel/cpg, etc. have intrinsic variations which need to be factored in for best outcomes when implementing Retail analytics. These(outcomes) help in monitoring these sub-verticals which herald a dynamic environment that are specific to them.For eg., heightened predictability of consumer behavior, that is a direct outcome of Retail analytics, helps reduce inventory and opportunity costs for grocery retail. Similarly for fashion retail, predictive analytics is used to analyze Sales against demand and supply.

In lieu of the above, it necessitates that retail organizations looking to maximize their RoI from analytics investments, need to :

  • Focus on a collaborative and consultative approach between their business, IT and partner ecosystem Ensure data initiatives are phased and aligned to existing organizational and data maturity
  • Implement a continuous delivery model with intermittent, measurable outcomes rather than a big-bang approach
  • Leverage re-usable assets in terms of pre-built tested algorithms, data models and plug-n-play vertical specific tools for rapid iterations and validations

Data and analytics is inarguably the single most impacting factor driving differentiation and growth for Retail organizations. It’s no more a luxury but a necessity to have a strategic and business driven outlook in the analytics journey with short and long-term business objectives. At the same time, deriving RoI intermittently is key to justify investments and build on top of a sustainable data foundation.

Business outcomes for Data & Analytics investments are correlated to:

  • Time to value – Are you seeing impact soon enough or is it still a vision without tangible outcomes?
  • Addressing business nuances – Are you analyzing factors with specifics of your business/as-is maturity and not just what is prevalent in the industry as a whole?
  • Commitment to the cause – Is the organization committed to the data analytics journey in terms of investments, skills and timeframe to move up the analytics value chain?
  • Partnering for the cause – Analytics is not the focus of a Retail Company, but your business is. It’s important to identify the right partner to provide the requisite thought leadership and walk with you on the journey. Do you have the right partner?​

We at Sonata Software are helping retail enterprises globally with retail analytics plug-n-play tools (Retina) , re-usable assets for AI/ML driven business use cases and helping build a future proof, sustainable foundation to their data-driven digital transformation journey.

Click here for you to learn more.