In this guest blog post Shamanth Shankar of Riversand explains why the next generation of Master Data Management (MDM) and Product Information Management (PIM) solutions must be deployed as cloud solutions.

As retailers grow, managing data across their application landscape becomes crucial. Business users and Information Technology (IT) leaders want to choose data management solutions that provide insights to them and provide relevant information to their customers along their purchasing life-cycle. Accommodating scale, speed and different data types requires that data management solutions evolve.

How are enterprises coping with scale and flexibility?

Enterprise software solutions are going through a revolution to accommodate scale and flexibility. Looking at the growth of AWS and Azure, one can imagine how aggressively enterprises are embracing cloud. AWS grew 54.9% year on year and Microsoft’s Azure grew  triple digits over the last five quarters. Cloud is growing at a 22% Compound Annual Growth Rate (CAGR), four times the rate of software spending growth. Flexibility in operating models (Operational Expense vs. Capital Expense), ease of implementation and cost savings lure business leaders towards the cloud. To strike a balance with the legacy of on premise solutions and cloud-based business friendly applications, enterprises will pursue a hybrid cloud model.

Cloud and Retailers

Compared to other verticals, retail has a lower barrier to adopting cloud. Cloud is expected to grow five-fold in retailing. Additional data points supporting this continued accelerated growth of cloud-based solutions, include;

• Digital commerce platforms are growing at 15% CAGR, driven by SaaS revenues.
• Non-Store retailers reported 12% year on year growth per the US Department of Commerce.

Retailers invest in various hybrid cloud-based solutions throughout their enterprise to providetheir consumers with personalized attention, constant engagement and better experiences.The central focus of this effort is to provide business users with a better user experience along with consistent data (especially product data) all with the goal of creating great experiences for consumers.

Product Information Management Solution

Synchronization of product data across applications and channels is critical to enterprises for improved efficiencies, faster new product introduction and higher sales. A Product Information Management (PIM) solution provides a single source of truth, high quality product content, global product taxonomies, aggregation and syndication with internal and external sources.

PIM solutions improve sales by providing the right product for the right customer at the right time, improve efficiencies by accelerating new product introduction, reduce supply chain costs and identify bottlenecks through better reporting. By connecting with data pools, vendor data, marketplaces, e-commerce platforms and Digital Asset Management solutions, PIM solutions connect to the entire application ecosystem and keep all the business users on the same page with “Trusted Product Data”. The foundation of this “Trusted Product Data” drives an enterprise towards data-driven and outcome based operations. In such an ecosystem, data models are defined, product data is mapped to marketplace structures, outcomes are measured and changes are accommodated on a periodic basis.

Transformation in Product Information Management

As retailers grow (organically or through acquisition), data models need to be changed, infrastructure needs to be expanded and global variations need to be consolidated into one solution. In addition to strategic topline growth, changing consumer choices, interactions and sentiments force business transformations.

Business leaders and IT leaders want to gain insights from their PIM solution and ensure they are providing relevant information to their customers. They expect a PIM solution to help them solve the following:

Assortment and Product Intelligence

Can they match the relevant assortment and products to the respective consumer segments, and understand  particular consumer’s sentiments?

Channel and Operational Intelligence

 How are the products performing on various channels and what impact does product data quality have on supply chain costs?

Competitive Intelligence

Does the competition differ by merchandising category?
How is the merchandise performing compared to the competition?

Both business and IT users are looking to accommodate this inward-looking information into their application ecosystem.

IT teams are finding it challenging to correlate external data with their internal data management practices. They are looking for cost effective technologies that can provide insights into underperforming product segments.

Merchandising teams curating product content have limited to nonexistent abilities to map or correlate product content to consumer segments, competitors, or sentiment via social channels.

Customer service teams are trying to analyze and draw insights from consumer and market segment analysis and marry them with category specific context.

Next Generation Solution

Current data management solutions need to evolve to manage increasing master data  and related expanding data pools at scale. These solutions will have to be based on hybrid technology frameworks involving SQL, NoSQL, Graph and persist both structured and unstructured data. To provide higher Return on Investment and lower Total Cost of Ownership to retailers, such solutions will need to be able to scale in or out with a pay-as-you-go model. Considering that enterprises will continue supporting on premise, private cloud and public cloud models, PIM solutions must provide all these capabilities both on premise and in the cloud.

Next Generation data management will bring global business complexities together into a single solution that is web-scale, dynamically configurable and offers the best user experience for both business and IT teams.

Shamanth Shankar supports business operations at Riversand. Till recently Shamanth led Marketing at Riversand. Prior to Riversand Shamanth consulted clients on Data & Analytics products, led S&OP at a manufacturing company and managed a Product Line at a public company. Shamanth holds degrees from Rice, Texa A&M and IIT Madras.