As retailers grow managing data across their application landscape becomes central. Business users and Information Technology (IT) leaders want to choose Data Management Solutions which provide insights to them and provide relevant information to their customers along their purchasing lifecycle. Accommodating scale, speed and different data types requires Data Management Solutions to evolve.

1. Howareenterprisescopingwithscaleandflexibility?
CloudandRetailers
ProductInformationManagementSolution
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Bringing Global Complexities to
Cloud-based MDM/PIM Solutions
As retailers grow managing data across their application landscape becomes central. Business users and
Information Technology (IT) leaders want to choose Data Management Solutions which provide insights to them
and provide relevant information to their customers along their purchasing lifecycle. Accommodating scale, speed
and different data types requires Data Management Solutions to evolve.
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 is
growth in triple digit over the last five quarters. Cloud is growing at the rate of 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 on premise
solutions and Cloud based business friendly application, enterprises will pursue a hybrid cloud
model.
Synchronization of product data across applications and channels is critical for enterprises for
improved efficiencies, faster new product introduction and higher sales. A Product Information
Management (PIM) solution provides single source of truth, high quality of product content,
global product taxonomies, aggregation and syndication with internal and external sources.
Compared to other verticals, retail has a lower barrier to adopting cloud. Cloud is expected to
grow five-fold in retailing. Couple of other data points which bolster this continued accelerated
growth of cloud-based solutions
Digital commerce platform is 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 provide
their consumers with personalized attention, constant engagement and better experience. The
central focus of in this application landscape is to provide their customers with better
experience and their business users with better user experience along with consistent data, in
particularly when it comes to product data.
SUPPLY
SELL

2. PIM solutions improve sales by providing the right product for the right customer at the right time, improves
efficiencies by accelerating new product introduction, reduces supply chain costs and identifies bottlenecks
through better reporting. By connecting with data pools, vendor data, marketplaces, eCommerce 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”.
NextGenerationSolution
TransformationinProductInformationManagement
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To accommodate these master and related data, the current Data Management solutions need to evolve to handle
volume, velocity and variety. These solutions will have to be based on hybrid technology framework involving
SQL, NoSQL, Graph and persist both structured and unstructured data. To provide higher Return of Investment
and lower Total Cost of Ownership to the retailers, such solutions will need to be able to scale in or out with a pay
as go model. Also considering that enterprises will have to continue supporting on premise, private cloud and
public cloud models, PIM solutions have to provide all these capabilities both on premise and on the cloud.
Next Generation Data Management Solutions will bring global business complexities under one solution that is
web-scale, dynamically configurable and offers the best user experience.
Business users and IT users are looking to accommodate this outside-in looking information into their application
ecosystem.
IT teams are finding it challenging to correlate external data to the data management practices internally. They
are looking towards technologies that can provide weighted focus on the right segment of products resulting in
either running out of money or exorbitant costs of data management making it unsustainable.
Merchandising teams curating product content have limited or nonexistent abilities to map or correlate product
content to customer segments, competitors, or sentiment via social channels. Customer Service teams are trying
to analyze and draw insights from customer and market segment analysis and marry them with category specific
context.
As retailers grow (organically or through acquisition), data models needs 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 the PIM solutions and ensure they are providing
relevant information to their customers. They are expecting PIM solutions to help them solve the following:
Assortment and Product Intelligence:
Do they have the relevant assortment and products to the respective consumer
segments and what are the consumer’s sentiments?
Channel and Operational Intelligence:
How are the products performing on various channels and what’s the impact of
product data quality on the supply chain costs?
Competitive Intelligence:
Is the competition different by merchandising category, and how is the
merchandise performing compared to the competition?
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.