February 28, 2020 
The industrial landscape is being reshaped quite rapidly with the introduction of new technological trends and advancements. With a considerable technical influence, the retail industry is no exception!
The paradigm shift of the retail industry from conventional brick-and-mortar stores to establishing a digital presence through online eCommerce platforms is quite evident.
While technological changes are gaining ground, today’s customers are more attuned towards the latest trends. Gone are the days where shoppers used to navigate between offline stores for a long shopping spree.
Now, the product browsing has evolved by a notch as today’s tech-savvy customers have resorted to mobile browsing, eCommerce apps, and other such relevant platforms.
Significance of Data for Retail Industry
Several researches and studies have reinstated the fact that mobile will continue to remain the go-to device when it comes to retail decision making. At the same time, brands and businesses have to buck up their retail games by planning to deliver automated, seamless and personalized experiences for their target customer base.
With social media platforms such as Instagram evolving as key contributors for higher online sales, retail brands must plan to leverage them optimally.
Data has always been the backbone for retail brands in their decision-making process, strategic or otherwise. Data-driven insights are crucial for retail brands to gather customer-centric information, identify opportunities for customer acquisition, engagement and retention as well as enhance their supply chain management efficiency.
However, with business scalability and globalization and product content being available online across several platforms, managing data both in terms of volume and variety becomes challenging. Now, let’s have a quick peek into the major data governance challenges pertaining to the retail industry.
Major Data-related Challenges in Retail
1. Multiple Touchpoints
The buyer journey involves multiple stages and stage-specific data are being captured by multiple interfaces within the retail ecosystem. It would be fair to say that the data are interlinked and have a chain effect. For instance, the data governance team needs to have a holistic and unified view of data pertaining to the customer purchase order, available inventory, order shipping details, etc.
However, as we can see these data are interlinked and need to be updated seamlessly over time. However, with multiple teams being responsible for updating the data, there are often scenarios of data silos or obsolete and irrelevant data.
Solution
A robust, efficient and centralized data governance system will ensure the apt management of the distributed data across the retail ecosystem. It ensures that the retail data stays relevant, up-to-date and consistent across multiple platforms.
Data silos can be effectively addressed as the data governance system ensures the real-time updates of data. Retailers have higher visibility on the relevant aspects of their operations that in turn boosts their omnichannel retail and marketing strategy.
2. Redundant Data Points
In the conventional retail scenario, there are usually multiple data repositories and warehouses, often scattered across multiple levels or departments in the retail arena. As most of these data repositories are offline, changes made to data in one might not be actually reflected in the other one until and unless this is specifically being pointed out.
It leads to data inconsistency and inaccurate data has a substantial negative impact on the retail strategy and eventually the performance. It also adds up to data processing, curation efforts by the concerned team members and is often a time-consuming and rather futile effort.
Solution
Though addressing the data inconsistency may seem daunting and far-fetched, a data governance system is an absolute solution. Data pipelines can help in data gathering, curation, modification as well as thorough validation of raw data. This not only enables greater data visualization but also makes data analysis easy, accurate and quick.
With data governance systems in place, retailers can amp up their merchandising tactics, share time-sensitive offer-related information with the customers that are sure to generate more sales and revenue.
3. Data Exposure
For the seamless functioning of retail activities, sharing of relevant data among the concerned stakeholders such as vendors, third-party entities are common. While data accessibility is inevitable, it also opens up challenges concerning the safety and security of retail and customer data. Though IoT and other technological advancements have been a boon, it also poses substantial security threats for retail-specific data.
Unauthorized access to customer data may cost retailers massively as it has reverse and drastic impact on brand-customer trust and relationship. Apart from losing out on customers, the damage may run deeper as retailers might have to deal with operational inefficiencies, roadblocks, lost sales opportunities.
Solution
Now, how can retailers limit the accessibility of sensitive retail data? An all-encompassing data governance application is the response! Most of the data governance systems usually have data encryption, two-factor authentication and tokenization feature in-built.
These features are crucial in ensuring high-level security of sensitive information despite several challenges and security threats.
Data Governance Best Practices
Set the Operational Model Right from the Start
Like other business functions, data governance function is also should be managed by the concerned team. Thus, it is crucial to define the roles and responsibilities of each member associated with the data governance program. Setting out SMART objectives, outlining definitive roles will go a long way in socializing the data governance program and ensure their success.
Data Domain Identification & Segregation
Businesses need to understand the nature of a data governance program as it is merely not a technical tool or application. It is rather a combination of people, process, and technology. The key stakeholders, business processes, datasets related to the customer domains should be identified as some of the key courses of action.
Adhere to Industry-trusted Security Practices
Despite ideal situations and precautionary measures being taken, threats to data privacy and security are inevitable. When businesses are planning to proceed full-throttle on their data governance programs, security measures must be their first priority. Accessibility to sensitive data should be protected with encryption and tokenization capabilities offered by most data governance applications.
For further insights into data governance, turn to the experts at Vinculum today.
