As a subject all by itself, data governance tends to make readers doze off to sleep. It’s a business enabler, which means data governance is best looked at through the customer view. A good example of this is selling cars to consumers, which has changed a lot over the years. 75% of car buyers now use the web to research their purchase, according to Auto Trader. Car buyers want to know everything before walking into a showroom, especially when buying an electric car: what’s the range on a full charge? How’s the maintenance contract? Is there a private lease option? Can I lease the battery? Gone are the days of buying a car merely based on its looks or brand prestige.
Like with many other products, the buying process of cars is moving online. This requires all the product information in which consumers are interested to be available online, searchable and comparable. Consumers today expect 24/7 service, real-time information and transparency on prices and product availability, as well as superior store and mobile apps, according to PwC’s Global Total Retail Survey. Companies that struggle to meet these consumer expectations will simply lose the customer’s attention and with it the business. The first line of business in the supply chain to face these current consumer demands is retail.
The Key to Creating the Omnichannel Experience
One of the biggest goals for retailers today is to create an optimal customer experience that is seamless across all channels. Simply engaging with customers across different channels is not enough; the information and interaction across the channels also need to be continuously aligned. This means the various channels need to exchange essential data in real-time to keep the customer conversation going and relevant. Consistent data across channels is essential to creating the omnichannel customer experience that consumers crave today. The starting point for retailers looking to embrace omnichannel is considering the way they manage their data for products and customers.
This starting point becomes immediately apparent when retailers consider becoming active on a marketplace like Amazon. To benefit from its vast sales potential, retailers need to supply quality product information, including categories, images, FAQs and additional product information that enables product filtering on Amazon. For example, is the product blue, dark blue or navy blue? This matters for the filter options, and consequently, for your marketplace success.
The second data domain that retailers need to master is customer data. The first set of data to consider is data that describes your customer relationships. By using the RFM model that is based on the recency, frequency and monetary value of a customer relationship, you can determine if a customer is new, loyal or even VIP. The recency tells you who to approach to prevent losing them as customers. And that’s only the start. Every customer interaction with your product data creates new customer data. By capturing and processing these digital footprints, retailers can determine where in the customer journey a customer is and match that with relevant content. This creates more customer value and therefore, more revenue.
Improving Supply Chain Operations and Meeting Changing Consumer Demands
Further down the supply chain, wholesalers play a vital role in managing product data. Working with correct product data like size and weight enables efficient logistics and improves supply chain operations. This, in turn, affects manufacturers and retailers, especially in the food and beverages industry. Consider, for example, the impact of a product recall with and without data on the product’s origin and manufacturing process. When you can pinpoint exactly in the process where something went wrong, you only need to recall a small number of products and not the full batch.
Quality product information in the supply chain also allows for meeting new consumer demands on sustainability and accountability. Brands working with Asian sweatshops, pension funds investing in oil & gas and fashion retailers using forced labor are currently feeling the pressure to comply with the new consumer paradigm. Consumers want brands that do good. And that means they want more information on the background and context in which products are made and services are provided. On the other hand, having full data insight also brings opportunities. When geopolitical developments endanger the availability of certain parts or products, for example, you can switch much faster to alternatives.
Data as a Product for Manufacturers
At the beginning of the supply chain, manufacturers are very much aware of the demand for quality product data. Governments, retailers, wholesalers and consumers are demanding more, better and richer data. In France for example, the materials of the packaging such as carton and Styrofoam are soon required to be listed. Information on the C02 produced during production, like the product carbon footprint label, is becoming an important tool for countries aiming to reduce their C02 footprint.
For consumers, two other trends have been pushing the demand for quality product content. Selling directly to consumers, known as direct-to-consumer (D2C), and the digitization of products. Manufacturers selling their products to end customers face new challenges such as increased competition, product differentiation and personalization. Utilizing product data and customer data is paramount to overcoming these obstacles. The digitization of products means adding digital capabilities to physical products so that consumers can interact with the product and get information in digital format.
Data is the Key Enabler for the Whole Supply Chain
From retailers to wholesalers to manufacturers, mastering data benefits the whole supply chain. Once the business side is clear, you can start looking at how to organize the processes needed to create high-quality data that is accurate, complete, consistent and reliable. This is called data governance, and encompasses a collection of processes, roles, policies, standards and metrics for the efficient and effective use of information, allowing an organization to reach its goals. When you work to improve the data quality within the whole supply chain, everyone benefits.
This is the third blog of our article series on Data Governance. Click here for the next article.