If you want your data to work for you, it’s important to make sure that you’re using it in the right way. While it’s becoming easier to collect data, the insights that you find are all about the model you are using them with.

This blog will look at how you can improve your store using data, using the diaper-beer model as an example

The Diaper-Beer Model

A legendary story from 30 years ago illustrates the value that data can bring to modern storefronts. Back in 1992, a group of consultants supporting a Midwest retailer found an interesting correlation between diaper and beer sales. The company cross-referenced sales data and store layout to generate unique insights, helping identify items that were often purchased together.

After digging deeper, the consulting team hypothesized that when men went shopping for diapers on weekend evenings, they often bought beer as well. This finding prompted the retailer to change the store layout so that the beer and diaper aisles were next to each other—leading to higher sales in both categories.

Though there are some skeptics of the diaper-beer model, the case study is a useful example of predictive analytics at work. The consulting team was able to sift through client data, uncover actionable insights and then make an informed decision that led to positive business outcomes.

The modern storefront is completely digital. It’s a company’s website and application. These new stores and digital aisles are generating an insane amount of data. To modernize the diaper-beer model, organizations can use a data lake to not only house all this unstructured data but also the tools necessary to generate insights on their data at an unprecedented scale. [source: Forbes]

It’s important to know when to look for patterns within your data, this way you can help guide consumers and encourage them to buy different products. It’s always a great idea to try and A/B test a few options and then compare them afterward. If you take a look at the famous diaper beer model, it’s good to make sure that your team is willing to constantly collect large amounts of data. This case story sparked conversations around predictive analytics.

The post The Diaper-Beer Model – Value-driven by Predictive Analytics appeared first on Sagar Nikam.

Business can be summed up as a human process of making, selling, and delivering a product or a service. Enterprise data strategy is very important to the success of any enterprise. Enterprise data strategy is to implement a uniform approach to the management of data throughout the enterprise.

It is to ensure a standard data platform that allows you to grasp an enterprise’s entire information flow. It is to use the same standards and data definitions throughout the organization so all departments can work with the same platform.

Data governance (DG) is the process of managing the availability, usability, integrity, and security of the data in enterprise systems, based on internal data standards and policies that also control data usage. Effective data governance ensures that data is consistent and trustworthy and doesn’t get misused. – from Techtarget

Some of the benefits of this are

1. Golden Source of Data – A centralized data storage to be used for all the reporting and analytics purposes. Avoiding the data risk, errors and saving times required for reconciliation of numbers from different report.
2. Rich Meta Data – Unified data attributes and definitions help to maintain rich metadata and logic. This reduces the risk of misinterpretation of data and in turn risky or wrong decision making
3. Security – This also help to implement a standardized Data Security and Data Risk management to ensure data security. Customer personal information can be stored centrally to ensure GDPR followed across all the platforms.
4. Enhanced and Standardized process – It helps to ensure standardization of processes across organizations to ensure accuracy of data
5. Data Quality – THis provide a chance to implement centralized Data Quality Framework across organization
6. Advanced Analytics – Centralized data helps to create a single view of customers, understanding interaction on different platforms and with different products. It helps to apply advanced analytics and machine learning model like building the Customer Propensity Model.

Having a data strategy is an important component of any business. It will allow you to take your company to the next level by ensuring that every department is running smoothly and efficiently. It also promotes a culture of Data-Informed decision-making across organizations. This will help you to streamline your business processes and data management.

Feel free to connect with me on LinkedIn to discuss this further – Sagar Nikam

The post Why would a consistent Enterprise Data Strategy be important in business? appeared first on Sagar Nikam.