Having data is one thing, actually using it is another. Here’s a story how a German Retail Company started a project to cleanse and consolidate their data (sitting in multiple systems) using the SAP Cloud Platform to create a Golden Customer Record.
A recent Forbes survey reports that the number of enterprises with more than 100 terabytes of unstructured data has doubled since 2016 – but that only 32% of those companies have succeeded in analyzing that data in any actionable way. The volume and complexity of data overwhelms companies, which in turn are unable to correctly evaluate the output of their data. This eventually leads to many negative factors like higher TCO, increase of manual efforts related to daily business processes, losing credibility or taking wrong strategic decisions.
In this blog, I will steer clear of reciting definitions of what it means to turn data into competitive assets. Instead, I will focus on the real-life experience from an ongoing project undertaken by a certain German Fashion Retail Company aimed at getting a data-driven, 360 overview of their business.
Lack of data integration impedes business operations of the German Fashion Retail Company
The Company is using multiple ERP systems for different business processes or parts of them. Systems are not integrated and there is no central overview or consolidation of data from all systems. The Company is using unique systems, e.g. one for online shopping (listing their items at amazon, Zalando, etc.) and another one for brick and mortar stores. Those two systems are not connected, so the company is not able to verify if the same person who uses online shops also buys clothes in brick and mortar stores or vice versa. On top, the total number of the Company’s customers is skewed, because what they count as two people shopping in different places, in reality could be one and the same customer.
To sum it up, the Company doesn’t have a clear overview of their customers and therefore it struggles to create well-targeted marketing campaigns, article planning or build predictive analysis.
How SAP Cloud Platform (SCP) can help break down data silos and turn data into competitive assets
Since multiple production source systems are used, the first and most important step is to build a data lake where only required data is automatically collected from all sources. For this purpose, we decide to go with SAP HANA native on the SAP Cloud Platform.
The second step is to ensure real time replication of data from sources to SAP HANA on cloud (data lake). This step is covered by the SDI (SAP Smart Data Integration) feature. In this way, we connect various source systems like Futura (MSSQL), ProAlpha (ProgressDB), Salesforce (Cloud), CSV. files and many more.
The combination of SDI, SAP HANA native and SDQ (Smart data quality), which can be used as a service accessible from SCP, also enables the ETL process (extract, transform and load) which is crucial for the project because of poor quality of source data. The main goal is to upload only cleansed and harmonized data. In other words, multiple data transformations are activated during the extraction phase (before load into SAP HANA). Following examples can be achieved:
- Correct format of telephone numbers
- Cleansing, enhancing, checking existence of addresses
- Enhancing emails
- Parsing names into correct format
- Finding all duplicates based on multiple factors (Address, Mail, Person, Birthday, …)
Once all data is stored in the data lake in a correct, cleansed format, the last step is to use it for BI purposes. Here, multiple functionalities can be supported, for example – SAP Analytics Cloud, SAP Design Studio or Power BI. This is usually chosen based on required complexity of reporting which company wants to achieve.
Creating the Golden Customer Record that boosts business
By leveraging new technologies such as SAP Cloud Platform, the German Fashion Retail Company in now on a good way to building the Golden Customer Record with a clear, comprehensive and trustworthy overview about each of their customer. They will be able to precisely answer questions about who their customer is, what their shopping habits are, or how they prefer to be contacted. Now, the German Fashion Retail Company can use all this data for devising tailor-made marketing and sales activities all focused on one goal – increasing profit.