Defining Data Readiness Process
- Mike Deskis
Before we can understand the processes performed by an IE, we first need to understand the use of the Data Readiness methodology and practice within Pricefx.
Data is such an essential component to the successful implementation of a pricing solution that Pricefx has established a Data Readiness Process to help our customers prepare for the start of their pricing project. The Pricefx Data Readiness Process encompasses the identification of essential data, the assurance of quality data, and the timely availability of both. By following this process, projects experience fewer delays and realize a faster time-to-value.
If you partner with Pricefx for your pricing solution, you will work from the onset with a dedicated Pricefx Data Readiness Manager (DRM) to prepare your data for the launch of your project. The DRM will guide you through key activities to help you identify the required data, ensure the quality of the data, and make the data available for the project team. When the data is “ready”, the configuration of your pricing solution will begin.
We present how we define Data Readiness, provides a high-level overview of our Data Readiness process, and recommends activities that can be started now to get you going on your data readiness journey.
Data Readiness Defined
What is it that makes the data “ready” to be used as part of a pricing solution implementation? We consider Data Readiness to be composed of three primary components as illustrated by this formula:
Data Readiness = Data Identification + Data Quality + Data Availability
Data Identification
The Product, Customer, and Transaction data, often referred to as the Master Data, are most critical to pricing setting, analytics, and related processes. Each can have a variety of attributes and relationships that are crucial to pricing processes. Working together, we help to identify the sources of this data by pinpointing the owners of the data along with associated business processes and systems. From here, we focus on mapping the data from the source systems to the Pricefx system. All required data transformations will also be identified as part of this readiness component.
On our journey to performing data identification we are presented with an important fact, a premise and a reoccurring myth:
Data Quality
Data loaded into Pricefx must be of “high quality” to successfully configure the solution and produce valuable, actionable results. During this part of the process, we focus on the characteristics and rules associated with each data attribute, all guided by a Seven-tier Data Quality Framework. We will use automated processes to check the condition of the data in a staging area before transforming and loading it into Pricefx.
Data quality means defining what data success is:
A pivotal need will be to identify the meaning of data quality:
Data Availability
Successful pricing solution implementations require high-quality, representative data available right from the beginning of the configuration effort. We work with you to establish a realistic timeline for when this data will be available and will align this with the overall project timeline. Progress is tracked using our Jira project management system in a manner that makes it easy to determine when the data is ready for the configuration to begin.
To have a better understanding of data availability, we need to recognize another recurring myth and the goal of our process.
The goal of a data integration process is the resolve the issue presented by data silos.