Why Integrated Workflow is Key to Being Data-driven
We live in a data-driven world. Reliable data can be turned into relevant insights that ultimately helps drive business decisions. However data does not magically become reliable. Information needs to be correlated, managed and blended together from a variety of sources, and despite the automation of Modern Data Management Platform as a Service, people are an essential part of the governance and validation process.
Workflow as part of business process management (BPM) is a critical component of both data management for IT and business execution. Last May, Gartner Announced that spending on Business Process Management suites would hit $2.7 Billion as organizations digitalize processes. We'll discuss custom workflows in the context of business execution in a later post, but let's explore the essential elements pre-integrated data governance workflow for a Modern Data Management platform, which includes the need to maintain reliable data via master data management (MDM) disciplines.
Data changes that drive business process decisions, such as market campaigns, sales opportunities, pricing discounts, compliance levels and support contracts, to name a few, are critical to the business, and changes to them require manual stewardship.
Traditional MDM tools have offered basic workflow within the framework of data stewards or IT, with extended capabilities and involvement of business users offered in either a custom build or ad hoc (e.g. sending requests via email with no return loop, feedback or status of request visibility) processes. Today's Modern Data Management platform provides out-of-the-box workflow processes at no additional charge, and because they are seamlessly integrated with both a new breed of data-driven applications, and existing process-driven apps like CRM, they can accept input and requests from frontline business users.
Data Change Requests (DCR)
Take the example of a DCR initiated by a sales rep during the course of their daily activities. The new information discovered, is entered in real-time, through the app on their mobile device. This can be either a new data-driven application seamlessly integrated with the Modern Data Management platform, or through their existing CRM application that they know and love.
These requests are prioritized and queued for data stewards to review, while the sales rep is kept up-to-date on their request. But that's only one way teams can collaborate on data.
Today, a Modern Data Management PaaS supports, through enterprise data-driven apps, all of the capabilities often seen in applications like Facebook, LinkedIn and Yelp. Including voting, ranking and rating, chat and discussion threads, even down to the attribute-level within a profile.
Custom Workflow Designs
Of course one-size never fits all. All out of-the-box workflows within a platform should be customizable, with visual editing and configuration of custom flows that meet an enterprise's governance framework and way of doing business.
Full Tracking and Traceability
It's goes without saying, but bears emphasizing that end-to-end traceability of any changes must be provided. Everyone in the enterprise, depending on their role and authority, should be able to see the status of requests, compare changes made at any point in time, and the complete authorization, workflow and approval chain that drove that request. As an added bonus, being able to compare changes at an attribute-level between any point-in-time is the ultimate goal.
Monitoring Productivity, Effectiveness and Closing the Loop
Data management is a continuous process, with limited resources and always more work than people available. The next generation of PaaS offers ongoing monitoring of governance and curation efforts. The data gathered helps inform an enterprise which areas can be improved, and can even offer gamefication options to make a tedious but necessary job fun and motivating.
Recommended or Autonomous Actions
With a myriad of ways teams within the enterprise can collaborate and govern data, they should expect the Modern Data Management platform to offer a little more assistance. Users should expect the platform to begin to learn, and have the smarts to provide recommended actions in the context of workflow to guide both business users and data stewards as to what to do next. Or to take action autonomously on their behalf.
That's it for my first post. I will be blogging more about this important topic soon. In the meantime I would love to hear from you if you have feedback or questions.
Mona Rakibe is a Principal Product Manager at Reltio. She's an expert in data management technologies with a specialty in content management and BPM, having worked for companies such as EMC, Oracle and BEA Systems.