How a product data governance strategy can drive value for industrial distributors

If you’re in the industrial distribution game, your competitive advantage stands or falls on three attributes;

Operational excellence and agility
The quality of the experience you provide for customers and suppliers
Your perceived (and real) value in a rapidly changing operating environment

These aspirations are inextricably linked to the way you govern your data.

Bad (or no) governance

There is a surprisingly large number of distributors whose sins include;

This confusion is leaving many organisations like rabbits caught in the headlights of a rapidly approaching digital juggernaut.

First things first

We can’t overemphasise the value of a well-thought-out and strategically executed product data governance framework. The end point enhances the following;

The establishment, monitoring and maintenance of best practices and guiding principles for product data governance.
Execution of these processes coherently.
Consistent delivery on the aims of the framework.

As data volume increases and access needs scaling, achieving the above becomes more complex. That’s why it’s important to act with purpose to establish a suitable data governance strategy.

Successful product data governance:

In a nutshell, we can highlight certain key steps to successful product data governance;

And finally, Customer Support Services

It is well worth researching what features you expect before implementing PIM. Vendors may provide a range of out-of-the-box functionalities, while others only offer these features as custom add-ons. When buying licences, enquire about the customer support offered inclusive of the price per user. What channels do you get? Chat and automated online support, or a real person?

Roles & Responsibilities

Establish clear ownership, accountabilities & responsibilities for the product data domain

Business Rules & Metadata

Define business rules and metadata for product data attributes

Concepts & Business Terms

Establish concepts and business language for products & attributes across the organisation

Data Quality KPIs & Monitoring

Set data quality KPIs for attributes & monitor quality throughout the product lifecycle

Policies & Procedures

Define clear data distribution policies & procedures for product data management

Establish clear data ownership and responsibilities. A data governance council is the ultimate arbiter of this – involve people from across the entire organisation.
Define data distribution policies, including the roles and accountabilities of internal and external stakeholders.
Delegate data quality responsibilities to pin down data quality KPIs and how they integrate with the company’s overall business KPIs.
Homogenise labelling and quality criteria to optimise strategic planning.
Document data lineage and access controls to ensure data security and regulatory compliance.

You want to base your business decisions on reliable, trustworthy data, fully aligned with how, what and why you use your data asset. That means optimal procedures for product data ingestion. A well-grounded process model should establish the linkage among:

The culture of the organisation: how decisions are made, how groups work together and who is involved.

The operating model: does it fit with the business activity/model? This could mean a centralised, decentralised or hybrid model.

The people: what’s essential for data governance is clear and committed leadership, ownership and accountability for processes and procedures and the involvement of personnel from all areas of the organisation – this is a holistic framework, not the exclusive domain of product managers or the I.T. department.

Good decisions made on bad data are just bad decisions you don’t know about yet!

Scott Taylor (AKA The Data Whisperer)

Astute operating principles

Added value data governance should demonstrate the following qualities;

Fundamental guiding principles – not just lip service, but to be referred to consulted and adhered to. These also act as SOPs in that if discrepancies arise, there is a set of principles to refer to.

Representation and active involvement of all areas of the business – not just the technological infrastructure support but any area of the business impacted by the success or failure of product data management. Organisation-wide buy-in is essential.

Frequent interaction and communication –digitisation is becoming a necessity, not a vague aspiration, so constant consultation, decision-making and oversight is a must. That way, standards remain high, consistent and reliable and drive value throughout the organisation.

Ownership, leadership, responsibility and accountability – these values can be mere abstractions if everyone talks the talk, but no-one is walking the walk. Throughout the reporting line of the company (up to executive management level) these are the living operating system of the product data governance model.

Clarity of roles and responsibilities – from top to bottom of the chain of command, you need a Chief Data Officer alongside data owners, stewards, custodians, strategists and analysts.

A governance committee: adherence to and respect for these assignments is critical to the operational and strategic success of the business. As such, you need to give these values priority, so everyone understands and buys into their importance.

Get the above right and you are bound to drive value in your business processes, including the ingestion, management and enriching of your product data assets. Most importantly, though, it adds value for your customers and their customer experience. After all, you need to demonstrate your tangible value if they’re going to choose you over your competitors.