Sell more. Reduce costs.

Business outcome is the end goal of any data management activity may that be data governance, data quality management, Master Data Management (MDM) and Product Information Management (PIM).

Business outcome comes from selling more and reducing costs.

At Product Data Lake we have a simple scheme for achieving business outcome through selling more goods and reducing costs of sharing product information between trading partners in business ecosystems:

Sell more Reduce costs

Neutron Star Collision and Data Quality

The scientific news of the day is the observed collision of two neutron stars resulting in gravitational waves, an extremely bright flash – and gold.

The connection between gravitational waves and Master Data Management (MDM) was celebrated here on the blog when those waves were detected for the first time as told in the post Gravitational Waves in the MDM World.

The ties to Product Information Management (PIM) was examined in the post Gravitational Collapse in the PIM Space.

Now we have seen a bright flash resembling what happens when two trading partners collide, as in makes business together encompassing sharing master data and product information. Seen from my telescope this improves data quality and thereby business outcome (gold, you know) as explained in the post Data Quality and Business Outcome.

Neutron Star Collide

Using Pull or Push to Get to the Next Level in Product Information Management

The importance of having a viable Product Information Management (PIM) solution has become well understood for companies who participates in supply chains.

The next step towards excellence in PIM is to handle product information in close collaboration with your trading partners. Product Data Lake is the solution for that. Here upstream providers of product information (manufacturers and upstream distributors) and downstream receivers of product information (downstream distributors and retailers) connect their choice of in-house PIM solution or other product master data solution as PLM (Product Lifecycle Management) or ERP.

Read more about that in the post What a PIM-2-PIM Solution Looks Like.

The principle behind Product Data Lake is inspired by how a data lake differs from a traditional data warehouse. In a data lake the linking and transformation takes place late, when the data is consumed by the receiver.

pdl-diagram-new

Product Data Lake resembles a social network as you connect with your trading partners from the real world in order to collaborate on getting complete and accurate product data from the manufacturer to the point-of-sales:

  • Pull-PushAs a downstream receiver, you can be on the winning side by utilizing our Product Data Pull service
  • As an upstream provider, you can be on the winning side by utilizing our Product Data Push service

To the Cloud and Beyond

Over at the Informatica blog Joe McKendrick recently wrote about When It’s Time to Give Data Warehouse a Digital Makeover.

In here Joe examines how data warehouses can be modernized to augment architectures supporting data lakes and Mater Data Management and the case for moving data warehouses to the cloud.

In my view, a lot of data management disciplines will eventually move to the cloud as one follows the other. By adding “beyond” I suggest, that cloud solutions will not only be something that is supported company by company. Eventually you will be able to get business outcome by sharing data management burdens within your business ecosystem.

My current venture called Product Data Lake is an example of such a solution. It modernizes the data warehouse thinking within product information sharing by using a data lake concept in the cloud ready-to-use by trading partners within business ecosystems:

  • If you are a provider of product information, typically as a manufacturer of goods, you can harvest your business outcome by using us for Product Data Push
  • If you are a receiver of product information, you can harvest your business outcome by using us for Product Data Pull

pdl-top

Data Quality and Business Outcome

take-2The connection between MDM (Master Data Management) and business outcome was discussed on this blog in the previous post called MDM, Reltio, Gartner and Business Outcome.

Now, MDM and Data Quality are closely connected disciplines. So, it was interesting to read today’s post on the Experian Data Quality UK blog, where James Marrable states this: Want to improve performance? Improve your data.

In his section around improving data James, among other things, suggests asking this question: “Do you have other data sources you can bring in to support the data you have?”

This is a key question to me and in my eyes a very important mean to make your data bring business outcome. Applying second party and third party data can increase the potential value of your first party data in these ways:

  • Utilizing third party data to compile complete, accurate and timely party data assets needed for understanding and connecting with customers.
  • Receive second party data to compile complete, accurate and timely product information.
  • Having a holistic view of internal and external data needed for decision making.

Hereby you will sell more, reduce costs and mitigate risks.

MDM, Reltio, Gartner and Business Outcome

A recent well commented blog post by Andrew White of Gartner, the analyst firm, debates What’s Happening in Master Data Management (MDM) Land?

The post is an answer to a much liked and commented LinkedIn status post by Ramon Chen, Chief Product Officer of Reltio.

In his post Andrew connects the classic dots: How does technology lead to business outcome? Especially the use of cloud solutions and the multi-tenant aspect is in the focus. Andrew asks: What do you see “out there”?

My view is that multi-tenant is not just about offering the same subscription based cloud solutions to a range of clients. It is about making clients sharing the same business ecosystem work in the same MDM realm. This is the platform described in Master Data Share.

Gartner Digital Platforms 2
Source: Gartner

Oh, and what does that have to do with business outcome? A lot. Organizations will not win the future the race by optimizing there inhouse MDM capabilities alone. With the rise of digitalization, they need to connect with and understand their customers, which I believe is something Reltio is good at. Furthermore, organisations need to be much better at working with their business partners in a modern way, including at the master data level. The business outcome of this is:

  • Having complete, accurate and timely data assets needed for understanding and connecting with customers. You will sell more.
  • Having a fast and seamless flow of data assets, not at least product information, to and from your trading partners. You will reduce costs.
  • Having a holistic view of internal and external data needed for decision making. You will mitigate risks.

Merchants vs Manufacturers in the Information Age

Merchants sells the goods produced by manufacturers. In that game merchants and manufacturers are basically allies. Then of course the merchant’s profit may depend on the margin he can get between the manufacturers price to him and the merchant’s price to his customer. In that game, merchants and manufacturers are kind of enemies.

When it comes to providing product information to the end customers, merchants and manufacturers are allies too. The more complete product information placed in front of the end customer, the better. This is increasingly important today with more and more goods sold in self-service scenarios as in ecommerce.

standoffBut again, there seems to be an enemy angle here too. Who should have the burden of lifting product information as the manufacturers have it to the way it is presented at the point-of-sales provided by the merchant? Often this seems to be stalled in a standoff as described in the post Passive vs Active Product Information Exchange.

At Product Data Lake we offer merchants and manufacturers an honorable way out of this standoff: