Why are so many businesses drowning in data?

Today’s guest blogger is Sam Phipps, who is a supply chain blogger & marketing manager at Slimstock. As a supply chain blogger with a passion for inventory, Sam helps businesses to optimise their processes to boost availability, save cost and maximise customer satisfaction. In this article, Sam explores why ‘good’ master data is critical to supply chain success.

As the inventory expert, Tony Wild, once highlighted: “inventory is the physical consequence of missing data.”

But almost all businesses manage some form of master data. In fact, many organisations have an abundance of it. So, what’s the problem then?

Just because lots of data exists within a business, this does not mean that it is correct or complete. Furthermore, just because the data is in place, this doesn’t mean that master data is used effectively.

Every department within a business depends on good quality master data. However, in certain areas of business such as operations and supply chain management, poor data can quickly result in bad decisions that impact the entire organization.

Yet, around 50% of all businesses lack the core master data which are a pre-requisite for ‘good’ supply chain management. And even for the remaining 50%, master data is often seen as an area that could be improved upon.

Fundamental to supply chain success

In essence, supply chain master data includes all of the product and transactional information related to a given item. From determining logistics routes to setting up promotions, this information is used to make thousands of decisions.

But in the context of supply chain management, correct and reliable master data is an absolute must for satisfying customer demand. After all, the foundation of inventory and supply chain success revolves around two key questions:

  • When should you place an order?
  • How big should your order be?

To determine both of these points, we depend on several bits of key information. And, without this data, it would be impossible to know how much inventory you need to fulfil your customer’s demand.

To give a few examples, the supply chain master data typically encompasses the following areas:

  • Specific details about the product in question (size, SKU number)
  • Information about the supplier (lead times, MOQs)
  • Details about the current inventory position (location, inventory level)
  • Details about the customer
  • Information around the past demand
  • As well as many other key data elements

Driving long-term efficiency improvements

So far, we have only touched upon the basics: aligning supply with demand. However, this is just the start.

Through some fairly simple analysis techniques, master data can be used to explore new opportunities for optimisation.

For example, the first area we can review is the ABC analysis. By focusing on how each item contributes to the overall business goals (whether than be profitability, sales turnover or something else), management can use this to determine which (and how many) products the company should prioritise.

We could also carry out a so-called Incremental Margin Analysis, which provides management with insight into which products contribute positively to the net margin.

Furthermore, we could explore the Delivery Time Deviation Distribution. This is an instrument that the supply chain team can use to gain insight into the performance of suppliers.

Each of these analyses requires slightly different master data elements. The table below provides an overview of what data is required.


Master data is everyone’s problem

No business can afford to overlook master data. But who should be the owner of the master data in your business?  Should it be the IT, finance, operations, or even the management team?

This is a difficult question to ask. And many businesses don’t have a clear-cut answer. Although there is a technological process or system that the IT team need to support master data should be seen as a priority by everyone!

To read more about how you can optimise you supply chain master data, click here: https://www.slimstock.com/en/master-data/

MDM and SCM: Inside and outside the corporate walls

QuadrantIn my journey through the Master Data Management (MDM) landscape, I am currently working from a Supply Chain Management (SCM) perspective. SCM is very exciting as it connects the buy-side and the sell-side of a company. In that connection we will be able to understand some basic features of multi-domain MDM as touched in a recent post about the MDM ancestors called Customer Data Integration (CDI) and Product Information Management (PIM). The post is called CDI, PIM, MDM and Beyond.

MDM and SCM 1.0: Inside the corporate walls

Traditional Supply Chain Management deals with what goes on from when a product is received from a supplier, or vendor if you like, to it ends up at the customer.

In the distribution and retail world, the product physically usually stays the same, but from a data management perspective we struggle with having buying views and selling views on the data.

In the manufacturing world, we sees the products we are going to sell transforming from raw materials over semi-finished products to finished goods. One challenge here is when companies grow through acquisitions, then a given real world product might be seen as a raw material in one plant but a finished good in another plant.

Regardless of the position of our company in the ecosystem, we also have to deal with the buy side of products as machinery, spare parts, supplies and other goods, which stays in the company.

MDM and SCM 2.0: Outside the corporate walls

SCM 2.0 is often used to describe handling the extended supply chain that is a reality for many businesses today due to business process outsourcing and other ways of collaboration within ecosystems of manufacturers, distributors, retailers, end users and service providers.

From a master data management perspective the ways of handling supplier/vendor master data and customer master data here melts into handling business-partner master data or simply party master data.

For product master data there are huge opportunities in sharing most of these master data within the ecosystems. Usually you will do that in the cloud.

In such environments, we have to rethink our approach to data / information governance. This challenge was, with set out in cloud computing, examined by Andrew White of Gartner (the analyst firm) in a blog post called “Thoughts on The Gathering Storm: Information Governance in the Cloud”.

Three Stages of MDM Maturity

If you haven’t yet implemented a Master Data Management (MDM) solution you typically holds master data in dedicated solutions for Supply Chain Management (SCM), Enterprise Resource Planning (ERP), Customer Relation Management (CRM) and heaps of other solutions aimed at taking care of some part of your business depending on your particular industry.

MDM Stage 1
Multiple sources of truth

In this first stage some master data flows into these solutions from business partners in different ways, flows around between the solutions inside your IT landscape and flows out to business partners directly from the various solutions.

The big pain in this stage is that a given real world entity may be described very different when coming in, when used inside your IT landscape and when presented by you to the outside. Additionally it is hard to measure and improve data quality and there may be several different business processes doing the same thing in an alternative way.

The answer today is to implement a Master Data Management (MDM) solution. When doing that you in some degree may rearrange the way master data flows into your IT landscape, you move the emphasis on master data management from the SCM, ERP, CRM and other solutions to the MDM platform and orchestrate the internal flows differently and you are most often able to present a given real world entity in a consistent way to the outside.

MDM Stage 2
Striving for a single source of truth

In this second stage you have cured the pain of inconsistent presentation of a given real world entity and as a result of that you are in a much better position to measure and control data quality. But typically you haven’t gained much in operational efficiency.

You need to enter a third stage. MDM 3.0 so to speak. In this stage you extend your MDM solution to your business partners and take much more advantage of third party data providers.

MDM Stage 3
Single place of trust

The master data kept by any organization is in a large degree a description of real world entities that also is digitalized by business partners and third party data providers. Therefore there are huge opportunities for reengineering your business processes for master data collection and interactive sharing of master data with mutual benefits for you and your business partners. These opportunities are touched in the post MDM 3.0 Musings.

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Your Place or My Place?

We, and that’s including myself, often talk about multi-domain master data management as a marriage between party master data management (also called Customer Data Integration abbreviated as CDI) and Product Master Data Management (also called Product Information Management abbreviated as PIM).

The third most common master data domain is locations (or places). I like the term place, because then we have a P trinity: Parties, Products and Places. However there may be a fourth P involved, as I read a post today by Steven Jones of Capgemini telling that multi-domain MDM is a Pointless question.

The Premise of the Pointlessness is that Party and Product is an IT Perspective. The rest of the business sees the world from mainly either a customer centric perspective or a supply centric perspective.

I agree about that these perspectives exists too and actually made a blog post recently on sell side vs buy side master data quality.

I don’t agree about that this is an (pointless) IT versus business question, obviously also because I have a hard time recognizing the great divide between IT and business. From my perspective is IT a part of the business just like sales, marketing and purchase is it too. And from a product vendor perspective in the MDM realm you actually address the conjunction of business and technological needs a bit opposite to either being a database manager vendor aimed mostly at the IT part of business or a CRM or SCM vendor aimed mostly at the sales or purchase part of business.

Multi-domain MDM isn’t in my perspective a pointless place, but a meeting place between IT and all the other places in business and the core business entities being parties, products and places.

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