May 17, 2020

Importance of multi-domain Master Data Management, by Stibo Systems

Supply Chain Digital
Supply Chain
supply chain news
Freddie Pierce
5 min
The single silo approach will not be able to cope
Written byBy Mikael Lyngsø (pictured, right), Chief Executive Officer of Stibo Systems Many organisations hold their business data in silos wit...

Written by By Mikael Lyngsø (pictured, right), Chief Executive Officer of Stibo Systems

Mikael Lyngso stibo systems.jpg

Many organisations hold their business data in silos within individual departments but, as revealed in research we carried out recently, there is a growing appreciation among businesses of the need for Master Data Management strategies.

Master Data Management, or MDM, is based on the principle of making a company’s data available and accessible to all of the systems and people that need it.

Traditionally, the majority of MDM initiatives have been based around a single master data domain, such as product or customer data, although many businesses are now broadening their horizons to include a number of domains.

But, according to Forrester, while nearly half of MDM professionals state that they have at least three domains requiring an MDM strategy, only 9 percent are actually using an MDM solution that focuses on two or more domains.

Indeed, a report from Gartner suggests that, by 2014, two-thirds of Fortune 1,000 organisations will have deployed two or more single-domain MDM solutions to provide support for their enterprise-wide MDM strategies.

The needs of the many outweigh the needs of the few

While businesses may make use of two or three different data domains, most organisations will experience greater issues from one domain over another. Smaller businesses in particular will only want or need to master this one particular domain before moving on to others.

As these businesses grow though, so will the number of data domains presenting challenges that need to be addressed, with each domain perhaps requiring its own unique information management solution. 

However, the implementation of these single-domain MDM platforms can potentially cost businesses almost twice as much as just one multi-domain MDM solution. They can also significantly reduce the opportunities for company-wide integration of data, making issues around the governance, quality and enrichment of data more complicated.

It appears clear then that, in the longer term, deploying a uniform multi-domain MDM platform is a logical solution to all of these issues, not least that of cost. After all, it would seem sensible to purchase one solution, rather than many, to manage the ever growing list of domains of data that pass through the various functions of a business.

Looking beyond costs alone, it’s also worth considering the logistics of using a uniform single-domain MDM platform. Sales teams, for example, may require access to customer data as well product data in order to provide better insight, and enabling them to provide better services and maybe offer products their customers weren’t even aware that they needed. And this requirement for more than one domain is then exacerbated when the use of MDM is applied to a whole company rather than just one department.

Once again, the logic of applying a uniform multi-domain MDM solution to such a situation seems clear but, whether implementing a single or a multi-domain solution, the market expertise of the solution provider will be central to its success.

Issues of trust

The simple fact that multi-domain MDM only requires a single Master Data repository means that users will have significantly less autonomy in updating and storing data than they would when using silo-based single domain solutions. This should then lower the likelihood of multiple definitions and rules being created across a company, allowing for greater synchronicity and consistency, and ultimately helping to encourage more effective data governance.

Data held in a single repository will only need to be cleansed once, and it’s less likely that the repository will hold as much redundant data as several different silos. In improving data governance by standardising a company’s data rules, processes and policies, and increasing the level of trust in the data it holds, multi-domain MDM could lead to more cross-departmental collaboration and the greater efficiency that this brings.

Big Data – how big is too big?

Of the data held by a business at any given time, it’s likely that around 80 percent of it is unstructured – textual information, or social data for example. It’s this unstructured data, or Big Data that, as we pointed out in our recent whitepaper, has grown from being a marketing buzzword into a resource that businesses now heavily depend upon for strategic as well as tactical gain.

With so much depending on the ability to quickly employ Big Data for the good of a business, organisations have identified the need to revise and upgrade their data management approaches and processes.

What is immediately evident is that, by its very nature, Big Data is made up of a wide variety of data which won’t – or can’t - apply to any single domain. It’s here then, that multi-domain MDM once again proves to be the best solution, efficiently and usefully integrating Big Data with a business’s own proprietorial and structured data.

Big Data’s ubiquity and its strategic importance to businesses are further reasons for considering the economic benefits of purchasing a multi-domain MDM solution rather than a series of single domain platforms.

On balance

The purpose of Master Data Management is to share relevant and trusted data with everyone and everything within a business that requires it. Managing supplier data, for example, is an important enabler in creating a single, accurate and complete view of suppliers that will improve purchasing and negotiation power.

As companies grow, and the number of touch points across the supply chain, and the amount and variety of information grows with them, so too do the number of data domains that can be used for the benefit of a business. The single silo approach to Data Management will soon no longer be able to cope with the sheer amount of data.

Questions of cost, efficiency and of governance must be considered and, through that lens, the use of single domain MDM weighed against that of multi-domain.

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Jun 11, 2021

NTT DATA Services, Remodelling Supply Chains for Resilience

6 min
Joey Dean, Managing Director of healthcare consulting at NTT DATA Services, shares remodelling strategies for more resilient supply chains

Joey Dean, the man with the coolest name ever and Managing Director in the healthcare consulting practice for NTT DATA and is focused on delivering workplace transformation and enabling the future workforce for healthcare providers. Dean also leads client innovation programs to enhance service delivery and business outcomes for clients.

The pandemic has shifted priorities and created opportunities to do things differently, and companies are now looking to build more resilient supply chains, none needed more urgently than those within the healthcare system. Dean shares with us how he feels they can get there.

A Multi-Vendor Sourcing Approach

“Healthcare systems cannot afford delays in the supply chain when there are lives at stake. Healthcare procurement teams are looking at multi-vendor sourcing strategies, stockpiling more inventory, and ways to use data and AI to have a predictive view into the future and drive greater efficiency.

“The priority should be to shore up procurement channels and re-evaluate inventory management norms, i.e. stockpiling for assurance. Health systems should take the opportunity to renegotiate with their current vendors and broaden the supplier channel. Through those efforts, work with suppliers that have greater geographic diversity and transparency around manufacturing data, process, and continuity plans,” says Dean.

But here ensues the never-ending battle of domestic vs global supply chains. As I see it, domestic sourcing limits the high-risk exposure related to offshore sourcing— Canada’s issue with importing the vaccine is a good example of that. So, of course, I had to ask, for lifesaving products, is building domestic capabilities an option that is being considered?

“Domestic supply chains are sparse or have a high dependence on overseas centres for parts and raw materials. There are measures being discussed from a legislative perspective to drive more domestic sourcing, and there will need to be a concerted effort by Western countries through a mix of investments and financial incentives,” Dean explains.

Wielding Big Tech for Better Outcomes

So, that’s a long way off. In the meantime, leveraging technology is another way to mitigate the risks that lie within global supply chains while decreasing costs and improving quality. Dean expands on the potential of blockchain and AI in the industry

“Blockchain is particularly interesting in creating more transparency and visibility across all supply chain activities. Organisations can create a decentralised record of all transactions to track assets from production to delivery or use by end-user. This increased supply chain transparency provides more visibility to both buyers and suppliers to resolve disputes and build more trusting relationships. Another benefit is that the validation of data is more efficient to prioritise time on the delivery of goods and services to reduce cost and improve quality. 

“Artificial Intelligence and Machine Learning (AI/ML) is another area where there’s incredible value in processing massive amounts of data to aggregate and normalise the data to produce proactive recommendations on actions to improve the speed and cost-efficiency of the supply chain.”

Evolving Procurement Models 

From asking more of suppliers to beefing up stocks, Dean believes procurement models should be remodelled to favour resilience, mitigate risk and ensure the needs of the customer are kept in view. 

“The bottom line is that healthcare systems are expecting more from their suppliers. While transactional approaches focused solely on price and transactions have been the norm, collaborative relationships, where the buyer and supplier establish mutual objectives and outcomes, drives a trusting and transparent relationship. Healthcare systems are also looking to multi-vendor strategies to mitigate risk, so it is imperative for suppliers to stand out and embrace evolving procurement models.

“Healthcare systems are looking at partners that can establish domestic centres for supplies to mitigate the risks of having ‘all of their eggs’ in overseas locations. Suppliers should look to perform a strategic evaluation review that includes a distribution network analysis and distribution footprint review to understand cost, service, flexibility, and risks. Included in that strategy should be a “voice of the customer” assessment to understand current pain points and needs of customers.”

“Healthcare supply chain leaders are re-evaluating the Just In Time (JIT) model with supplies delivered on a regular basis. The approach does not require an investment in infrastructure but leaves organisations open to risk of disruption. Having domestic centres and warehousing from suppliers gives healthcare systems the ability to have inventory on hand without having to invest in their own infrastructure. Also, in the spirit of transparency, having predictive views into inventory levels can help enable better decision making from both sides.”

But, again, I had to ask, what about the risks and associated costs that come with higher inventory levels, such as expired product if there isn’t fast enough turnover, tying up cash flow, warehousing and inventory management costs?

“In the current supply chain environment, it is advisable for buyers to carry an in-house inventory on a just-in-time basis, while suppliers take a just-in-case approach, preserving capacity for surges, retaining safety stock, and building rapid replenishment channels for restock. But the risk of expired product is very real. This could be curbed with better data intelligence and improved technology that could forecast surges and predictively automate future supply needs. In this way, ordering would be more data-driven and rationalised to align with anticipated surges. Further adoption of data and intelligence and will be crucial for modernised buying in the new normal.

The Challenges

These are tough tasks, so I asked Dean to speak to some of the challenges. Luckily, he’s a patient guy with a lot to say.

On managing stakeholders and ensuring alignment on priorities and objectives, Dean says, “In order for managing stakeholders to stay aligned on priorities, they’ll need more transparency and collaborative win-win business relationships in which both healthcare systems and medical device manufacturers are equally committed to each other’s success. On the healthcare side, they need to understand where parts and products are manufactured to perform more predictive data and analytics for forecasting and planning efforts. And the manufacturers should offer more data transparency which will result in better planning and forecasting to navigate the ebbs and flows and enable better decision-making by healthcare systems.

Due to the sensitive nature of the information being requested, the effort to increase visibility is typically met with a lot of reluctance and push back. Dean essentially puts the onus back on suppliers to get with the times. “Traditionally, the relationships between buyers and suppliers are transactional, based only on the transaction between the two parties: what is the supplier providing, at what cost, and for what length of time. The relationship begins and ends there. The tide is shifting, and buyers expect more from their suppliers, especially given what the pandemic exposed around the fragility of the supply chain. The suppliers that get ahead of this will not only reap the benefits of improved relationships, but they will be able to take action on insights derived from greater visibility to manage risks more effectively.”

He offers a final tip. “A first step in enabling a supply chain data exchange is to make sure partners and buyers are aware of the conditions throughout the supply chain based on real-time data to enable predictive views into delays and disruptions. With well understand data sets, both parties can respond more effectively and work together when disruptions occur.”

As for where supply chain is heading, Dean says, “Moving forward, we’ll continue to see a shift toward Robotic Process Automation (RPA), Artificial Intelligence (AI), and advanced analytics to optimise the supply chain. The pandemic, as it has done in many other industries, will accelerate the move to digital, with the benefits of improving efficiency, visibility, and error rate. AI can consume enormous amounts of data to drive real-time pattern detection and mitigate risk from global disruptive events.”


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