May 17, 2020

Comment: Three Criteria Your Supply Chain Analytics Partner Should Meet

Supply Chain
business intelligence
Supply Chain
Shashikiran PB, Principal – An...
5 min
Three Criteria Your Supply Chain Analytics Partner Should Meet
When it comes to choosing an analytics partner for supply chain, there is an important checklist businesses should go through to ensure they find the ri...

When it comes to choosing an analytics partner for supply chain, there is an important checklist businesses should go through to ensure they find the right one.

Each company is present at a different stage of analytics maturity and the fact is that even within the same company, different planning processes have different levels of depth and maturity when it comes to analytics. So, the need is to find a true partner that can handle multiple aspects to analytics services as well as the ability to integrate with a customer’s current environment.

So when evaluating a potential analytics service partner, we should look at whether they can provide all the following services in equal measure.

  • Business Intelligence (BI) – reports and visualization
  • Planning problems – design, develop and support of an analytics based solution
  • On-demand rapid analytics – an extended client-team with onsite and offshore model

If the partner is unable to provide any of the above, there is a need to reconsider and evaluate other partner options.

The first thing your analytics services partner should be able to do is get your company’s BI in shape – this is the very backbone of analytics.    The problem right now for most companies is that their data resides in all types of systems that don’t talk to one another.   The right analytics partner should be able to create a platform powered by data engineering, big data and technology that can put the data in one place and make it efficient so that it can be easily refreshed.  On top of this platform, the partner can create BI solutions to help businesses make better informed decisions based on real data.

A good supply chain analytics partner should also be able to help through the planning processes through analytics intervention using applied mathematics and technology deployment.   This includes problem solving in issues like routing, scheduling, production planning, and stock allocation. It involves moving from spreadsheets to real-time analytics solutions and knowing how to move beyond the limits of off the shelf analytics products. In many cases, the partner needs to exploit the capabilities of the existing products with the client and then, build layers of customization to make the results even more effective.

Finally, the right supply chain analytics partner should be able to run on-demand rapid analytics.  Every single organization we have spoken with at Tredence has dozens of small unsolved analytics problems. These problems surface on a fairly regular basis and the clients cannot hire full time people to solve these smaller issues when they arise.   But if you can find the right analytics partner, this team can handle ad-hoc demand for decision support analytics with highly developed skillsets in data extraction, cleansing and preparation, rapid analysis and generation of actionable insights. Using an onsite team as well as a technically skilled offshore team has shown to be the right combination for solving these on-demand analytics problems providing effective trade-offs in terms of costs, turnaround time and access to a large pool of skills.

As an example, we’ve done work with a major trucking company that has been using big legacy analytics systems for over 30 years. The client was evaluating several dimensions in order to improve on operational efficiencies; for instance, they were evaluating what is the right number of vendors to work with to have the best trade-off between costs, risks and service levels, OR, why are some software upgrades failing across our fleet of trucks or which auto parts are likely to fail next?  They could not invest three plus years to build out another big analytics solution; they needed someone to do rapid, accurate analysis, by first creating a data pool and run queries on it, with mathematical manipulation that could be used for immediate insights. They needed an analytics team that would run reports in a consistent, accurate manner every time, with a user interface that was intuitive and visually appealing.

The company realized that even if they had an analytics service provider already doing Step 1 and Step 2 for them (BI and Planning Problems), they needed to also do Step 3 -execute on-demand rapid analytics. 

In this case, the first thing Tredence did was to remove the obstacles around on-demand analytics. We deployed a team consisting of both onsite resources at the client location as well offshore ones at our Global Delivery center in Bangalore. This team produced rapid insights and answered the most pertinent customer needs on the scale of urgency and importance. With these problems behind us, the client could concentrate on addressing longer term problems that needed powerful solutions driven by advanced analytics and technology. In parallel, a high majority of BI tasks were automated leading to further efficiency across the board.

Apart from these three important criteria is change management – this is how an analyst evaluates his own work and makes it better.

Your supply chain analytics partner should be able to take a step back and examine what was the original business problem for their client, what did the analytics achieve, and how that is tied back into their business.

For instance, as a supply chain partner, we believe that there is a massive revenue opportunity for one of our clients in how they plan their truck routes from their distribution center on a day to day basis. Our analytics services can recommend the best way to do truck planning, but if we stop there, the solution can never be utilized.  We need to take into account the business’ IT system where orders are prioritized based on which customer is most important and then fed into the transportation system.   We need to understand the user rights associated with the system and who is allowed to view which information about orders and routes. Our job as the supply chain analytics services provider is to understand how our solution integrates with the current environment of the customer. We even need to think about how the planners as well as the truck drivers are incentivized in order to make the best decisions for the client.

It’s really about integrating analytics with the current business environment. If a business picks a company that can do the first three criteria but does not understand change management or how the analytics should be integrated into an existing business environment, then they are really on a self-fulfilling mission that will never truly make an impact on solving the business problems.

Going through this checklist and ensuring your partner can do the full circle of supply chain analytics from BI, to planning, to on-demand rapid analytics and then integration is essential for answering challenging business problems.  Be prepared to have potential partners explain how they conduct each step for their clients to win your analytics business.

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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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