May 17, 2020

Five common pitfalls for Supply Chain Digital Transformation

Dr. Madhav Durbha
6 min
Man in warehouse holding a digital tablet
Dr. Madhav Durbha, LLamasoft,discusses the five common pitfalls organisations face when digitally transforming their supply chains.

Digital supply chai...

Dr. Madhav Durbha, LLamasoft, discusses the five common pitfalls organisations face when digitally transforming their supply chains.

Digital supply chains are all the rage now! A quick browse through the public filings and investor presentations of several publicly traded corporations indicates some sort of digital supply chain initiative under way. This is not surprising given the major factors reshaping supply chains, such as rapidly shifting consumer behaviors, trade wars, heavy M&A activity, the Amazon effect, increased focus on sustainability and cyber-physical convergence. However, are these digital efforts bearing fruit and delivering on the promise?

A recent McKinsey Global Survey reports that just 14% of the respondents state that their digital transformation efforts have made sustained performance improvements. This is a rather low number, but not all that shocking. In my experience of having assisted a number of organizations through their digital journies, a few common themes stand out among those that failed to sustain their transformation. Avoiding these pitfalls will help organizations sustain the value creation from their digital transformation efforts. Let us examine these.

1. Treating digitalization as the end

It is important to remember that digitalization is the means to the end. The end represents a sustainable, positive value creation to the business and its stakeholders. Successful digital transformation efforts have strong executive sponsorship, clearly communicated goals through the organization, development of internal competencies, and an obsessive focus on measuring and sustaining the value created. A text book example is the story of Domino’s Pizza evolving into an e-Commerce powerhouse. Domino’s kept the customer experience at the center of its transformation. Besides making several changes to its recipes and ingredients over recent years, it built a highly immersive, fun, digital platform wherein a customer placing an order in their app can track the progress of the pizza being made until the point of delivery. Domino’s backed these front-end investments by designing and running a high performance supply chain. Thanks to their transformation efforts, investors are being richly rewarded. The stock price went from US $3 in 2008 to US $249 as of this writing, an increase of 83 times! Exciting as their digital journey has been, it is still the means, with the end goal being delighting customers and driving value to all their stakeholders. Of course a strong executive sponsorship and shaping the culture to rally behind the transformation continue to be key ingredients for their success.

 

2. Opting for a big bang… or is that the bust?

Going digital can be a double-edged sword. When done correctly, such as in the case of Domino’s, the results are game changing. However, when done incorrectly, mistakes can propagate and amplify much faster. History has plenty of examples of companies blaming failed supply chain digitalization efforts for missed quarterly results and writing off millions in investments. Big bang deployments with a massive scope are especially prone to such mishaps. While it is great to have big, hairy, audacious goals as the ends for the digital transformation, milestones along the way that generate value are critical. There should be enough value created at each of these milestones that the transformation can become self-funding and self-sustaining. 

A large discrete manufacturing company started with an ambitious goal of standardizing on one global enterprise resource planning (ERP) as a digital backbone for its transformation. However, over time this turned into a moving target as the company pursued inorganic growth with an acquisition spree. Additionally, while the ERP system was great for capturing transactions, it came up short in providing end-to-end forward visibility to drive decisions and stretching beyond the four walls of the enterprise. In the end the digital transformation became more of a technical endeavor rather than enabling big needle-moving value. While not disastrous by any means, the company did not quite derive the benefits it was hoping for. While there are several examples such as the one above, this is one area where I am seeing progress. Organizations are increasingly opting for best of breed approaches rather than relying on one vendor to do it all. Most projects we are engaged in now are opting for paybacks in a span of months as opposed to years, with the first step of value creation starting in as short as 8 to 12 weeks. Celebrations of success along the way to rally the organization behind the efforts and gain momentum will be critical. 

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3. Looking inside-out and automating the current processes

Organizations often make the mistake of automating existing processes as opposed to rethinking them in light of the potential digitalization can offer. As an example, often times I see organizations embark on their supply chain transformation by investing in demand planning systems that rely on the same historic data they used all along as the basis for forecasting. They deploy a commercial off-the-shelf package with statistical algorithms to automate the forecast generation that was happening in excel spreadsheets. While such organizations are internally focused on what has been shipped or sold in the past as the basis for forecasting, hoping that history will repeat itself with certain upward trends, external causals such as weather, GDP, employment levels, industrial production and demographic shifts are having a major impact on demand patterns. Few leading organizations are taking innovative, outside in approaches to drive significant (15 to 20%) forecast accuracy improvements by factoring in such external causals and leveraging machine learning algorithms that help discern patterns beyond human comprehension and draw correlations to the sales patterns. Such forecast accuracy improvements can dramatically impact capital spend reduction while delivering top-line growth by staying in tune with market shaping trends. Such is the power of “outside-in” thinking in digitalization.

 

4. Leaving the brains behind

Often times, I see organizations make big investments in Business Intelligence (BI) technology to develop dashboards and visualizations and call it digitalization. While this is a step forward in the digital journey, such descriptive analytics can surface more problems with little to no guidance as to what to do about them. Organizations need to take the journey forward into predictive and prescriptive analytics. A combination of approaches such as optimization, heuristics, simulation, and machine learning should be considered for addressing specific types of analytics. Afterall, algorithmics are like tools – each has its purpose and place. Access to a library of algorithms that power the brains of the enterprise will be extremely powerful in a world where data is the new oil and the algorithms are the heavy machinery that process the data into insights. As math powers the brains of the enterprise, it is becoming cool again! Organizations cannot leave the brains behind if they aspire to drive interconnected decisions weighing complex tradeoffs.

 

5. Not adequately developing the organizational competency

While avoiding the above pitfalls can unlock significant value, sustaining the transformation calls for developing an internal competency. While external consulting partners can help drive the strategy and implementation of digital efforts, organizations need to build internal competencies to sustain value creation. Otherwise the value delivered will wither away over time. In light of emerging technologies and the transformative effect they have on supply chains, organizations should rethink the role of humans and the skills they need to be successful in the future, helpubg their employees make a smooth transition into the increasingly digital realm. No wonder Amazon recently announced that it is retraining a third of its US work force to help prepare for the future. There is no shortcut to investing in the workforce. It is a small investment for sustained value creation and a key aspect of change management.

For more information on all topics for Procurement, Supply Chain & Logistics - please take a look at the latest edition of Supply Chain Digital magazine.

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Jun 11, 2021

NTT DATA Services, Remodelling Supply Chains for Resilience

NTTDATA
supplychain
Supplychainriskmanagement
Procurement
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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