More interesting things in robotics in 2022 - Supply chains and sentience!
Good afternoon! Last week, our Workplace team wrote about the McKinsey survey showing that DEI policies aren't yet creating measurable economic mobility for frontline workers across the country. So, in today's Braintrust, we asked a group of diversity, equity, inclusion and belonging professionals about the role of research in their work and the kind of research and data they thought would help push their missions forward. Questions or comments? Send us a note at braintrust@protocol.com
Sherika EkpoAnaplan
Interim chief people officer at Anaplan
The growing body of DE&I research in recent years has made a huge impact on our field by equipping DE&I professionals with new evidence, language and validation to elevate DE&I to a board-level priority. But we’ve reached a tipping point where companies need to go beyond activities and drive impact. Research can help us get there. More than the topic, I’m interested in how researchers deliver their findings to the business world. A lot of research in DE&I successfully illuminates a problem, but it often fails to take the next step by offering relevant benchmarks and evidence-backed actions that business leaders can apply to their own organization.
For example, I think pay equity requires more granular research that goes beyond the “hows,” “whys” and “how much” to dive deeper into discrepancies across more dimensions and touchpoints during the employee lifecycle to inform recommendations beyond pay reviews. The corporate world hasn’t tackled this issue enough or is prepared for what’s ahead. From the impacts of inflation and effects of the pandemic to the increasing dimensions of diverse identities as new generations enter the workforce, pay equity will only become a more critical and complex issue. While anecdotally we think companies are making change, continued macro disruption and societal shifts will throw this progress on its head. To see more impact from research on pay equity and other DE&I topics, there needs to be a tighter connection between the findings and strategies for tackling or implementing them.
Randall TuckerMastercard
Chief inclusion officer at Mastercard
A research- and data-driven approach to DEI is critically important. It makes the work relevant and level with other key functions for business leaders. Business strategy, sales and finance are tightly tied to data, and DEI should be, too. We need to get more intentional around how we define the scope of the work, and research can help us get there, while data helps us to solve for the right opportunity and, ultimately, to create an environment where everyone can reach their greatest potential and contribute to problem-solving and innovation. Analytics ensures that the work is grounded in a proven need state and demonstrates progress.
Benchmarking, both within an organization and among peer sets, is an important way a brand can better understand the trajectory of its DEI journey and mark goal posts along the way.
Perhaps most significantly, research can put a fine point on problems and opportunities we may have only understood in anecdotal ways. Tracking demographics is important, but insights on how those demographics are faring — their lived experience at work — is another level entirely that helps guide the work with greater intention and impact and can help us to understand how companies are harnessing the power of intersectionality to advance DEI.
Once you can quantify and define a problem, you can work to solve it. It’s not a nice-to-have, but an imperative to get right, as this work is at the forefront of our customers,' investors' and employees' minds.
Karen Craggs-MilneThoughtExchange
Vice president of environment, social and governance at ThoughtExchange
If I had to narrow suggested DEI research opportunities to two areas, I would pick these:
The need for more intersectional data collection and analysis, moving away from research that simplistically presents women, LGBTQI2S or other groups as homogenous. We need to strive for a more dynamic and richer understanding of oppression, with insights on how different sub-groups experience and navigate power and oppression differently.
Tracking how initiatives with good intentions, even those that have demonstrated traction and progress, created unintended outcomes — both positive or negative. In other words, can we track and measure the hidden costs or hidden benefits of adopting DEI work with any useful insights for DEI practitioners? This is the fourth element of my Conscious Equality Framework, a holistic approach to DEI work, and it is missing from most DEI work and research.
If we can make progress on even one of these, there would be a lot for us to work with!
Brian ReavesUKG
Chief belonging, diversity and equity officer at UKG
Research, like the McKinsey Women in the Workplace report, is an essential element of DEI&B work, because it accelerates the educational foundation that ultimately inspires people to change. While companies are used to relying on quantitative demographic data, qualitative data needs to also be understood to enact meaningful change. In truth, both are equally important. Take equity and belonging as an example: An organization may be able to measure equity from a quantitative perspective, but without considering the subjective experiences across intersectional groups pertaining to topics such as authenticity, acceptance and affiliation, leaders are missing the full picture and likely will not be able to address the root causes of the inequities they hope to address. Understanding your organization’s qualitative and quantitative data is critical to planning for holistic change. Leveraging external research is also essential to understand benchmarks and opportunities, which is why UKG is partnering with HBR Analytic Services for a research study on pay equity in America, to be published this fall. Armed with quantitative data on the existing pay gaps between men and women, organizations can supplement their own equity initiatives with key questions that can identify the root causes of pay inequity from a qualitative perspective. Being aware of the data is step one, but holding leaders accountable is a necessary next step — and to do so, DEI&B professionals must be empowered with quantitative and qualitative data to give them the necessary insights required to enable the required long-term, systemic change.
Laura ShenWEX
Chief diversity and inclusion officer at WEX
Many businesses don’t understand that diversity, equity and inclusion is not a zero-sum game. To fully achieve inclusive and equitable organizations and societies, human resources, people leaders, as well as those leading DE&I research must aggregate data and proven practices to truly make an ongoing impact.
For this to be possible, we need a platform or mechanism to compile data safely and securely across industries and geographies and create an open-source repository. A great example I saw of this recently was TheSkimm’s #ShowUsYourLeave database that provided unprecedented insight into parental leave policies across companies. Large-scale, cross-industry databases like this not only empower employees through transparency, but also prompt impactful action from employers by pushing us to collectively raise the bar.
The openness of these platforms will allow WEX and others to filter through data to discover deeper and more specific insights. It will also enable us to continue to benchmark efforts and determine where we are and where we want to be. This is the ultimate collaborative effort to embrace DE&I.
Sylvia MolCodeSignal
Industrial-organizational psychologist and head of the Skills Evaluation Lab at CodeSignal
As an industrial-organizational psychologist, for me it’s vital that my team continuously conducts our own research to identify opportunities to reduce bias in communications, processes and our product. In addition to looking at how different demographic groups are impacted by our solutions when it comes to hiring decisions, it's important for us to hear directly from our end users who identify as a part of underrepresented minority groups. To comply with regulations, protect our customers and set them up for success, we need to know how different demographic groups are performing relative to each other. Equally important is to know what are the impressions of our customers and their end users — their candidate pool. How can we make the hiring process more approachable, either in terms of communication, prep materials or processes?
Third-party research data is helpful in setting benchmarks or identifying areas of our own research where we want to bolster the information we are collecting and analyzing. Ultimately, to make progress on DE&I initiatives both for our employees and our customers, I need to have command of the data and insights I’m getting from my own internal research more than I need generalized findings from a third party.
See who's who in the Protocol Braintrust and browse every previous edition by category here (Updated Aug. 9, 2022).
Good afternoon! In today's edition, we asked supply chain and manufacturing experts to tell us what mistakes they see companies making during modernization. Questions or comments? Send us a note at braintrust@protocol.com
Duncan AngoveBlue Yonder
CEO at Blue Yonder
Too many companies are finding themselves struggling to manage the extreme supply chain volatility of the past few years, often turning to disconnected technology tools, along with planning and execution processes that are spread across functions. This ultimately results in a disconnected response or companies find themselves placing their own metrics and objectives above what’s best for the supply chain as a holistic, connected entity. These are simple mistakes when approaching supply chain modernization, which companies can’t afford during this period of economic uncertainty. To keep pace, supply chains must evolve to become living, fluid ecosystems. This will enable disruptive events to be recognized and addressed by all partners, immediately, in a synchronized and collaborative manner. No matter how geographically distributed the value network is, and how many partners it includes, today even the most complex global supply chain can be digitally connected via intelligent solutions in near real time.
Hans ThalbauerGoogle Cloud
Managing director, Global Supply Chain, Logistics & Transportation at Google Cloud
One of the biggest mistakes I often see companies make when modernizing their supply chain processes is focusing just on their orders, forecasts, and inventory, and not taking into account external factors like public information, traffic, weather, climate, and financial risks. In order to adequately prepare for inevitable future disruptions and interruptions, companies need to look holistically. By connecting these internal and external data sets, we create a community of data that fosters collaboration between business partners.
Companies need to be able to see how goods move from the factory to the warehouse to the store and ultimately the front door. The challenge with this increased visibility across the supply chain is that it has created an increase in data complexity at a scale that is impossible for humans to manage. As a result, analytics and AI are essential for managing and making sense of it all.
One of the most exciting opportunities created by all this internal and external data is around predictive analytics. Predictive analytics can make it easier for companies to make better, faster decisions, both in how they support moving inventory through the supply chain and in how they understand available capacity to support customers, for example. They can predict traffic, storms and customer demand. And as climate, pandemic, global conflicts, migration, and other issues continue to constrain the supply chain, the role of data and analytics in helping to anticipate issues is even more vital.
Torsten PilzHoneywell
Senior vice president and chief supply chain officer at Honeywell
Supply chains are now – more than ever – a technology-driven industry, and in our case, we put technology and our domain knowledge of the supply chain team in one.
The most important ingredients are the transparency and visibility of data. At Honeywell for instance, we created the largest operational data infrastructure with the integration of Honeywell Forge. It resulted in a single source of truth for data, performance monitoring and analytics. This intelligence helps Honeywell not only predict future business outcomes, but also better analyze and respond to real-time data to optimize production processes, increase productivity and be more cost-effective. Throughout the process, I learned six lessons, that I can now share with you are the top six mistakes you should avoid, in order to be successful in your modernization endeavor:
Being too short term focused
Not having a real program but trying to do it one business case at the time
Not taking employee aspects into account, i.e. training, upskilling, ‘who-does-what’
Outsourcing the entirety of the modernization plan to third party vendors
Limiting the modernization to supply chain exclusively or separately. It needs to be a business transformation including commercial and engineering teams
Not having a digital strategy that goes alongside the supply chain modernization
Like at Honeywell, your thorough and broad transformation can directly impact the supply chain, which as we’ve seen, can become more resilient, more intelligent and more agile. This would not have been possible without our employees who continue to build the supply chain of the future.
Aidan Madigan-CurtisEclipse Ventures
Partner at Eclipse Ventures
The biggest mistake leaders frequently make when attempting to modernize supply chains, is focusing on implementing new tools or technologies rather than doing a root cause analysis of the specific problems they are trying to solve.
Over the past several decades, most supply chains have become convoluted, inflexible, inefficient, and opaque. There were many historical benefits to offshoring supply chains, but we’ve also collectively assumed significant risk in how we manufacture almost everything from chicken nuggets to smart phones.
Supply chain leaders looking to modernize their manufacturing or logistics operations need to first closely examine where their chains are inefficient or broken before attempting to implement solutions. There are many examples of different types of supply chain issues: single-sourced raw commodities, sub-assemblies that travel several times around the world before final assembly and test, suppliers who obfuscate yield reports or shipping records, and/or the use of congested ports all represent common issues in supply chains today.
Supply chain leaders should resist the urge to believe that any one technology can be a panacea to their supply chain woes. A thorough risk assessment of each step of their chains, paired with an evaluation of different solutions, including simple fixes like removing middlemen in communications chains, asking for data in your suppliers’ preferred format or language, or ensuring your process includes a detailed serialization of inputs and finished assemblies for downstream traceability, may be the best - and often most simple - solutions to some of the most egregious supply chain problems.
Richard KenediGE Digital
General manager, Manufacturing & Digital Plant at GE Digital
Consider the process of modernizing your supply chain as a great opportunity for improvement. The biggest mistake would be to migrate existing procedures and practices into a new infrastructure. Clearly, you don’t want to mimic your old systems in a modern one.
As a result of changes in behavior and recent disruptions caused by the pandemic, certain areas in your supply chain need special attention. A modern supply chain demands world class manufacturing processes. A more efficient supply chain requires that you have complete visibility into your KPIs across your operations, including carbon emission, energy consumption, etc. The production system shall not be the weakest link of your supply chain. In this regard, software has become mission critical.
The new generation of manufacturing software allows you to provide interoperability between the various components of your supply chain, end-to-end traceability of raw materials and finished goods, and instant access to important parameters such as efficiency and quality data in almost real time. Then, it supports strategies such as continuous improvement and Lean process optimization, monitoring, auditing, and reduction of WAGES (Water, Air, Gas, Electricity, Steam) consumption. All of this functionality can generate tremendous savings. Finally, it leads to more informed decisions regarding investments in production capacity or outsourcing.
Software is essential to industrial and supply chain operations. It delivers the agility required to face disruptions, changes in strategy and adapt to new business models such as the Circular economy.
Caroline PanBright Machines
CMO at Bright Machines
If supply chains were given a tagline in 2022, it would be “Make it Modern.” Outdated outsourcing strategies, antiquated equipment, and a dearth of workers in the right locations brought global supply chains to a virtual standstill when the perfect storm hit. The tendency in these situations is to band-aid the problem – rachet up factory capacity though additional labor and capital expenditures – or conversely, embark on a multi-year digital transformation strategy requiring massive investments in IT infrastructure and software systems.
But there’s a better way to get started, AND future-proof a company’s operations at the same time. By focusing on desired business outcomes – including efficiency, yield, and the ever-elusive supply chain “resiliency” – companies can make smarter decisions about technologies that will drive immediate impact. Take automation, for example. Modern, full-stack solutions are now available that are flexible, programmable, and easy for assembly line technicians to troubleshoot on their own. Multiple SKUs can be run down a single line and changed on the fly, providing the ability to dynamically adjust output as market demands shift. Modular lines can be integrated into an existing facility and enable future reuse, extending the life of the equipment. And due to the economics of automation, manufacturing can be reshored and products can be built closer to the end consumer, shortening lead times and carbon emissions. More and more companies are embracing this pragmatic approach, investing in real capabilities that benefit both their near and long-term goals, versus simply focusing on the act of modernization itself.
Sean HenryStord
Founder & CEO at Stord
If brands want to enact meaningful change, they need to stop modernizing each part of the supply chain in isolation. This causes them to lose the big picture, and with it the opportunity to truly understand and optimize their networks from end to end.
For example, a CPG brand can implement specialized tools for order management or inventory management, or pick up an excellent BI solution to help forecast demand. But if these are treated as discrete areas, the company ends up with siloed data and pockets of intelligence that don’t lead to an overall strategy.
Supply chains are like living organisms in which each part affects the whole. If you want a modern supply chain, you need the system connectivity, consolidated visibility and centralized intelligence that allows you to see what impact a logistics change made over here will make to a delivery schedule halfway across the country.
It’s about having complete visibility to make the best decisions, and that can’t happen when your supply chain is a series of technology islands.
Indranil SircarMicrosoft
CTO, Manufacturing Industry at Microsoft
As organizations modernize their supply chains, it’s essential to prioritize end-to-end visibility, agility, skilling, security, and sustainability.
End-to-end visibility across your supply chain is critical for businesses across all industries. This kind of view is possible through digital transformation and turns a supply chain into a smart, interconnected network of partners and processes. Additionally, supply chain agility is also critical and empowers organizations to understand and respond quickly to real-time information. By implementing essential technology, companies can implement the right resources – people, inventory, equipment – at the right place, and at the right time.
As many of us know, one of the biggest impacts from the pandemic was on the global workforce, especially regarding safety and operations. When companies prioritize workforce transformation, a combination of reskilling and automation, they can address potential future disruptions.
Lastly, security and sustainability are imperative. By evaluating and investing in supply chain risk mitigation strategies, companies can ensure secure and compliant supply chains. Additionally, organizations can significantly improve operations by adopting sustainable practices. Pinpointing the origins of emissions across supply chains enables companies to begin to reduce their environmental impact. Companies can improve resilience to climate risks by sourcing from alternative suppliers and conducting ongoing analysis of risks to materials, logistics, suppliers, and fixed assets.
At Microsoft, we’ve learned that it’s imperative to lay the foundation for digital transformation capabilities. One thing is clear: disruption is here to stay, and building a modern, agile, and sustainable supply chain will allow manufacturers to withstand future challenges.
Sam Smith-EppsteinerInnovation Endeavors
Partner at Innovation Endeavors
Too often, we see companies innovating within their existing supply chain framework and ecosystems. We believe there is a real opportunity to fundamentally rethink supply chains given the myriad core technical innovations we see across value chains.
For example, one way to modernize the supply chain for heavy equipment would be to invest in high-capex, repetitive production abroad to minimize variable costs. However, we see an opportunity to take advantage of the marriage between industrial automation and machine learning to enable more flexibility and scalability for part production. Companies driving intelligence and automation include Machina Labs in formative, Velo3D in additive, and CloudNC in subtractive methods. These novel approaches not only enable the potential to reshore production but can also be the backbone for a more iterative, agile engineering process.
Core innovations that justify a holistic supply chain evaluation include novel bio materials, new approaches to decarbonized production (e.g., industrial heat, electrification), and increasingly autonomous commercial electric logistics options. Optimizing within an existing supply chain might generate a local optimum but miss the global maximum opportunity, particularly when considering climate impact.
See who's who in the Protocol Braintrust and browse every previous edition by category here (updated July 26, 2022).