Smart technology providers in the manufacturing world know a lot about data collection, advanced analytics, artificial intelligence, and a whole lot more, but they don’t know everything. And, even if they did, they don’t know it in Spanish, Mandarin, Farsi, or English. So, when you talk to technology people, you tend to hear a lot about “partner ecosystems.”
Smart Industry recently spoke to Megan Buntain, vice president of global partnerships and ecosystem for Seattle-based Seeq, a provider of advanced analytics software with ML and AI to manufacturers such as pharmaceuticals, oil and gas, mining, pulp and paper, energy, utilities, and chemicals.
Buntain is responsible for leading and continuing to grow the Seeq global partner ecosystem, enabling the company to accelerate customer value. She previously served as director of cloud partnerships and VP of cloud transformation, where she built the program that launched Seeq as a top-tier partner of the cloud providers.
To SI, Buntain detailed Seeq’s approach to partner ecosystems, or business networks that serve similar audiences but aren’t competitors. The following are Buntain’s lightly edited answers to our questions.
Smart Industry: How does Seeq tap into partner ecosystems and what role does this interaction play in the company’s business plan?
Buntain: Our partner ecosystem, made up of technology partners, systems integrators, and value-added resellers, enables Seeq to accelerate customer value through co-innovation and joint customer engagement. We’re tapping into the global ecosystem to expand our services and engineering capabilities.
Industrial companies need their digital investments to generate significant returns. By collaborating with partners, including certifying engineers at these organizations as Seeq analytics engineers, we can expand our reach and effectively deliver these returns for customers in more regions and industry verticals.
Our partners also drive workforce empowerment and enablement within more customer organizations. For example, Seeq global services partners ensure training and support are offered in the language and time zone preferred by customers in different regions.
Smart Industry: How can these tech partnerships help to accelerate sustainability initiatives?
Buntain: Database integrations made possible by partners enable sustainability teams to extend the power of these systems to integrate time series process data preparation, analysis, and continuous improvement with their sustainability tracking initiatives to ultimately reduce environmental impact.
For example, Seeq and partner Microsoft announced in April a solution that enhances sustainability programs by preparing and integrating critical time series data and subject matter expert (SME) knowledge into the corporate reporting and continuous improvement cycle.
Smart Industry: Are there other areas, besides sustainability, where partner ecosystems have been valuable?
Buntain: Our certified partner community applies our software techniques to engineering problems, including asset management, process improvement, and emissions mitigation. Recently, we issued a call for papers from our partners, and they responded with more than 20 use cases that included documented business value and ROI in operational areas, such as reductions in raw material usage, improvements in asset lifecycle performance, and reduced methane flaring—just to name a few.
Smart Industry: How do these technology partnerships allow manufacturers to scale and operationalize advanced analytics, machine learning, and artificial intelligence?
Buntain: A key area of focus with our technology partner ecosystem has been improving the collaboration between SMEs in the plant and data science teams. Traditionally, the plant teams have insights and context related to the assets and processes they are managing, but it has been challenging to get that information into the hands of data scientists who can apply innovations in machine learning to solve increasingly complex problems.
We recently announced a partnership with Databricks, a data and AI company, to simplify data science access to high-quality asset and process data, unify IT and OT data processing, and accelerate AI/ML adoption across industrial manufacturing and other sectors.
Seeq has always been focused on ensuring value and insights from operational data are available to every person within a company, regardless of their role. Partnership efforts, like the one with Databricks, make this a reality.
Smart Industry: Can you elaborate on the benefits of partnering with “hyperscalers”—large cloud service providers—such as Amazon Web Services and Microsoft?
Buntain: Those partnerships bridge the OT and IT divide to drive business value for our shared customers. The cloud helps companies in a few ways:
- Scalability: Businesses have the agility to scale software up or down as their needs change. The cloud ensures teams have the computing resources to remain online during peak demand periods. A process engineer using Seeq can experience the same application performance when they are analyzing hundreds of assets as they do when they are focused on just one asset.
- Advanced analytics: Using the cloud, organizations can analyze terabytes of sensor data at millisecond frequencies. With purpose-built software for manufacturing data, insight generation is automated, aiding decision-making and improving business performance.
- Workforce empowerment: Modern software equips employees with insights and context at their fingertips—whether they are at the plant, working in the office, or at home—along with the ability to easily collaborate and share insights with colleagues anytime.
Hyperscaler partnerships help us ensure continuity of critical processes while producing new operational and maintenance insights, increasing efficiency, boosting profits, and generating overall business value for our shared customers.
Smart Industry: Can you provide some examples, or case studies, where collaboration with technology partners have proven successful?
- Marathon Oil is monitoring thousands of wells with a finite number of resources. Historically, the teams were faced with a cumbersome and manual data analysis process. This manual process, combined with disparate systems and long lead times to mobilize internal development resources, prompted the organization to deploy its Digital Oilfield Project. This project is focused on providing user-friendly and automated time series analytics to SMEs, along with full autonomy to create intelligent alerts using Seeq on AWS. With more proactive alerts, the team reduced unplanned outages, ultimately keeping production online longer. Additionally, the autonomy to create alerts within the integration hub empowers teams to work on new high-value problems while saving internal development resources for more complex tasks.
- Syngenta is using Seeq on AWS to take tangible action toward its 2030 Sustainable Operations Commitments, which include the goal to “reduce the carbon intensity of operations by 50%.” The team created near-real-time carbon intensity estimates that empower the company to make data-driven decisions that track measurable progress towards its 2030 goals, helping the manufacturer emerge as a sustainability leader in the chemical industry.
- Chemicals manufacturer Covestro, which used to follow a predictive maintenance approach for heat exchangers. Leveraging operational data from their PI System historian, SMEs used Seeq on AWS to calculate the heat transfer coefficient of heat exchangers, and these values were then used to predict when equipment fouling would degrade production quality. Company engineers employed linear regression analyses to identify the best times for removing built-up solids from the heat exchanger. In the past, these types of calculations took days to complete, but using Seeq, the team automates these measurements in minutes, empowering factory operators to efficiently schedule built-up solids removal.
- Chevron sought to automate their regulatory compliance reporting for greenhouse gas emissions across their refineries. By leveraging Seeq on Microsoft Azure, the company gained live access to data from multiple refinery historians, enabling its SMEs to apply calculations and contextualization for quarterly regulatory emissions reporting. With automatic calculations and real-time updates that incorporate the latest data, Chevron reduced analysis time from two or three days to just a few hours. Most notably, the new up-to-date and readily available emissions performance information empowered the company to take a proactive approach to emissions identification and mitigation, resulting in prevention in some instances, rather than reporting events long after the fact.