Harnessing Data Archives - gettectonic.com

24Oct

AI Innovation at Salesforce

AI innovation is advancing at an unprecedented pace, unlike anything I’ve seen in nearly 25 years at Salesforce. It’s now a top priority for every CEO, CTO, and CIO I speak with. As a trusted partner, we help customers innovate, iterate, and navigate the evolving AI landscape. They recognize AI’s immense potential to revolutionize every aspect of business, across all industries. While they’re already seeing significant advancements, we are still just scratching the surface of AI’s full transformational promise. They seek AI technologies that will enhance productivity, augment employee performance at scale, improve customer relationships, and ultimately drive rapid time to value and higher margins. That’s where our new Agentforce Platform comes in. Agentforce represents a breakthrough in AI, delivering on the promise of autonomous AI agents. These agents perform advanced planning and decision-making with minimal human input, automating entire workflows, making real-time decisions, and adapting to new information—all without requiring human intervention. Salesforce customers are embracing Agentforce and integrating it with other products, including Einstein AI, Data Cloud, Sales Cloud, and Service Cloud. Here are some exciting ways our customers are utilizing these tools: Strengthening Customer Relationships with AI Agents OpenTable is leveraging autonomous AI agents to handle the massive scale of its operations, supporting 60,000 restaurants and millions of diners. By piloting Agentforce for Service, they’ve automated common tasks like account reactivations, reservation management, and loyalty point expiration. The AI agents even answer complex follow-up questions, such as “when do my points expire in Mexico?”—a real “wow” moment for OpenTable. These agents are redefining how customers engage with companies. Wiley, an educational publisher, faces a seasonal surge in service requests each school year. By piloting Agentforce Service Agent, they increased case resolution by 40-50% and sped up new agent onboarding by 50%, outperforming their previous systems. Harnessing Data Insights The Adecco Group, a global leader in talent solutions, wanted to unlock insights from its vast data reserves. Using Data Cloud, they’re connecting multiple Salesforce instances to give 27,000 recruiters and sales staff real-time, 360-degree views of their operations. This empowers Adecco to improve job fill rates and streamline operations for some of the world’s largest companies. Workday, a Salesforce customer for nearly two decades, uses Service Cloud to power customer service and Slack for internal collaboration. Our new partnership with Workday will integrate Agentforce with their platform, creating a seamless employee experience across Salesforce, Slack, and Workday. This includes AI-powered employee service agents accessible across all platforms. Wyndham Resorts is transforming its guest experience by using Data Cloud to harmonize CRM data across Sales Cloud, Marketing Cloud, and Service Cloud. By consolidating their systems, Wyndham anticipates a 30% reduction in call resolution time and an overall enhanced customer experience through better access to accurate guest and property data. Empowering Employees Air India, with ambitions to capture 30% of India’s airline market, is using Data Cloud, Service Cloud, and Einstein AI to unify data across merged airlines and enhance customer service. Now, human agents spend more time with customers while AI handles routine tasks, resulting in faster resolution of 550,000 monthly service calls. Heathrow Airport is focused on improving employee efficiency and personalizing passenger experiences. Service Cloud and Einstein chatbots have significantly reduced call volumes, with chatbots answering 4,000 questions monthly. Since launching, live chat usage has surged 450%, and average call times have dropped 27%. These improvements have boosted Heathrow’s digital revenue by 30% since 2019. Driving Productivity and Margins Aston Martin sought to improve customer understanding and dealer collaboration. By adopting Data Cloud, they unified their customer data, reducing redundancy by 52% and transitioning from six data systems to one, streamlining operations. Autodesk, a leader in 3D design and engineering software, uses Einstein for Service to generate AI-driven case summaries, cutting the time spent summarizing customer chats by 63%. They also use Salesforce to enhance data security, reducing ongoing maintenance by 30%. Creating a Bright Future for Our Customers For over 25 years, Salesforce has guided customers through transformative technological shifts. The fusion of AI and human intelligence is the most profound shift we’ve seen, unlocking limitless potential for business success. Join them at Dreamforce next month, where we’ll celebrate customer achievements and share the latest innovations. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

October 24, 2024in Agentforce Platform

13Aug

The Role of Data to Harness AI

Harnessing AI for Enhanced Sales and Service: The Role of Data Organizations are racing to leverage AI to enhance their sales and service experiences. The Role of Data to Harness AI cannot be underestimated. However, great AI solutions rely on quality data. Traditionally, companies have managed structured data—neatly organized into rows and columns, such as customer engagement data from CRM systems. But businesses also hold a wealth of unstructured data in formats like documents, images, audio, and video recordings. This unstructured data can be highly valuable, offering deeper AI insights that are more accurate and comprehensive, grounded in real customer interactions. Yet, many organizations struggle to effectively access, integrate, and utilize their unstructured data to gain a holistic customer view. With advancements in large language models (LLMs) and generative AI, organizations can now bridge this gap. To succeed in the AI era, companies need to develop integrated, federated, intelligent, and actionable solutions across all customer touchpoints while managing complexity. Leveraging Unstructured Data for Superior AI Performance For instance, when a customer seeks help with a recent purchase, they typically start with a company’s chatbot. To ensure a relevant and positive experience, the chatbot must be informed by comprehensive customer data, including recent purchases, warranty details, and past interactions. Additionally, the chatbot should draw on broader company data, such as insights from other customers and internal knowledge base articles. This data can be spread across structured databases and unstructured files, like warranty contracts or knowledge articles. Accessing and utilizing both types of data is crucial for a satisfying interaction. The key to accurate AI responses is augmenting LLMs with both real-time structured and unstructured data from within a company’s systems. An effective approach is Retrieval Augmented Generation (RAG), which combines proprietary data with generative AI to enhance contextuality, timeliness, and relevance. Ensuring Relevance Across Scenarios A unified view of customer data—both structured and unstructured—provides the most relevant information for any situation. For example, financial institutions can leverage this comprehensive data to offer real-time market insights tailored to individual banking needs, providing actionable advice based on current information. Companies are increasingly exploring RAG technology to improve internal processes and deliver precise, up-to-date information to employees. This approach enhances contextual assistance, personalized support, and decision-making efficiency across the organization. The Role of Data to Harness AI Preparing Data for AI: Key Steps By addressing these areas, organizations can harness the full potential of AI, transforming customer interactions and enhancing service efficiency. Talk to Tectonic today if your data is ina disarray. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

August 13, 2024in Generative AI

07Mar

AI and the Role of Healthcare CIOs

Healthcare leaders see significant potential in data analytics and AI technology to transform the industry over the next five years, according to a new market research report from Arcadia and The Harris Poll. AI and the Role of Healthcare CIOs The report, titled “The Healthcare CIO’s Role in the Age of AI,” examines AI’s impact on the healthcare sector and how decision-makers are preparing to leverage the technology. Notably, 96% of healthcare leaders surveyed believe that adopting AI effectively will provide a competitive edge both now and in the future. While only a third see AI as essential today, 73% expect it to become critical within five years. How Health Systems Are Using AI Around 63% of respondents revealed that their organizations use AI to analyze large patient data sets to identify trends and guide population health management efforts. Another 58% are using AI to analyze individual patient data to identify opportunities for improving health outcomes. Close to half of the leaders indicated that AI is being used to optimize electronic health records (EHR) management and analysis. These trends align with the findings of the recent “Top of Mind for Top Health Systems” survey, conducted by the University of Pittsburgh Medical Center’s Center for Connected Medicine (CCM) in collaboration with KLAS, which identified AI as the most exciting emerging technology in healthcare with transformative potential for both administration and care delivery. The excitement surrounding healthcare AI largely stems from its ability to break down data silos and tap into the wealth of clinical data that healthcare organizations already collect. “Healthcare leaders are thoughtfully preparing to harness the full value of AI in care delivery reform,” said Aneesh Chopra, Arcadia’s chief strategy officer. “As safe, secure data sharing scales, technology leaders prioritize data platforms that organize fragmented patient records into clinically relevant insights at every stage of the patient journey.” A quest for a 360 degree patient view abounds. Using AI to Support Strategic Priorities The Arcadia survey emphasized the importance of using analytics to improve patient care, with 83% of leaders believing that harnessing data will help healthcare organizations remain competitive and resilient while overcoming digital transformation and financial challenges. Eighty-four percent of respondents cited technology as a current priority, with 44% focusing on an enterprise-wide approach to data analytics, 41% prioritizing AI-driven decision-making, and 32% working to simplify technical ecosystems. These efforts are viewed as crucial to advancing other strategic goals, with 40% of leaders prioritizing the patient experience, 35% aiming to improve outcomes, and 29% focusing on patient engagement. Although healthcare leaders view AI adoption positively for strategic advancements, hurdles remain. While 96% of respondents are confident in adopting AI, many feel pressured to move quickly. When asked about the sources of this pressure, 82% cited data and analytics teams, 78% pointed to IT and tech teams, and 73% mentioned executives. However, successfully implementing AI requires talent and resources that some organizations lack. About 40% of leaders identified a lack of talent as a significant barrier to AI adoption, signaling the need for IT and analytics teams to acquire new skill sets. Seventy-one percent of IT leaders reported a growing demand for data-driven decision-making skills, while two-thirds pointed to a rising need for expertise in data analysis, machine learning, and systems integration. Additionally, nearly 60% mentioned the need for roles that focus on training and support for healthcare staff. The Evolving Role of CIOs CIOs and other healthcare leaders are seeing their roles evolve as AI and data become more integrated into healthcare operations. Eighty-seven percent of respondents see themselves as strategy influencers, actively involved in setting and executing AI strategies, while only 13% view themselves as purely focused on implementation. Despite these evolving roles, many CIOs feel constrained by daily operations. Fifty-eight percent reported being primarily focused on tactical execution rather than developing long-term AI strategies, although they believe they should spend 75% of their time on strategic planning to be most effective. Part of these strategies will likely focus on improving communication and workforce readiness. Three out of four leaders cited a lack of effective communication between IT teams and clinical staff as a barrier to leveraging new technologies, and two out of five noted that clinical staff are not fully equipped to make the best use of data analytics. “CIOs and their teams are setting the stage for an AI-powered revolution in patient care and healthcare operations,” said Michael Meucci, Arcadia’s president and CEO. “Our findings highlight a strong consensus that a solid data foundation is necessary to realize the future of AI in healthcare. At the same time, the human workforce, with evolving talent and skills, will shape the real-world impact of AI in healthcare.“ Content updated August 2024. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more Top Ten Reasons Why Tectonic Loves the Cloud The Cloud is Good for Everyone – Why Tectonic loves the cloud You don’t need to worry about tracking licenses. Read more

March 7, 2024in Generative AI, Salesforce Development Services, Salesforce Health and Life Sciences Solutions

14Jul

Quest to be Data-Driven

“Data-driven” is a business term that refers to the utilization of data to inform or enhance processes, decision making, and even the revenue model. The quest to be data-driven is afoot. In recent years, a data-driven business approach has gained a great deal of traction. It is true that every business deals with data — however, data-driven businesses systematically and methodically use data to power business decisions. Incorporating the notion of being a data-driven enterprise enriches the understanding of how data can profoundly impact business operations. Leveraging data not only offers valuable insights but also enhances adaptability, thereby sharpening the competitive edge of an organization. These insights serve as a foundation for making market predictions and adapting business strategies accordingly, often leading to revenue growth. While data may not provide solutions to all organizational challenges, embracing a data-driven approach lays a solid groundwork for achieving organizational goals. Data-driven contrasts with decision making that may be driven by emotions, external pressure, or instinct. So, what exactly constitutes a data-driven enterprise? It transcends mere number-crunching; it involves creating sustainable value for customers and innovating efficiently in the digital economy. Encouraging a data-driven approach across all facets of the business is paramount to success. Gaining data insights from data is invaluable. It allows organizations to reshape customer interactions, provided the data is accurate, accessible, and integrated into existing processes. However, many struggle to extract value from their data due to the complexity of transforming raw data into actionable insights. Understanding the hierarchy of data, information, and insights is crucial, as actionable insights drive data-driven success. Furthermore, adaptability emerges as a crucial factor in today’s rapidly evolving landscape. The ability to swiftly respond to changes and leverage data for informed decision-making is paramount. Data-driven insights serve as powerful tools for facilitating change and fostering agility, ensuring organizations remain competitive. Moreover, data serves as a catalyst for revenue generation through various business models such as Data as a Service (DaaS), Information as a Service (IaaS), and Answer as a Service (AaaS). By putting customer satisfaction at the forefront and leveraging data-driven insights, organizations can evolve their products proactively and drive growth. Building a data-driven enterprise involves a strategic approach encompassing nine key steps, including defining end goals, setting tangible KPIs, and fostering a data-driven culture across the organization. However, challenges such as deciding what to track, lack of tools or time for data collation, and turning data into meaningful insights may arise. Overcoming these challenges requires a cultural shift towards data-driven decision-making and the adoption of modern data architectures. Walking (or perhaps running) the data-driven journey with Tectonic involves connecting and integrating various data sources to ensure seamless data flow. By embracing a data-driven approach, organizations can unlock the full potential of their data, driving innovation, enhancing customer experiences, and achieving long-term success in today’s dynamic, rapidly evolving business landscape. Expanding upon this foundation, let’s go deeper into the transformative power of data-driven enterprises across various industry sectors. Consider, for instance, the retail industry, where data-driven insights revolutionize customer experiences and optimize operational efficiency. In the retail sector, understanding consumer behavior and preferences iscrucial to daily, quarterly, and annual success. By harnessing data analytics, retailers can analyze purchasing patterns, demographic information, and social media interactions to tailor marketing strategies and product offerings. For example, through personalized recommendations based on past purchases and browsing history, retailers can enhance customer engagement and drive sales. Moreover, data-driven insights enable retailers to optimize inventory management and supply chain operations. By analyzing historical sales data and demand forecasts, retailers can anticipate fluctuations in demand, minimize stockouts, and reduce excess inventory. This not only improves operational efficiency but also enhances customer satisfaction by ensuring products are readily available when needed. Furthermore, in the healthcare industry, data-driven approaches revolutionize patient care and treatment outcomes. Electronic health records (EHRs) and medical imaging technologies generate vast amounts of data, providing healthcare professionals with valuable insights into patient health and treatment efficacy. By leveraging predictive analytics and machine learning algorithms, healthcare providers can identify patients at risk of developing chronic conditions, enabling early intervention and preventive care. Additionally, data-driven approaches facilitate personalized treatment plans tailored to each patient’s unique medical history, genetic makeup, and lifestyle factors, improving treatment outcomes and patient satisfaction. In the manufacturing sector, data-driven strategies optimize production processes, enhance product quality, and reduce operational costs. By implementing Internet of Things (IoT) sensors and connected devices on the factory floor, manufacturers can collect real-time data on equipment performance, energy consumption, and production efficiency. Analyzing this data enables manufacturers to identify inefficiencies, minimize downtime, and proactively schedule maintenance to prevent costly equipment failures. Moreover, data-driven insights inform process improvements and product innovations, enabling manufacturers to stay competitive in an increasingly globalized market. The ultimately transformative impact of data-driven enterprises extends across various industry sectors, revolutionizing business operations, enhancing customer experiences, and driving innovation. By embracing a data-driven approach and leveraging advanced analytics technologies, organizations can unlock new opportunities for growth, efficiency, and competitive advantage in today’s data-loaded digital economy. Becoming data-driven requires harnessing the full potential of your data, transforming it into actionable insights, and iteratively refining your processes. Remember, data itself is not the ultimate goal but rather a powerful tool to drive informed decision-making and organizational growth. To establish a truly data-driven organization, consider the following nine steps: By following these steps, your organization can effectively harness the power of data to drive innovation, improve decision-making, and achieve sustainable growth in today’s data-driven landscape. Tectonic recognizes the challenges in the quest to be data-driven. We’ve launched a Data Cloud Salesforce Implementation Solution to help you. Content updated May 2024. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing,

July 14, 2021in Data, Enterprise, Salesforce, Salesforce Data Cloud, Salesforce Health and Life Sciences Solutions, Salesforce Hospitality Travel and Transportation, Salesforce Manufacturing Automotive Energy, Technology

Harnessing Data

The Role of Data to Harness AI

Recent Posts

Agentforce Powered Marketing

Payload and REDA

Amazon Q Business

Salesforce and AWS-Agentic Enterprise

Salesforce and Asana Integration Approach

Contact Us

Be in touch today — and start your business on a path to success.

Category

Archives