How Data Centers Are Driving The Renewable Energy Transition

The argument could be made that data centers are a major driving force in the energy transition to renewables...Siemens

With the backdrop of a global energy crisis, it’s perhaps a good time to discuss the real energy cost of data centers, why they’ve become one of the world’s fastest-advancing industries, and how an argument could be made that they are, in fact, a major driving force in the energy transition to renewables.

Firstly, let’s consider their growth. Between 2015 and 2021, internet users have increased by 60%, and internet traffic by 440%, according to IEA data. But despite a rise in workload for data centers of 260% in the same time period, global energy use attributed to data centers has remained relatively flat, representing just a 10% increase.

Decoupling service demand from energy

This decoupling of energy usage from service demand is hugely significant. It’s being driven by rapid innovation of digital technology in data centers, allowing the industry to offset huge increases in demand with improved infrastructure efficiency.

In short, we are building more and more digital capacity, modernizing legacy infrastructure and meeting the growth, but in real terms we’re not using much more energy than we were five years ago.

The real challenge here is how we limit the environmental impact of global internet use. We should be honest; there is an impact, there always will be and we need to continue to use technology and commercial innovation to mitigate it.

Looking at the lifecycle of a datacenter, we see that more than 85% of the carbon impact today comes from operations. There is also certainly an impact during construction and it’s also significant – certainly worthy of mitigation – but net-zero construction will not address the larger part of the challenge: the carbon impact of running the facility for 20 years or more.

Driving the energy transition

Enter the concept of energy mix. A data center’s carbon performance is broadly a function of the energy mix in the location in which it’s operating. There are some exceptions, where operators take the responsibility to generate power on-site using renewables or gas, but largely speaking local grids power data centers.

The data center industry is a major buyer of PPA agreements for renewable energy, and this has a significant impact on the energy mix. In 2021, Amazon and Microsoft were the two largest corporate buyers of renewable energy through PPA; to a degree, the data center industry is helping to drive decarbonization by underwriting a significant proportion of grid-scale, carbon-free energy for industry.

This can catalyze a whole ecosystem at a national level, and also demonstrates to the broader industrial base that critical loads can reliably move to renewables.

Growing adoption of renewable energy – and higher levels of infrastructure redundancy at the IT level – are also leading to new design best practices in data centers. Battery Energy Storage Systems (BESS) are replacing diesel gensets as short-term backup power supply, for example.

With energy markets increasingly interconnected, data centers adopting BESS can generate unprecedented revenues by running in island mode in case of outages (without emitting carbon dioxide from diesel generators) or stabilizing the frequency of the grid.

Beyond carbon reduction

The quest for efficiency is as important as ever, and the discipline of energy management has a massive effect on the operational impact of a data center. Innovation in technology for managing environmental conditions inside a data center is having a significant impact on energy consumption.

We know that 20% to 40% of a data center’s energy use can go towards cooling and ventilation, and this mechanical load is a prime area for optimization through technology. White space cooling is a good example. Our technology for this – a white space cooling optimization solution – uses an advanced machine-learning model to analyze the effect of cooling on specific areas of a data center, creating an influence map to limit energy use to only what’s necessary.

AI engines like this can make a significant difference to a data center’s energy costs; it’s one of the reasons the new Greenergy data center in Estonia is the most energy efficient in the Baltic region.

Building elasticity into data center design is also a key factor in reducing the sector’s energy consumption and cost. Through intelligent design, instrumentation, control and automation, a data center can enable and disable capacity when it’s needed, rather than constantly running circuits and networks with no work to do.

In addition to preventing the over-provision of infrastructure, this is crucial at times of the year where additional capacity is needed to cover short peaks in demand. Black Friday and the Christmas period are a perfect example; with better mechanical, electrical and automation design we can dynamically reduce or increase data center infrastructure resources, enabling them to reliably run closer to their capacity for short periods of time.

The future?

Digitalization and the rise of internet access have delivered significant benefits to humanity, but we should be humble enough to acknowledge there is a sustainability impact. Our mission now is to continually and steadily drive that impact toward zero.

The data center industry has led by example by willingly investing in decarbonization, and has demonstrated that an ecosystem of technology companies can work together to measure, manage and fundamentally change an industry’s approach to energy through innovation. We must continue this pace of investment and innovation if we are to deliver the lowest possible impact of our digital lives on the environment.

Ciaran is VP and Global Head of Siemens’ Datacenter Solutions business, tasked with the continued development of Siemens as a technology provider to the….

Source: How Data Centers Are Driving The Renewable Energy Transition

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Using Hybrid Cloud To Meet The Challenges Of Modernizing Data Architectures

Abstract modern research and data background lines...getty

Cloud computing helps businesses by delivering on-demand computing power and resources swiftly, in many instances minimizing or eliminating the need to buy, install, and maintain new and expensive physical hardware and infrastructure. But at the same time, organizations still need to keep their most valuable data and IT systems within their own on-premises data centers due to key considerations such as security, privacy, safety, and meeting regulatory mandates.

That is why enterprises have adopted a hybrid cloud architecture across their IT operations that provides in many use cases greater software-as-a-service application flexibility, increased cost savings, more efficient processing, and storage capabilities, as well as broader options when it comes to governance and privacy. We see hybrid cloud as integral in the accelerating adoption of data warehouse platforms that function as a containerized application for developing highly performant, self-service data warehouses in the cloud which can be scaled dynamically and upgraded independently.

With hybrid cloud, in alignment with their multi-cloud implementations, organizations can continue to have their own private, on-premises IT infrastructure for their most mission critical data and systems, while also bringing in public cloud resources to advance their hybrid data and data architecture modernization strategies.

The hybrid cloud trend runs in parallel with broader multi-cloud adoption as it allows organizations to use more than one public cloud service, with each public cloud service typically supporting different applications. However, hybrid cloud challenges must be addressed to realize hybrid cloud’s benefits.

Key Hybrid Cloud Challenges and Trends

Organizations are increasingly compelled to distribute and spread data throughout their data centers, private clouds, and public clouds to meet the expanding demands of collecting, storing, analyzing, and managing massive amounts of fast-growing data volumes usually in real-time. Plus, with more data now created and originating outside data centers, they are finding overall data administration more complex and creating new cost containment, performance, and integration challenges.

Today we find most organizations already have a hybrid cloud strategy in place that is increasingly aligned with their broader adoption of multi-cloud, analytics, and AI. As a result, organizations are ramping up their hybrid cloud as well as multi-cloud implementations to augment their on-premises data center and private cloud data warehouses with public cloud platforms.

In addition, legacy data warehouses frequently lack granular control over resources allocated to jobs and tasks as well as the ability to support multiple versions of tools and engines. Accordingly, we see that users, groups, and workloads are required to use the same versions of query engines and tools. Such interdependency muddles operations and the upgrade process and can suppress innovation, especially across hybrid cloud environments.

Why Hybrid Cloud? Attaining More Hybrid Data Optimization and Flexibility

One key benefit of hybrid cloud is that it can provide more technological and process freedom for businesses. Instead of being limited by existing on-premises data center capabilities, using hybrid cloud allows organizations to quickly respond to their unique business needs by accessing additional compute resources through public cloud platforms, creating more data workload optimization and management flexibility.

The value of this option is that public cloud services can be available at the push of a button and configured automatically according to customer data workload demands and policies, including elastic up/down scaling capabilities. This kind of flexibility and measurable cost structure is especially critical today, as intricate macroeconomic conditions continue to challenge businesses around the world.

By having a hybrid cloud strategy, growing businesses can move quickly on their topmost compute needs rather than having to wait until costly infrastructure is budgeted, planned, and eventually installed. Opting for hybrid cloud can mean optimizing compute resources in areas such as streamlined upgrade processes and operations, accelerating time to market and innovation, as well as keeping operational costs manageable.

Hybrid Cloud Helps Address Data Storage Complexities

Hybrid cloud also enables organizations to make better business decisions by giving them a more flexible storage framework. Today, organizations typically store data in individual repositories maintained for each data center, creating a complex and fragmented data storage system that leads to bottlenecks and inefficient data operations. This is why we see organizations rapidly adopting the data lakehouse across their hybrid cloud architecture.

The data lakehouse blurs the line between structured and unstructured data, enabling organizations to store all types of raw data in one location, while still having a storage layer on top to provide transactional views of data and structured data management and analytics when needed. And by transitioning to hybrid cloud, enterprises can attain advantages through being able to bring together and pool all those isolated repositories together to create a unified data lakehouse as well as distributed data warehouse implementation.

This hybrid data approach allows access to more insights and information through streamlined access and administration of their overall data. While we are seeing versions of this from a number of data platform providers such as AWS, IBM, Oracle, Teradata, and Snowflake, a robust example of what I am speaking about is the Cloudera Data Platform (CDP).

CDP provides its users with a unified platform that offers portable, interoperable data analytics essential to optimizing the entire data lifecycle and more efficient management of distributed data. This applies to any data running across the organization’s hybrid cloud including public cloud, on premises, and edge environments. CDP’s common security, governance, metadata, replication, and automation provided by Cloudera Shared Data Experience (SDX) also enables the platform to operate as an integrated system.

Different vendors each have slightly different approaches to offering the tools and technology required for enterprise data leaders. It’s important for enterprises to carefully select the right platform to meet its data and analytics needs, but the benefits of a hybrid data approach should be a key consideration.

Flexibly pooling is another feature critical to a hybrid data strategy. This feature pools critical business data together, regardless of where it is physically stored, and is another major benefit of the hybrid cloud approach to break down data silos within organizations and deliver unified data management. Improved data management delivered by hybrid cloud is a huge boon for enterprises that are seeking to modernize their aging business operations.

Hybrid Cloud Helps Organizations Improve Business Outcomes

Immense flexibility is one of the greatest strengths of hybrid cloud. Growing businesses, including small to mid-sized businesses (SMBs) and large enterprises, can be thwarted when their internal IT operations are unable to meet their hybrid data requirements. But by being able to flexibly access power, performance, storage, and networking resources, organizations can react more quickly to growth opportunities and improve business outcomes.

Another benefit of hybrid cloud is that it is not an either-or decision. For many companies, moving their operations to the cloud can be worrisome due to factors such as regulatory and legal concerns. With hybrid cloud, that either-or decision is less onerous since it can allow organizations to use hybrid cloud according to their technical and business priorities.

Another part of the hybrid cloud value proposition is that going the hybrid cloud route means that organizations can avoid vendor lock in. Organizations opting to embrace a hybrid cloud strategy can gain more flexibility in balancing and optimizing their on-premises and public cloud data resources. Workloads and data can be distributed across public cloud platforms, allowing for more choice based on both IT operational and business priorities.

Other Hybrid Cloud Benefits for 2023 and Beyond

The popularity of hybrid cloud is continuing to gain steam in post-pandemic 2023 as organizations are looking at a wide range of strategies, including hybrid cloud, to boost their IT operations and modernize their data platforms to improve competitiveness and better respond to uncertainties such as supply chain issues and macroeconomic pressures.

By adopting hybrid cloud, organizations can be better protected against downtime and data loss related to data center disruptions as well as from non-data center sources. With a hybrid cloud approach, organizations can improve the load-balancing and distribution of their critical operations during troubleshooting cycles.

As cloud computing continues to evolve and deliver more data management demands hybrid cloud will also continue its own unique growth by meeting data workload optimization goals across on-premise, public cloud, and edge environments, allowing organizations to avoid the fragmentation and limitations of a single environment approach and potentially debilitating trade-offs across any of their data realms.

By bringing both essential services together for customers, hybrid cloud is solidly positioned to deliver the flexibility, cost savings, security, and on-demand compute power needed by today’s IT organizations.

I am a principal analyst of Futurum Research and CEO of The Futurum Group. I spend my time researching, analyzing and providing the world’s best..

Source: Using Hybrid Cloud To Meet The Challenges Of Modernizing Data Architectures

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Presentation: Resilient Real-time Data Streaming Across the Edge and Hybrid Cloud InfoQ

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How Data Is Helping To Resolve Supply And Demand Challenges

Perhaps one of the most sweeping outcomes of the 2020 pandemic has been its effect on the global ... [+]getty

Perhaps one of the most sweeping outcomes of the 2020 pandemic has been its effect on the global supply chain. From consumer goods to raw materials, products are either unavailable for purchase or take excessively long to reach their destinations. Even common grocery items like baby formula are becoming hard to find, as reported by CBS in an April 2022 report.

Analysts predict that the major supply and demand crunches will have less impact in the future, per CNBC. However, businesses and buyers aren’t content to wait until early 2023 to feel less of a pinch. They want answers now, and they’re getting them in the form of innovative uses of data and technology.

As it turns out, data—when utilized thoughtfully—has value in smoothing out supply chain hiccups. Below are several examples of how data is being tapped to tackle post-pandemic procurement and delivery issues.

1. Data is revealing where companies should focus their resources to satisfy customers.

Nothing is as frustrating for shoppers as being unable to get what they want. To better allocate resources and anticipate needs, some brands are leveraging real-time data analytics. Understanding in-the-moment demands enables teams to pivot and respond.

An example of this type of process is Chipotle’s use of Semarchy’s data management tool. After “The Great Carnitas Shortage of 2015,” the company realized that it needed to make adjustments to its supply chain. By aligning operations, communications channels, and ordering platforms, Chipotle found it could more easily stay ahead of supply chain issues. This has helped the company meet customer experience assumptions and avoid snags.

2. Data is reducing friction from delays in service industries.

Many services that followed more traditional in-person models were forced to embrace digitization during Covid. Many found that their internal processes weren’t ready for the challenges or consumer expectations of online transactions, though. For instance, some small to mid-sized financial lenders realized that they didn’t have the workflows or tools to streamline application processing. As a result, they risked falling behind their bigger competitors.

Data-driven software solutions from entities like publicly traded MeridianLink have helped fill this gap. MeridianLink, valued at over $2 billion, designed a data-rich platform to gather and process loans rapidly. Their platform has enabled nearly 2,000 financial institutions to swiftly turn around consumer loan applications without causing friction. Due to the improvement in efficiency backed by data, banks, credit unions, and mortgage lending houses can keep pace. In today’s strong real estate market, that’s a huge supply and demand advantage.

3. Data is freeing employees to concentrate more fully on supply chain management.

Overcoming major supply chain hurdles can only happen when thought leaders have the bandwidth to brainstorm. Regrettably, far too many of them are bogged down by repetitive tasks. If those tasks can be automated, they can take up far less time. The result is teams who can concentrate on solving high-level concerns.

For instance, consider digital pioneering company IBML and its Cloud Capture software. The software captures, identifies, and classifies information from any source such as a complex invoice or a standard customer return form. Once appropriately logged, the information becomes available to authorized users. This type of consistent data capture facilitates a less clunky document processing. It also frees executives, managers, and supervisors to divert attention toward pressing supply chain concerns.

The supply chain conundrum won’t be fixed overnight or even in a few months. Yet fresh, data-driven solutions can help companies undergo fewer stressors as a result of supply and demand interruptions.

https://i0.wp.com/onlinemarketingscoops.com/wp-content/uploads/2023/01/Serenity-Gibbons_avatar_1525181923-400x400-1.jpg?resize=64%2C64&ssl=1

Source: How Data Is Helping To Resolve Supply And Demand Challenges

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Harnessing The Power of Data Can Grow Business Revenue By Up To 9.5%

Image credit: Kaleidico

Businesses in Australia and New Zealand that use data effectively can, on average, increase their annual revenue by 9.5%. This translates to an additional $38 million in annual revenue for large organisations in Australia with more than 200 employees.

According to a new AWS report prepared by Deloitte Access Economics, organisations with more than 100 employees improved their data capabilities in the previous year, with 34 per cent achieving Advanced or Master levels of data maturity, compared to 16 per cent in 2021.

Almost half of the organisations polled (48 per cent ) stated that effectively capturing and analysing data can lead to increased productivity, followed by improved customer experience (45 per cent ) and lower operating costs (42 per cent).

Finance and insurance companies scored the highest on the data maturity scale, with 50 per cent achieving Advanced or Master status, followed by manufacturing (45 per cent ) and information, media, and telecommunications (33 per cent ).

On the other hand, construction, healthcare and social assistance, and retail trade organisations have the lowest data maturity levels, with less than 20 per cent of surveyed organisations in these industries achieving Advanced or Master levels of data maturity.

Unusual challenges

While improving data maturity benefits businesses, large organisations in Australia and New Zealand continue to face challenges in climbing the data maturity ladder, with 42% of organisations achieving Basic and Beginner data maturity.

The main barrier cited by organisations to use data and analytics was a lack of funding (44 per cent ), which has been exacerbated by COVID-19, with 49 per cent of respondents reporting that competing priorities have resulted in fewer resources for data and analytics since the pandemic’s onset. Furthermore, 37 per cent of organisations cited poor data quality as a barrier to businesses adopting more advanced data analytics.

“We are excited to see that more organisations have advanced their data capabilities, which will help them to drive productivity, and create a positive impact on the economy while delivering significant financial returns for their business,” said John O’Mahony, partner at Deloitte Access Economics.

“Investing in cloud solutions will help businesses further their data capabilities and leverage advanced analytics tools such as artificial intelligence, machine learning, and the Internet of Things to achieve data-driven insights.

In fact, businesses that already use the cloud are 71 per cent more likely to have invested in artificial intelligence and machine learning capabilities versus organisations using on-premises data storage. To increase productivity and innovation, organisations should have a clear and practical roadmap for advancing on the data maturity ladder, invest in attracting and retaining talent, and leverage the right technology to reap the full benefits.”

According to the report, one-third of Australian and New Zealand organisations (35 per cent ) cited a lack of skilled resources as a barrier to developing their data and analytics capabilities. To improve data maturity, 33 per cent of surveyed organisations prefer to upskill their current employees, followed by outsourcing to other organisations (24 per cent ), and hiring skilled staff (24 per cent ).

“Data can be an invaluable source of growth for organisations in Australia and New Zealand. The key is recognising its inherent value, analysing it effectively, and building a data-driven culture.

“No matter what stage organisations are in their data journey, AWS is committed to helping customers leverage the scalability, cost efficiency, and security of the cloud to scale their data projects and unify their data to drive productivity and innovate on behalf of their customers,” said Rada Stanic, chief technologist at AWS in Australia and New Zealand.

“Organisations will also benefit from building data skills within their teams, which may involve upskilling current staff through on-the-job training and training courses or collaborating with organisations such as our extensive network of AWS Partners.

“As organisations increase their data maturity, it will transform how they solve problems and build customer experiences, leading to breakthroughs in all industries, including healthcare, finance, retail trade, and manufacturing operations.”

.
Related contents:
NetApp BlueXP: the unified data experience for the evolved cloud Data Centre News Magazine

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Accelerate Customer Success And Brand Loyalty With Data

 

Recently, financial services and telecommunication providers have experienced significant challenges. They encountered digitally savvy competitors, increased expectations for online customer service (pre-and post-pandemic), and higher case volumes of agitated customers. Meanwhile, remote work affected the productivity of service staff, daily operations, and more. But they aren’t the only service-driven industries reacting to disruption and increasing consumer expectations.

Quality of service can mean the difference between keeping or losing customers, so organizations need to examine how, where, and when they engage with them. A single customer view looking at experiences across service, marketing, and commerce is essential. Unfortunately, many businesses struggle with disparate data and disconnected applications that obfuscate that view. That means service fulfillment and relevant technologies must step up to help organizations deliver more consistent, seamless, swift, and personalized experiences for customers who agree “good enough” service won’t suffice.

Transforming your service strategy and operations with data leads to better business results. A data-driven service approach is making a positive difference in the financial services and telecommunications industries and can also help your business achieve these benefits:

1. Enhanced, personalized customer experiences across all channels

2. More productive, empowered service agents influencing success

3. Increased efficiency, prioritization, and automation throughout service operations

4. Reduced IT complexity and costs leading to higher margins

The Risks Of Poor Customer Experience

If customers experience less-than-stellar service, there’s a greater risk of switching to competitors. In fact, 80% of consumers will switch after just one poor experience1—driving businesses to compete on more than price and choice. There are other serious downstream effects: increased customer churn, diminished reputation and trust, stalled growth, and attrition of employees, agents, or leadership.

Business circumstances can change instantly. Customer interactions can portend issues with serious implications (i.e., costly compliance or regulatory fines or sharp declines in satisfaction scores). Each problem puts a company at greater risk for stolen market share you can’t afford to lose.

With a commitment to data-driven and digitally driven service operations—from the contact center to the field—you are better positioned with customers and can reduce or eliminate most risks. In digital environments, engagement barriers are often reduced or eliminated allowing customers to gain more service access, and brands to gain increased opportunities for better customer service delivery.

How To Unlock Data And Transform Customer Service End-To-End

Transitioning to data-driven service starts with leaders’ commitment to building and maintaining a cohesive data strategy spanning people, processes, and technologies that support business resilience and future growth. The next step is unifying data sources with intuitive and flexible analytics to achieve a single source of truth.

When you infuse analytics across service operations (and the business), agents and leaders gain that invaluable, complete customer view to impact personal, swift, effective service, and transform the call center from a siloed operation to an agile changemaker that affects marketing, sales, product development, and more. Tangible results include:

For financial services…

· Up to 31% increase in customer satisfaction

· Up to 29% increase in agent and user productivity

· Up to 27% reduction in customer retention

For telecommunications…

· 37% faster time to resolution

· 55% decrease in cost to serve

· 53% increase in average revenue per user (ARPU)

Let’s examine the four benefits of data-driven service and relevant resources as you focus on protecting the bottom line.

1. Enhanced, personalized customer experiences across channels

 

Customers are precious business assets, so carefully nurturing and protecting each relationship is key. Regardless of how they engage, each expects a personal interaction resulting in swift resolution. Maybe there’s a service issue and they made several attempts to get help. Or maybe there’s an opportunity to upsell their existing products and services. Unfortunately, the siloed data systems sitting inside and outside of your organization’s customer relationship management (CRM) system make it more complicated to deliver best-in-class service.

Data, analytics, and AI are foundational to digital enterprises where functional insights drive positive business outcomes. According to McKinsey, many companies using data-driven practices report above-market growth of +15%2—especially in the B2B market, but the same practices apply to B2C enterprises.

Charles Schwab relies on data to answer financial planning questions, improve customer experiences, drive operational leverage, and more. Shifting from a static to dynamic customer view with Tableau helps their call centers, branches, and headquarters staff see data errors or inconsistencies and discover insights to make product adjustments so clients’ money goes further and their engagement stays positive.

“Now those receiving and handling the customer calls are making their own impact, helping maintain higher customer satisfaction levels. They’re transitioning into a role where they’re looking at the data behind customer engagement.” Senior Data Analyst, Charles Schwab

2. More productive, empowered service agents influencing success

When agents shift from system to system trying to access information and manually perform processes, customers feel and react to the effects of disengaged communication, fragmented experiences, and long wait times. They want meaningful interaction from service staff seeing a complete view of customer and business data to influence smarter responses and actions.

As noted in the “State of Service” report from Salesforce Research, 91% of customers say they’ll make another purchase if the service is good1. With intuitive analytics, your agents can access and catalog data, then analyze it for valuable and trusted insights, and also share it with others to act in customers’ best interests. Access to pre-built dashboards like Tableau’s Call Center Accelerator gives your service team deeper views of overall service levels and helps all business leaders analyze agent performance—good and bad. Feel confident knowing data is at their fingertips to make better, quicker decisions in all customer interactions.

workforce

Thousands of customers depend on internet, cable, and phone providers to deliver reliable service. When customers use these services, ample data is created and can be collected. Verizon analyzes it with Tableau to ensure customers are satisfied, problems get handled, and departments like marketing or call centers can see patterns and behaviors to improve service. A Center for Excellence is critical as they perform analyses, support data management, and deliver insights to stakeholders for improved decision-making.

“Insights from dashboards help us optimize call center operations to reduce multiple customer calls. Monitoring these timely dashboards shows us that as the resolution rate and satisfaction index of customers go up, volumes for calls and dispatches—key cost drivers—go down. Senior Manager of Data Analytics, Verizon

3. Increased efficiency and prioritization of more complex cases throughout service operations

Before 2020, contact centers could manage traditional customer demand and service spikes. But these spikes are usually short-lived and predictable versus the unforeseen changes and new expectations growing from digital engagement and the pandemic. With a smaller workforce also handling call center cases due to downsizing, data-driven technologies that support efficiency, prioritization, and automation are necessary to the experience equation—particularly for large, dispersed enterprises.

Today, interactive analytics with built-in AI help your staff confidently understand all customer data and service performance in their workflows, which helps them be more predictive and proactive when choosing how to act on behalf of customers. AI-powered analytics also fuel speed to insights for better contact routing, improved call center and field staff capacity, and automaton of more cumbersome, time-intensive processes.

For example, a single dashboard displaying call center KPIs in Tableau can help management see and know where to optimize operations—from streamlining or eliminating multisystem dependencies to automating low-value processes that hamper productivity and communication. This frees up service staff to help more customers and address more complex cases.

Inconsistent, fragmented data at Telstra made pipeline, revenue forecasting, and quicker delivery of new technologies to customers difficult. But the combination of Sales Cloud and CRM Analytics transformed how they deliver customers new solutions and measure business value. Sales Cloud provides a complete view of enterprise customers and enables sales to forecast and collaborate for more meaningful interactions. CRM Analytics also helps line of business managers and service staff stay focused on how to achieve their business KPIs.

4. Reduced IT complexity and costs leading to higher margins

By using a self-service solution like Tableau, gain highly configurable, manageable, and customizable analytics to increase performance clarity and create faster, more accurate business decisions or predictions. IT is no longer a bottleneck, and service operations staff, business analysts, and executives have a clear understanding with direct visibility of the customer journey and what factors extend or detract from success.

This can translate to better planning with staffing, forecasting, and seasonality to reduce service costs and maintain high-quality, year-round customer engagement.

Growing through mergers and acquisitions, strategic data became vital to business operations for JPMC. IT made data easily accessible for business teams through Tableau so domain experts could keep up with industry changes, regulations, and risks, and optimize for customer success. For example, marketing operations analyze the customer journey to inform promotional materials and products like the mobile application and branch managers examine retail data to implement better banking experiences.

“We put Tableau on our robust customer data sets…to quickly ask questions like ‘How many customers have a Freedom and a checking account, and use the mobile wallet.’ ” Director of Analytics, JPMorgan Chase

Embrace Data-First Service And Win With Customers

In the competitive, highly regulated environment facing financial services, telecommunications, and other industries, leading with data-first service creates a winning position. Grow and protect valued customer relationships with the help of a world-leading analytics solution like Tableau combined with Salesforce, the leading CRM, to connect with customers in more meaningful ways across every channel—every time.

 

Allison (Ally) Witherspoon Johnston, Senior Vice President, Product Marketing, Tableau. Allison leads the Tableau product marketing team and has worked at Salesforce

Source: Accelerate Customer Success And Brand Loyalty With Data

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