❯

Drive contact center success with data

Drive contact center success with data It relies entirely on accurate information for effective communication with customers. Data provides a foundation on which all companies are run.

The extraordinary circumstances of the last two years created radical shifts in customer demands and expectations. To retain customers, stay competitive, and build brand loyalty, CSPs must make the customer experience their top priority. Empower your contact centers with data so they can respond more quickly, accurately, and intelligently, to deliver greater customer satisfaction.

❯

The impact of data literacy on organizations

The impact of data literacy on organizations The survey found that organizations that invest in data literacy and upskilling at scale—especially those with more mature initiatives—experience powerful benefits like improved decision-making, innovation, productivity, customer and employee experience, and more.

To explore enterprise data literacy, upskilling, and related organizational issues, challenges, and benefits, we commissioned Forrester Consulting to conduct surveys with over 2,000 decision-makers and employees in 10 countries. The survey found that organizations that invest in data literacy and upskilling at scale—especially those with more mature initiatives—experience powerful benefits like improved decision-making, innovation, productivity, customer and employee experience, and more.

Both decision-makers and employees in various departments consider basic data literacy as the most important skill for success. While everyone agrees that data skills are important for workforce success, there is disagreement on whether or not employees are being adequately trained. Forrester found a gap between the need for data skills training and implementation—which is harming organizations’ competitiveness.

❯

Building a data fabric for analytics with

Building a data fabric for analytics with Building a data fabric for analytics with Tableau … The capacity of data fabrics to unlock data and connect applications is central to the future of work and …

The capacity of data fabrics to unlock data and connect applications is central to the future of work and underpins transformation initiatives, powering everything from increased automation to digital‑first experiences. Organizations are pivoting to this composable IT model, empowering more people—developer and non‑developer alike—to connect data and applications in a secure and frictionless way.

❯

Manufacturers: Moving from Complexity to Clarity

Manufacturers: Moving from Complexity to Clarity Moving from Complexity to Clarity. Leaders in manufacturing organizations are under pressure to create business value. You need to identify risks in complex supply chains, achieve sustainability goals, enable your teams to succeed, and create a customer experience that nurtures loyalty.

Leaders in manufacturing organizations are under pressure to create business value. You need to identify risks in complex supply chains, achieve sustainability goals, enable your teams to succeed, and create a customer experience that nurtures loyalty.

But how can you make smarter decisions to overcome your four manufacturing needs without creating extra complexity? In this whitepaper, you’ll learn how leveraging your data creates the free flow of facts you need to make critical and profitable decisions.

You’ll discover how business leaders at world-class manufacturing organizations are using data and analytics to overcome their key challenges—reducing risk and cost whilst driving innovation.

❯

4 Ways Data is Transforming the Industry

4 Ways Data is Transforming the Industry See Table of Contents of related articles. Digital transformation has placed data at the center of organizations of all sizes, across all industries, in both public and private sectors.

Competitive Advantage of Data Analytics

Cost Reduction…

Better Decision-Making…

Improved Products and Services.

Like it or not, manufacturing is moving faster and leaner as dated, status-quo business systems fall to the wayside

More than ever the manufacturing industry must organize and understand massive amounts of data from many systems to drive operational efficiencies, higher levels of service, and support.

Having the ability to explore the impact and interplay across production efficiency, product quality, customer demand, and service excellence simply isn’t possible without big data and meaningful analytics.

Here are four ways leading manufacturers are revolutionizing their industry with data:

1.Improving Production, Plant Performance and Product with Self-Service Analytics

2.Enhancing Sales and Operations Planning with Data blending and Forecasting

3.Mobilizing Supply Chain with Real-time Analytics

4.Listening, Interpreting and Reacting to Customer Feedback Faster

1. Improving Production, Plant Performance and Product with Self-Service

People within manufacturing have traditionally accessed data insights via static reports from enterprise applications and business intelligence tools, all managed and used only by the IT department. This old way, predominantly designed and built in the 1990s, is generally complex, inflexible, and time-consuming.

Because the best analytics implementations are user-created dashboards running on top of IT-managed infrastructure, optimization for self-service is key.

Self-service analytics will empower individual manufacturing employees and entire organizations alike to see and understand data across the demand chain, within production operations and throughout the entire service life cycle.

With added visibility into operational performance, employees will be able to monitor data throughout the entire organization and apply it to strive for continuous business and process improvements via the philosophies of six sigma or lean principles.

Self-service also supports the implementation of the DMAIC framework to support a data-driven improvement cycle allowing an individual to explore and identify the root cause of product defects or bottlenecks.

Supply chain analytics: Deliver more with less

Supply chain analytics: Deliver more with less supply chain analytics gives you visibility across your entire supply chain by integrating data from your existing systems to create a real-time…

Navigating today’s global supply chain is a series of complex, ongoing challenges. But forward-looking companies are finding that the challenges bring opportunities to optimize their supply chain—no matter the scale—and minimize the impact of disruptions.

Tableau supply chain analytics gives you visibility across your entire supply chain by integrating data from your existing systems to create a real-time, single source of truth. You can securely share and consume insights internally at all levels of your organization and externally with your supply chain partners.

How You Can Put Data at the Center of Every Decision

How You Can Put Data at the Center of Every Decision Any decision you make needs to start with your business goals at the core. So, start by asking yourself: What goals do you want to improve?

The key to making better decisions is to be data-driven. When you prioritize data-first thinking across your organization and give teams what they need to be successful with data, you’ll kick off a chain reaction that boosts efficiency, effectiveness, and bottom-line results.

Explore the four steps to putting data at the center of every decision and start making an impact with data:

1.Use data to identify business objectives

2.Use data to minimize complexity and accelerate understanding.

3.Use a data-first mindset across every team and workstream.

4.Use data to communicate more effectively.

Get the tools to make better decisions and learn how to use data:

Identify trends and opportunities

Create meaningful benchmarks

Predict with greater accuracy

Understand where course corrections should be made

Build consensus

Tell a persuasive story to your team and shareholders

BARC Data Preparation Study

BARC Data Preparation Study A survey-based BARC study into the use of technologies for data preparation. Examines drivers, use cases, benefits, challenges and organizational issues.

There is a high potential for creating value from the use of data. Being able to use it correctly requires an acute awareness of how to handle data and brings with it plenty of changes in terms of organization and technology. Business users demand a fast and flexible analytical landscape from their IT departments. A lack of resources, a lack of flexibility, and complex, historically grown systems are standing in the way of efficient and agile delivery. Smart data management is key for business success, especially in the field of digitalization where data and analytics are of increasing importance and have a growing influence on the business. Unfortunately, many companies are still learning this. For a long time now, data management has ceased to be only an IT area of expertise. Traditional IT tasks related to data management are increasingly being taken over by business departments to ensure timely completion. First and foremost comes data integration and the provision of data.

Deployment scenarios for data preparation range from self-service BI tools directly accessing operational or analytical systems to specialized self-service data integration (DI) tools for supplying analytical models or explorative sandboxes with data. Self-service data integration tools enable business users to prepare relevant data in a flexible and self-reliant manner to be used for analysis. The self-service trend in DI has already reached the market, forcing leading DI vendors to offer options and interfaces as well as governance frameworks for data integration by business users. In addition, BI vendors (specialists and BI generalists) are adding data preparation capabilities to their analysis and data discovery tools.

This places additional strain on companies’ BI organizations and BI governance as the responsibility for analytics becomes increasingly scattered. It is also a challenge for IT departments – who are in charge of operating the software tools, and application servers and fulfilling data needs – as they have less control over user behavior. Therefore, striking the right balance between flexibility and data governance is a crucial element in the success of data preparation.

This study clearly demonstrates the benefits, timeliness, and relevance of data preparation for analytics. It shows how and by whom data preparation is being driven and how the balancing act between governance and flexibility can be achieved by specifying the requirements for data preparation governance. In this BARC study, we also show how data preparation is used today, which challenges need to be overcome, and in which organizational framework this takes place.

10 ways to add value to your dashboards with maps

10 ways to add value to your dashboards with maps In this whitepaper, we’ll share 10 tips for improving the analytic and aesthetic value of maps for your dashboards.

In this post, we’ll share 10 tips for improving the analytic and aesthetic value of maps for your dashboards.

Context is key…
Let the data stand on its own. …
You don’t need a legend on your map* …
Use a map as a filter. …
Use highlighting actions. …
It’s all about color for design and data.

The most effective data visualizations balance function and design. And because many analytics projects involve spatial data, it is critical to know how to strike this balance with maps. In this whitepaper, cartographer Sarah Battersby shares ten tips for improving the analytic and aesthetic value of dashboards with maps.

Advances in the Era of Smart Analytics

Advances in the Era of Smart Analytics Get all the metrics and dimensions you need from your favorite marketing platforms. KOinetmedia is the easiest way to move your marketing data to any destination. Custom visualizations. High-quality connectors. Be a smarter marketer. Free trial. Cost-efficient tool.

Constellation Research is a Silicon Valley-based technology research and advisory firm specializing in digital transformation and disruptive technologies. In this recent report, author Doug Henschen, VP, and Principal Analyst explore the evolution of self-service BI and the rise of smart analytics in the market, examining four key areas in which Tableau continues to invest: Data prep, data analysis, and discovery, natural language interactions, and predictive analytics. With a greater variety of data and increased demand to use it, Tableau is not just out to democratize data, but to make complex analyses of it simpler—speeding up insight to action. Technologies like machine learning, natural language processing, and smart algorithms (all under the umbrella of smart analytics), are a great opportunity for the world of analytics to take the next big leap. Tableau is at the forefront of this new era pushing the boundaries of what’s possible to help more people than ever before see and understand data.