Digital disruption, economic instability, political upheavals and skills shortages have all at some point in the past 24 months been blamed for business failure, or at the very least, lost profitability and earnings.
It’s perhaps not a huge surprise that a Gartner CEO survey on business priorities revealed that digital business is a top priority for next year. Survey respondents were asked whether they have a management initiative or transformation program to make their business more digital. The majority (62 percent) said they did. Of those organisations, 54 percent said that their digital business objective is transformational while 46 percent said the objective of the initiative is optimisation.*
So, for businesses it’s a case of learning to evolve and be agile, to use technology to help compete more efficiently and not fall victim to inertia. As businesses become increasingly dependent on the insights from data analytics and face-up to competition fuelled by the 24/7 society of in
Organizations are charging ahead with investments in cloud and analytics to deliver agility, scalability and cost savings. With computing power advancements and continuous growth of data, cloud provides the elastic workloads and flexibility required for modern business. However, the environment of flexibility and choice that cloud provides also creates complexity and challenges.
In this white paper, learn how organizations are applying expertise and using the latest methods to move analytics to the cloud, including:
• Why are organizations moving analytic work to the cloud?
• What are the key challenges and misconceptions?
• How do IT leaders provide choice while maintaining control?
Envision this situation at a growing bank. Its competitive landscape demands an agile
response to evolving customer needs. Fortunately, analytically minded professionals in
different divisions are seeing results that positively affect the bottom line.
• A data scientist in the business development team analyzes data to create customized
• experiences for premium customers.
• A digital marketer tracks and influences the customer journey for prospective
• mortgage customers.
• A risk analyst builds risk models for the bank’s loan portfolios.
• A data analyst examines data about local customers.
• A technical architect defines a new system to protect bank data from internal and
• external cyberthreats.
• An application developer builds a new mobile app for online customer portfolio
Between them, these employees might be using more than a dozen packages for
analytics and data management.
Over the last decade, the enterprise analytics landscape has dramatically
transformed. Vendors have come and gone, and platforms have
continually expanded their offerings to include new functionality and
keep pace with the demands of the businesses they serve. Originally
envisioned as an IT-centric tool for enterprise reporting, analytics today
has evolved into a business solution—empowering a range of users
across every line of business, including front-line employees, field
personnel, and executives.
The rise of self-service analytics over the past decade has played a key role in promoting a data-driven mindset
within every business function. However, this practice is limited to a skilled few. The vast majority of business
professionals lack the time, analytical skills, or inclination to conduct their own analyses, and fail to effectively use
analytics on a day-to-day basis. The result? Despite decades of investments, BI adoption at most organizations
remains at 30%.
The failure of e
Today, despite massive investments in data, IT infrastructure,
and analytics software, the adoption of analytics continues to lag
behind. In fact, according to Gartner, most organizations fail to hit
the 30% mark. That means that more than 70% of people at most
organizations are going without access to the critical information
they need to perform to the best of their abilities.
What’s stopping organizations from breaking through the 30%
barrier and driving the pervasive adoption of intelligence? Simple.
The majority of existing tools only cater to users who are naturally
analytically inclined—the analysts, data scientists, and architects
of the world. The other 70%—the people making the operational
decisions daily within a business—simply lack the time, skill, or
desire to seek out data and intelligence on their own.
HyperIntelligence helps organizations operationalize their
existing investments and arm everyone across the organization
with intelligence. Whether
THe use of analytics has exploded across business, and the value it already has delivered has heightened executives' expectations. Now data can be processed in real time to meet a constantly widening range of analytic needs. How your organization utilizes them in the next decade will be essential to your success.
Data and analytics are the key accelerants of digitalization, transformation and “ContinuousNext” efforts. As a result, data and analytics leaders will be counted upon to affect corporate strategy and value, change management, business ethics, and execution performance.
The oil field is being dynamically transformed through the connective power of the Internet, the advancements in remote connected sensors, and the possibilities of machine learning and artificial intelligence (AI).
As the quest for hydrocarbons and alternative energy sources extends into deeper and harsher environments, operators, service companies, and asset owners are leveraging technology advancements to ensure their employees are safer, their fields are more productive, and their capital assets are operating at peak efficiency.
TIBCO Data Virtualization is a proven approach used by four of the top five integrated energy companies to deliver more analytic data sooner from across upstream and downstream operations. Specific use cases described include: •? Offshore Platform Data Analytics •? Well Maintenance and Repair •? Cross Refinery Web Data Services •? SAP Master Data Quality If you are an energy company facing similar data and analytic challenges, consider TIBCO Data Virtualization.
Endesa is a leading energy company in Spain and Portugal with around 10,000 employees, providing services for over 11 million customers. The company is committed to spreading a more sustainable energy culture and strives to be at the forefront of the technological transformation of the energy industry. To meet this goal, Endesa joined the Enel Group in 2009, a multinational energy company and leading integrated operator in the global electricity and gas markets, with a particular focus on European and Latin American markets.
"Como vamos usar todos os dados da rede inteligente?"
Produtores, distribuidores e consumidores de eletricidade em quase todos os países desenvolvidos estão se perguntando isso. Os dados gerados por medidores inteligentes, os dispositivos conectados, os geradores de energia, barragens hidrelétricas, fazendas solares e consumidores cada vez mais sofisticados têm o potencial de melhorar consideravelmente a confiabilidade da geração, gerenciamento, armazenamento e da distribuição de energia.
A análise avançada pode ajudar a alcançar todo esse potencial. Mas, como? Ela desempenha um papel importante nas empresas de serviços que buscam transformar dados em dinheiro, por meio da análise das informações acumuladas para melhorar a gestão da demanda, a alocação de ativos e de pessoal, a previsão de demanda e a manutenção preditiva e preventiva. De fato, a análise está alimentando essa transformação do setor.
“¿Cómo utilizaremos todos los datos de la red inteligente?”
Los productores, distribuidores y consumidores de electricidad de casi todos los países desarrollados se están haciendo esa pregunta. Los datos producidos por los medidores inteligentes, los dispositivos conectados, los generadores de energía, las presas hidroeléctricas, las granjas solares y los consumidores más sofisticados, tiene el potencial de mejorar considerablemente la confiabilidad de la generación, gestión, almacenamiento y distribución de electricidad.
La analítica avanzada puede ayudar a alcanzar todo ese potencial. Pero, ¿cómo? Tiene un papel de gran relevancia en las empresas de servicios que buscan convertir los datos en dinero mediante el análisis de la información acumulada para mejorar la gestión en el lado de la demanda, la asignación de recursos y de personal, pronosticar la demanda y el mantenimiento preventivo. De hecho, la analítica está impulsando esta transformación de la industria.
In this e-book, you’ll discover
1. How next-generation cloud technologies such
as customer journey mapping platforms and
advanced analytics are poised to transform the
2. The top operational and technical challenges
that next-generation cloud technologies tackle.
3. Examples of how companies can tap into
next-gen cloud technologies to elevate the
Let’s face it: in today’s B2B landscape, the buyers call the shots. Buyers today are proactive, research
their own options, and often include many decision makers rather than just one who can be wooed on
a golf course or over dinner.
So, where does that leave the salesperson? To succeed in this new landscape, sales professionals must
understand how the buyer’s journey has changed and unlock the advantages that data analytics and
statistical modeling can offer. Sales and marketing teams must also learn how to align their efforts to
present a truly coordinated experience.
Read this paper to learn how to take advantage of untapped opportunities for helping sales teams
evolve in today’s buyer-empowered landscape.
While interest in Machine Learning/Artificial Intelligence/ (ML/AI) has never been higher, the number of companies deploying it is only a subset, and successful implementations a smaller proportion still. The problem isn’t the technology; that part is working great. But the mere presence and provision of tools, algorithms, and frameworks aren’t enough. What’s missing is the attitude, appreciation, and approach necessary to drive adoption and working solutions.
To learn more, join us for this free 1-hour webinar from GigaOm Research. The webinar features GigaOm analyst Andrew Brust and panelists Jen Stirrup, Lillian Pierson, and special guest from Cloudera Fast Forward Labs, Alice Albrecht. Our panel members are seasoned veterans in the database and analytics consulting world, each with a track record of successful implementations. They’ll explain how to go beyond the fascination phase of new technology towards the battened down methodologies necessary to build bulletproof solutions th
Published By: FICO EMEA
Published Date: Aug 30, 2019
Telecommunications companies lost more than $29 billion to consumer fraud in 2017 globally (1.27% of their revenues). The largest and most advanced communications service providers (CSPs) have sophisticated fraud detection systems and processes in place, but those organizations are now questioning their fraud readiness. Are they doing enough? Fraudsters may be individuals or increasingly sophisticated criminal networks. They constantly develop new methods and target new lines of business
Read this interview where Anat Hoida, Head of the FICO’s Telecom Practice in Europe, Middle East, and Africa, discusses the impacts of the evolving spectrum of fraud risks on the growth and competitiveness of CSPs globally.
Published By: Genesys
Published Date: Jun 19, 2019
Successfully managing a contact center requires a collaborative, multidisciplinary approach to handle a broad range of operational and tactical tasks. Planning, day-to-day operations and quality management must be seamlessly orchestrated, along with human resources functions like recruitment, learning and development, and employee scheduling.
Read this executive brief to learn how to transition to an AI strategy that can take your team – and business results – to the next level. See how you can:
Create an AI strategy with a single data model that includes routing, interaction analytics, forecasting/scheduling and predictive engagement
Harness the power of your data to align customers with the best resource
Drive employee effectiveness by ensuring you hire the right people and manage their performance to drive their success over the long term
Published By: SAP Concur
Published Date: Aug 07, 2019
"Spend Management is the planning, process, and system of managing business dollars to positively affect the production of products and services. Spend management usualy includes processes relating to procurement, supply chain management, and outsourcing. Optimal spend management relies on the ability to understand and control company spend through automation tools and analytics.
Steps to Strategic Spend Management
All CFOs are concerned with how their company is spending its money. However, this is of particular concern for CFOs of small to mid-size businesses who need to manage their cash flow effectively to survive.
To survive and maintain a competitive advantage, companies need to be strategic in their spend management and identify ways to invest wisely to meet current demands and fuel growth for the future. Expense and invoice management can no longer be viewed as simply a cost center.
Download this white paper to explore five initiatives that can help guide your company towa
Today’s C-level executives expect data and analytics to provide them with speed and agility to deliver competitive advantage and to disrupt new markets. But, in today’s complex data environment exists a near paradox between these expectations, that companies will be able to rapidly deliver value using data and analytics--and the complexities of the data landscape, making it more difficult to find, govern, connect to and access the data needed to deliver that value.
Once thing is clear: if management expectation is to be met, simplifying connectivity is a must.In this white paper, veteran analyst Mike Ferguson, Managing Director of Intelligent Business Strategies explores how simplifying data access –connectivity –aligns expectations with data realities thus decreasing time to value.
To stay ahead of the competition in a global marketplace, firms are increasingly speeding up operations, in many cases adopting real-time systems and tools to allow for instant decision-making and faster business cycles. Download here to learn how.
Published By: Sitecore
Published Date: Nov 04, 2009
This report highlights the strategic value of a next generation web content management system integrated with lead scoring, email marketing, customer relationship management, and web analytics. The report links the technology and practices of Best-in-Class organizations to engage customers, provide personalized experiences and manage the lead lifecycle.
Published By: Sitecore
Published Date: Jan 06, 2009
This guide offers insight into the WCM technology choices available today, discusses some of the requirements both IT and business users should consider when selecting a WCM solution, and includes advice for ensuring a successful evaluation process.
Published By: Sitecore
Published Date: Jul 08, 2009
This whitepaper discusses the need to target outcomes and focus on building a complete, 360-degree view of your customers -- who they are, where they came from, what they do, and how you can best meet their needs.