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Few Marketers Capitalize on Data Analytics to Optimize CX

For all the talk of data analytics, organizations are still struggling to use it effectively.

That’s the picture painted by two recent studies, which confirm data alone doesn’t create a data-driven organization. Organizations today remain data rich and insight poor.

More Data Than Insights
The studies — one by Forbes Insights and Dun & Bradstreet and a second by Experian Data Quality — show wide gaps between the promise and use of data analytics.

Marketers can develop highly targeted campaigns and promotions from data generated by websites, apps and the Internet of Things.

But few are aggressively using such insights, studies show. In fact, organizations have long ways to go to optimize the use of the data their teams are consuming and analyzing.

What’s more, many organizations still don’t trust data enough to use it to make decisions. Rather, they need to engineer wholesale cultural changes to drive adoption and use of advanced analytics.

Data analytics are tools that measure and interpret collected information and work in sync with, or as part of, other platforms in the digital marketing ecosystem.

For marketers, data analytics provide insight into the effectiveness of their campaigns, guide their management and operations decisions, and empower them to scale a personalized, real-time marketing experience to millions of people.

Marketers can harness the power of data analytics to deliver measurable, value-added results.

Guesses, Gut Feelings Trump Data

According to the Experian Data Quality report, 97 percent of organizations use data to power business opportunities. But only 44 percent trust that data enough to use it to make important business decisions.

More than half —52 percent — rely on educated guesses or gut feelings to make decisions based on that data.

“Businesses today recognize the importance of the data they hold, but a general lack of trust in the quality of their data prevents them from achieving strategic business objectives,” the report concluded.

Experian Data Quality, a subsidiary of Experian, surveyed more than 1,400 data management professionals to understand how data is being used within organizations and assess how data quality impacts business priorities. The findings are summarized in its 2017 global data management benchmark report.

Data Management, Governance Needed

Most organizations want to use data to increase revenue and better serve customers.

But first, they need to establish a foundational level of trust in the data they use.

“How do you build confidence in your data? With a strong focus on good governance and data quality,” the report notes.

High quality data will enable organizations to power more opportunities for themselves and their customers.

But organizations should think carefully about their needs before they invest in technologies such as Master Data Management (MDM), which the report calls “a huge buzzword in boardrooms around the world.”

Roger Yeh, a senior technical consultant at Experian Data Quality, said many see MDM as “this magical solution.” He continued:

“And they’re right. But that’s like saying you would hire Shaquille O’Neal just so he can help you replace light bulbs in high ceilings or clean the gutters. What many don’t consider is that MDM is often overkill for what the organization actually wants to accomplish.”
Before embarking on your data projects, Yeh said organizations should “really think” about their end goals.

At ARKE, we could not agree more. We believe the best strategy starts with the identification of the goals you want to meet — and that you need to articulate strategy before you invest in any technology.

A ‘Critical Need’ for Analytics

The Dun & Bradstreet/Forbes Insights 2017 Enterprise Analytics Study focuses on the increasingly important role analytics play in driving core enterprise business activities, from strategy to operations.

It further suggests organizations have critical needs for investment, prioritization, and implementation of analytics. In addition, corporate leadership needs to invest in the people, processes, and technologies that empower decision support and decision automation.

More than 300 senior executives in North America, Britain, and Ireland were surveyed for the study. The authors described data analytics as a “competitive differentiator,” adding more focus and investment is critical.

“Those that haven’t yet begun to prioritize implementation of advanced analytics within their organizations will be playing catch-up for a long while, and may never fully recover,” said Nipa Basu, chief analytics officer, Dun & Bradstreet.

More Data, Bigger Data Challenges

The Dun & Bradstreet/Forbes Insights draws some important conclusions, notably that “today’s data-driven enterprise has a never-ending appetite for more data.”

But it also notes data analytics skills gaps persist across the enterprise. That shows a need for better tools and best practices, the report noted.

There is surprisingly little sophistication in the ways companies analyze data. About 23 percent of those surveyed still use spreadsheets for data work. Only 41 percent use predictive models and/or advanced analytical and forecasting techniques. Only 19 percent of respondents use no analytical tools beyond basic data models and regressions.

In addition:

  • 24 percent cited data quality and accuracy as major obstacles to the success of their analytics efforts. Only 42 percent said they are confident in the quality of their data.
  • 27 percent said lack of knowledge hampers their data and analytics efforts. More than half (52 percent) use third-party data vendors to help them make better use of big data.

Business leaders need to do more with all the data their teams are consuming and analyzing. The C-Suite and senior leadership should do more to drive the cultural change needed for better use of analytics.

But data and analytics remain promising areas of opportunity, the study found. Survey respondents said these areas of analytics insights will be most valuable in the next 12 months.

Irish Digital skills are less well developed than Global Peers.

Nearly half of Irish digital initiatives for business are not delivering, according to findings in PwC's 2017 Irish Digital IQ survey published today.

The survey finds that less than two-thirds (64%) of Irish organisations have the digital skills required for an evolving digital economy and is similar to global peers (65%). At the same time, almost one out of two (46%) Irish respondents admitted that the lack of properly skilled teams is a barrier when it comes to achieving expected results from digital technology initiatives.

Nearly half (48%) of Irish executives reported that their strategic digital initiatives failed to deliver to their planned scope and is similar to global levels (45%). Furthermore, Ireland scores poorly (44%) when it comes to measuring outcomes from digital investments and has deteriorated from 60% in 2015.

The survey highlights that just over half (58%) of Irish respondents felt that their organisation embraces rapid change and disruption and lags global counterparts (69%).

Irish respondents rated their organisations' digital skills behind that of global peers for all key capabilities. For example, only around half of Irish respondents rated their skills' competencies as 'strong' or 'very strong' in the areas of cybersecurity (Ireland: 58%; Global: 64%), data analytics (Ireland: 54%; Global: 59%) and evaluating emerging technologies (46%; Global: 55%).

The survey suggests that a step-up in investment is needed in key areas of emerging technologies in order to keep pace with global levels. For example, in Ireland, 58% of executives plan to invest substantially in the internet of things over the next three years compared to 63% globally; for artificial intelligence this is 54% compared to 63% globally.

Just 6% of Irish executives plan to invest heavily in Blockchain over the next three years compared to 11% globally. One in five (20%) Irish respondents plan to invest substantially in drones by 2020, but these skills are virtually non-existent at present in Ireland.

Speaking at the survey launch, PwC Ireland Digital Leader, Ronan Fitzpatrick said, "Now, more than ever, upskilling is needed. The findings of the survey highlight that Irish businesses are trailing its global peers in terms of the adequacy of its digital skill sets. This training includes teaching employees the skills to harness technology, whether that's a new customer platform or a new breed of collaborative robot."

He added, "It also means cross-training workers to be comfortable and conversant in disciplines outside their own, as well as in skills that can support innovation and collaboration, such as agile approaches or design thinking. With increases in automation, robotics and AI, the workforce is changing and skills need to move with those changes."

Data Analytics Is No Longer A Nice Option -- It's The Core Of The Enterprise

Global businesses are facing increasing complexity and market volatility. In response, all business functions are turning to data-driven analytics and insights as a means to manage this increasing uncertainty, while better understanding their organizations’ customer bases and growing their businesses.

The move to data-driven insights is being forced by continued business reliance on technology and automation throughout the enterprise. Growth in digital technologies is driving the ability to analyze more data. This, in turn, is fueling the enterprise’s appetite for better data, more advanced analytics skills and the implementation of best practices. Analytics is the primary enabler to derive truth and meaning from data that drives the business growth.

In March 2017, Dun & Bradstreet and Forbes Insights explored the current state of analytics adoption across the enterprise via a survey of more than 300 executives in North America, the U.K. and Ireland across a range of industries. A recent report, “Analytics Accelerates Into the Mainstream,” sponsored by Dun & Bradstreet, analyzes the survey results.

Some key findings:

  • Senior executives finally understand the value of analytics and are making investments in technology, people and processes.
  • Data analytics skills gaps persist across the enterprise, as 27% of analytics professionals surveyed cite this skills gap as a major impediment in their data initiatives.
  • Data analytics has moved from IT and finance to the majority of business functions.
  • Today’s data-driven enterprise has a never-ending appetite for more data.
  • Analytical methods and tools trail both the appetite and ambition of most business leaders: 23% of analytics professionals are still using spreadsheets as their primary tool for data analysis.
  • There is a dire need for better data analytics best practices, with 19% using only basic data models and regressions.
  • People capital is a major factor for data analytics success.

While data analytics has gone mainstream, the C-suite and senior leadership need to do more to drive the cultural change needed for better utilization of analytics, as 38% of those surveyed say their companies need to do more.

Enterprises that plan to achieve data analytics excellence need to embrace a hybrid expertise model. Of the companies surveyed, 60% are using third parties to support organizational bandwidth while 55% are outsourcing some or all of their analytics needs.

The hybrid expertise model can help enterprises improve the quality of their data analytics, as 55% of those surveyed said that third-party analytics partners execute work of higher quality than analytics work completed in-house.

To move to a data-driven enterprise, business leaders need to do more with all the data their teams are consuming and analyzing. Only 38% of respondents strongly felt that business leaders took full advantage of their analytics initiatives.

Analytics now drives today’s enterprise, from formation of business strategy to powering operational excellence. It has clearly moved from being an optional operational element to serving as the core of corporate activities. It is no longer enough to just employ a few analysts and data scientists and leave them in a silo. Today’s business world demands that analytics best practices, technology, and personnel power every business function, and thus today’s C-suite needs to make the right data investments in these areas.

More important: The C-suite and all business leaders need to spearhead a wholesale cultural change across the enterprise to help drive adoption and utilization of advanced analytics. Data analytics is the new competitive differentiator. Business leaders that grasp this and commit to it will succeed. Those who delay do so at their own risk.

Data-driven transformation holds key to survival for banking and insurance services.

Colm Lyon, CEO and founder of, was the guest speaker at the FTI Consulting Leaders Breakfast in the Merrion Hotel on Thursday 23 March. On the agenda was how data-driven transformation holds the key to long-term survival and success in financial services and the three main forces driving change in this sector; rising consumer expectations, the emergence of fintech providers, and changes to the regulatory environment. Colm was presented with the FTI Consulting Recognition Award for Industry Disruption by Mark Higgins, senior managing director, FTI ConsultingPerformance Analytics, which specialises in advanced analytics to drive client company performance.

Colm Lyon, CEO and founder of, was the guest speaker at the FTI Consulting Leaders Breakfast in the Merrion Hotel  at which he was presented with a Recognition Award for Industry Disruption by Mark Higgins, senior managing director.  Photo: Peter Houlihan.

Colm Lyon, CEO and founder of, was the guest speaker at the FTI Consulting Leaders Breakfast in the Merrion Hotel at which he was presented with a Recognition Award for Industry Disruption by Mark Higgins, senior managing director. Photo: Peter Houlihan.

Entrepreneur Colm Lyon is the former founder and CEO of Realex payments and his new venture,, is the first Irish non-bank to strike a landmark deal to deliver debit cards. Colm said, “Vision and execution are the two key aspects to driving a business forward. In the payments and banking industry there is now considerable opportunity for new players to enter the market. Changing regulations, developments in technology and customer expectations are driving this change. It’s an industry that will never be the same again.”

Mark Higgins said, “Leaders in financial services are beginning to realise that data holds the key to their success. How organisations grapple with and use data to capture commercial value is no longer an IT centric challenge, it’s a CEO challenge. It involves real transformation in a company’s mindset and organisation
Colm Lyon, CEO and founder of, was the guest speaker at the FTI Consulting Leaders Breakfast in the Merrion Hotel  at which he was presented with a Recognition Award for Industry Disruption by Mark Higgins, senior managing director.  Photo: Peter Houlihan.

The role that regulators are playing to restore public confidence in the financial services industry was also highlighted with incoming changes that includes the introduction of GDPR to safeguard consumer privacy protection, PSD2 compliance to improve payments across the EU and strengthening surveillance for risk, fraud and money laundering.

Mark Higgins said, “Consumers want convenience, personalisation and immediacy. Using advanced analytics, internet one-stop travel shops are enabling customers to identify attractive weekend destinations and secure the best prices and book flights with only seven clicks on their mobile phone. There is no reason why banks and insurance companies cannot be as agile in their customer dealings. They are awash with data but the two big challenges facing them are, one, organising and using data effectively and the second is culture, getting people to line up behind the required change and transformation.”

Ian Duncan, managing director, FTI Consulting Performance Excellence commented “Fintech companies like are game changers and disruptors of the status quo; they’re nimble and hiring bright, smart people who see a more exciting and attractive future. The challenge facing large financial institutions is how to dismantle outdated work practices and structures and introduce new ways of working that empower small cross functional teams. Only then will they level the playing field in the war for talent.”

FTI Consulting Performance Analytics is headquartered in Dublin and is part of a global business advisory firm operating in 28 countries with 4,700 employees.

Colm Lyon, CEO and founder of, was the guest speaker at the FTI Consulting Leaders Breakfast in the Merrion Hotel at which he was presented with a Recognition Award for Industry Disruption by  (left) Mark Higgins, senior managing director and Ian Duncan, managing director. Photo: Peter Houlihan.

Colm Lyon, CEO and founder of, was the guest speaker at the FTI Consulting Leaders Breakfast in the Merrion Hotel at which he was presented with a Recognition Award for Industry Disruption by (left) Mark Higgins, senior managing director and Ian Duncan, managing director. Photo: Peter Houlihan.

15 data and analytics trends that will dominate 2017

big data trends 2017

Along with social, mobile and cloud, analytics and associated data technologies have earned a place as one of the core disruptors of the digital age. 2016 saw big data technologies increasingly leveraged to power business intelligence. Here's what 2017 holds in store for the data and analytics space.

John Schroeder, executive chairman and founder of MapR Technologies, predicts the following six trends will dominate data and analytics in 2017:

  • Artificial intelligence (AI) is back in vogue.
  • In the 1960s, Ray Solomonoff laid the foundations of a mathematical theory of AI, introducing universal Bayesian methods for inductive inference and prediction. In 1980 the First National Conference of the American Association for Artificial Intelligence (AAAI) was held at Stanford and marked the application of theories in software. AI is now back in mainstream discussions and the umbrella buzzword for machine intelligence, machine learning, neural networks and cognitive computing, Schroeder says. Why is AI a rejuvenated trend? Schroeder points to the three Vs often used to define big data: Velocity, Variety and Volume.
    Platforms that can process the three Vs with modern and traditional processing models that scale horizontally provide 10-20X cost efficiency over traditional platforms, he says. Google has documented how simple algorithms executed frequently against large datasets yield better results than other approaches using smaller sets. Schroeder says we'll see the highest value from applying AI to high volume repetitive tasks where consistency is more effective than gaining human intuitive oversight at the expense of human error and cost.
  • Big data for governance or competitive advantage. In 2017, the governance vs. data value tug of war will be front and center, Schroeder says. Enterprises have a wealth of information about their customers and partners. Leading organizations will manage their data between regulated and non-regulated use cases. Regulated use cases data require governance; data quality and lineage so a regulatory body can report and track data through all transformations to originating source. Schroeder says this is mandatory and necessary but limiting for non-regulatory use cases like customer 360 or offer serving where higher cardinality, real-time and a mix of structured and unstructured yields more effective results.
  • Companies focus on business- driven applications to avoid data lakes from becoming swamps. In 2017 organizations will shift from the "build it and they will come" data lake approach to a business-driven data approach, Schroeder says. Today's world requires analytics and operational capabilities to address customers, process claims and interface to devices in real time at an individual level. For example, any ecommerce site must provide individualized recommendations and price checks in real time. Healthcare organizations must process valid claims and block fraudulent claims by combining analytics with operational systems. Media companies are now personalizing content served though set top boxes. Auto manufacturers and ride sharing companies are interoperating at scale with cars and the drivers. Delivering these use cases requires an agile platform that can provide both analytical and operational processing to increase value from additional use cases that span from back office analytics to front office operations. In 2017, Schroeder says, organizations will push aggressively beyond an "asking questions" approach and architect to drive initial and long term business value.
  • Data agility separates winners and losers. Software development has become agile where DevOps provides continuous delivery, Schroeder says. In 2017, processing and analytic models will evolve to provide a similar level of agility as organizations realize data agility, the ability to understand data in context and take business action, is the source of competitive advantage not simply having a large data lake. The emergence of agile processing models will enable the same instance of data to support batch analytics, interactive analytics, global messaging, database and file-based models, he says. More agile analytic models are also enabled when a single instance of data can support a broader set of tools. The end result is an agile development and application platform that supports the broadest range of processing and analytic models.
  • Blockchain transforms select financial service applications. In 2017, there will be select, transformational use cases in financial services that emerge with broad implications for the way data is stored and transactions processed, Schroeder says. Blockchain provides a global distributed ledger that changes the way data is stored and transactions are processed. The blockchain runs on computers distributed worldwide where the chains can be viewed by anyone. Transactions are stored in blocks where each block refers to the preceding block, blocks are timestamped storing the data in a form that cannot be altered. Hackers find it theoretically impossible to hack the blockchain since the world has view of the entire blockchain. Blockchain provides obvious efficiency for consumers. For example, customers won't have to wait for that SWIFT transaction or worry about the impact of a central datacenter leak. For enterprises, blockchain presents a cost savings and opportunity for competitive advantage, Schroeder says.
  • Machine learning maximizes microservices impact. This year we will see activity increase for the integration of machine learning and microservices, Schroeder says. Previously, microservices deployments have been focused on lightweight services and those that do incorporate machine learning have typically been limited to "fast data" integrations that were applied to narrow bands of streaming data. In 2017, we'll see development shift to stateful applications that leverage big data, and the incorporation of machine learning approaches that use large of amounts of historical data to better understand the context of newly arriving streaming data.

Hadoop distribution vendor Hortonworks predicts:

  • Intelligent networks lead to the rise of data clouds. As connections continue to evolve thanks to the Internet of Anything (IoAT) and machine-to-machine connectivity, silos of data will be replaced by clouds of data, Hortonworks says.
  • Real-time machine learning and analytics at the edge. Smart devices will collaborate and analyze what one another is saying, Hortonworks says. Real time machine-learning algorithms within modern distributed data applications will come into play — algorithms that are able to adjudicate 'peer-to-peer' decisions in real time.
  • More  pre-emptive analytics: from post-event to real-time and pre-event analysis and action. We will begin to see a move from post-event and real-time to preemptive analytics that can drive transactions instead of just modifying or optimizing them, Hortonworks says. This will have a transformative impact on the ability of a data-centric business to identify new revenue streams, save costs and improve their customer intimacy.
  • Ubiquity of connected modern data applications. For enterprises to succeed with data, apps and data need to be connected via a platform or framework, Hortonworks says. This is the foundation for the modern data application in 2017. Modern data applications are highly portable, containerized and connected. They will quickly replace vertically integrated monolithic software.
  • Data will be everyone's product. Data will become a product with value to buy, sell or lose, Hortonworks says. There will be new ways, new business models and new companies looking at how to monetize that asset.

DataStax, which develops and supports a commercial version of the open-source, Apache Cassandra NoSQL database, predicts:

  • The emergence of the data engineer. The term, "data scientist," will become less relevant, and will be replaced by "data engineers," DataStax says. Data scientists focus on applying data science and analytic results to critical business issues. Data engineers, on the other hand, design, build and manage big data infrastructure. They focus on the architecture and keeping systems performing.
  • Security: Growth of IoT leads to blurred lines. IoT's growth has largely gone unchecked, DataStax says. With a lack of standards and an explosion of data, it isn't entirely clear who is responsible for securing what. Most at risk are ISPs, which is why we'll see these providers take a leading role in the security conversation in the year ahead, DataStax says.
  • Hybrid wins, thanks to certain enterprise-ready cloud applications. It is becoming clear that many large organizations that have built their databases on legacy platforms would rather pull out their teeth than switch, DataStax says. Hybrid data architectures that encompass legacy databases, yet allow organizations to take advantage of cloud applications, will be a major focus for these organizations.
  • Cutting ties thanks to serverless architectures. DataStax believes the move to serverless architectures — applications that depend on third-party applications or services in the cloud to manage server-side logic and state, or that run in stateless compute containers that are event-triggers — will become more widespread in the coming years. The adoption of serverless architectures will have a widespread impact on how applications are deployed and managed.

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