Hannah Duce, director of strategic alliances at Rackspace Technology, and Edward Kerr, the company’s product director, are quick to point out that different industries have different needs for the cloud and are often best served by highly customized solutions created to address their unique needs. It’s a singular mindset at Rackspace, where technology teams serve as trusted guides in the cloud journeys of more than half of the Fortune 100.

“One of the contributors to our success is that we excel in and have tremendous technical depth across the hybrid and multi-cloud worlds,” says Kerr. “We of course handle all of the basics, whether it’s helping an organization get the most out of their deployments with Amazon Web Services and Microsoft Azure, but we also have people with significant expertise that isn’t easily replicated by the vast majority of enterprises today.”

As one example, Kerr points to a customer who wants to move their on-premises infrastructure based on VMware by Broadcom technology to the cloud but also has a crucially important workload in OpenStack. In such a situation, Rackspace’s teams draw on technical expertise honed over years in both environments.

“Rackspace of course founded OpenStack with the National Aeronautics and Space Administration and we remain one of VMware’s earliest and closest partners,” he adds. “When you are a great partner – one that puts in the time and does the work needed to really know those they collaborate with, the partnership that results delivers exceptional value, particularly to the enterprise customer.”

It’s a formula that clearly works. In addition to its enviable presence in the Fortune 100, Rackspace’s more than 7,000 employees and 40 data centers serve companies of all sizes in 120 countries and numerous industries. These include healthcare, manufacturing, non-profit, education, consumer goods, automotive, food and beverage, travel, retail, government, and public utilities to name a few.

“One of the things that has really enabled us to excel across industries is the ability our teams have to fully manage and perfect the entire stack down into all of the peripheral applications,” says Duce. “Low latency is then delivered by our private high-speed network that extends across our data centers and includes onramps into the major hyperscalers.

It’s an approach made possible by Rackspace’s dedicated teams, each of which brings significant industry expertise to their work. Healthcare is but one example.

“Our healthcare team not only knows Epic electronic health records inside and out, but also the    numerous applications that work with it in a clinical setting,” she adds. “We also bring with us everything needed to address compliance requirements, for example in healthcare those associated with HIPAA and HITECH.”

Partners to Enterprises that Need a Multi-Cloud Expert

Now in its second decade of a close partnership with VMware, Rackspace offers an extensive portfolio of private cloud solutions, as well as sovereign clouds for the United States and United Kingdom also powered by Broadcom by VMware technologies. The company was even a testing partner for VMware Cloud Foundation, (VCF).

“We’ve spent a lot of time together with VMware teams over the years doing beta testing on our respective and combined solutions,” says Kerr. “VCF stands out because it includes everything needed to build and run an exceptional cloud, from security to visibility tools. Most enterprises will also find that it delivers exceptional value – value that increases when they consider the tools they will no longer need to invest in because Broadcom has already provided them in VCF.”

At Rackspace, VCF, like all technologies, is backed up by fanatical support – something Kerr believes is a key differentiator for Rackspace even if it is increasingly defined in a new way.

“In the past, fanatical support was associated with the time you would put in over the holidays or on the weekend after a problem occurred,” he says. “What people want now is proactive fanatical support – support that creates automation and safeguards that not only prevent problems before they occur, but which also lead to the strongest possible cloud. VCF inherently includes both.”

Kerr stresses that enterprises also desire flexibility more than ever before, something that led Rackspace to create Rackspace Elastic Engineering. With the service, Rackspace assembles a team with highly specific cloud solutions and services expertise and skill sets. Customers then purchase a bucket of hours they can use as they see fit, for as long as needed. It’s part of a concerted effort to proactively address customers’ needs.

“Whether you are optimizing your data center, consolidating data centers, fully existing the data center business, or optimizing your AI projects with our Rackspace AI Anywhere private cloud,  we will provide you with a cloud that addresses the unique needs encountered in your industry, and the unique needs encountered in your business,” adds Duce. “Our ability to provide a hybrid or multi-cloud solution, along with all of the managed services and technical expertise needed to realize its full potential, is why we thrive in the Fortune 100 and on Main Street.”

For more information on Rackspace visit here.

Look to CIO.com for stories about the industry-leading providers in the Broadcom Advantage Program and insights on how they are helping enterprises succeed in their private, hybrid, and multi-cloud endeavors.


Introduction
Since its inception decades ago, the primary objective of business intelligence has been the creation of a top-down single source of truth from which organizations would centrally track KPIs and performance metrics with static reports and dashboards. This stemmed from the proliferation of data in spreadsheets and reporting silos throughout organizations, often yielding different and conflicting results. With this new mandate, BI-focused teams were formed, often in IT departments, and they began to approach the problem in the same manner as traditional IT projects, where the business makes a request of IT, IT logs a ticket, then fulfills the request following a waterfall methodology.

While this supplier/consumer approach to BI appeared to be well-suited for the task of centralizing an organization’s data and promoting consistency, it sacrificed business agility. There was a significant lag between the time the question was asked, and the time the question was answered. This delay and lack of agility within the analysis process led to lackluster adoption and low overall business impact.

The emergence of self-service BI in recent years has challenged the status quo, especially for IT professionals who have spent the better part of the past two decades building out a BI infrastructure designed for developing top-down, centralized reporting and dashboards. Initially, this self-service trend was viewed as a nuisance by most IT departments and was virtually ignored. The focus remained on producing a centrally-managed single source of truth for the organization.

Fast-forward to today and IT finds itself at a crossroad with self-service BI as the new normal that can no longer be ignored. The traditional approach to BI is becoming less and less relevant as the business demands the agility that comes with self-service to drive adoption and improve organization outcomes. This, paired with the continued exponential growth in data volume and complexity, presents IT with an important choice.

Either the demand for self-service BI is embraced, and IT evolves to become the enabler of the broader use and impact of analytics throughout their organizations, or it is ignored and IT continues as the producer of lower-value enterprise reporting stifled by the limitations of traditional tools. IT professionals who are ready to serve as a catalyst and embrace this opportunity will deliver far greater value to their organizations than those who choose to ignore the real needs of their business users and analysts.

As organizations begin the transition from a traditional top-down approach driven by IT to a self-service approach enabled by IT and led by the business, a new framework and overall strategy is required. This means that past decisions supporting the core foundational
components of a BI program—people, process, and platform—must be revisited. Adjustments are needed in these three core areas to support the shift from a model of top-down BI development and delivery to a self-service-based modern BI model which is driven, and
primarily executed on, by the business.

People
Self-service analytics does not mean end users are allowed unfettered access to any and all data and analytic content. It means they have the freedom to explore pertinent business data that is trusted, secure, and governed. This is where process comes into play and represents the component that requires the most significant shift in traditional thinking for IT. A successful modern BI program is able to deliver both IT control and end-user autonomy and agility. A well-established and well-communicated process is required for an organization to strike this delicate balance.

A top-down, waterfall-based process only addresses the IT control part of the equation. A traditional BI deployment focuses primarily on locking down data and content with governance. This means limiting access and freedom to only a few people with specialized technical skills who are expected to meet the needs and answer the questions of the many. This typically involves developer-centric processes to design and build the enterprise data warehouse (EDW) model, build the ETL jobs to transform and load data into the model, construct the semantic layer to mask the complexity of the underlying data structures, and finally build the businessfacing reports and dashboards as originally requested by the business.

The unfortunate reality is that this approach often fails to deliver on the vision and promise of BI—to deliver significant and tangible value to the organization through improved decision making with minimal time, effort, and cost. Top-down, IT-led BI models often have an inverse profile of time, effort, and cost relative to the value they deliver to the organization.

A modern analytics solution requires new processes and newly-defined organizational roles and responsibilities to truly enable a collaborative self-service-based development process. IT and users must collaborate to jointly develop the rules of the road for their secure environment that each other must abide by in order to maximize the business value of analytics without compromising on the governance or security of the data.

IT’s success is highlighted, and its value to the organization realized, when the business can realize significant value and benefit from investments in analytics and BI. Should IT still be considered successful even if not a single end-user utilizes the BI system to influence a single business decision? Traditional processes intended to serve top-down BI deployments are too often measured by metrics that are not tied to outcomes or organizational impact.

If the ETL jobs that IT created ran without failure and the EDW was loaded without error and all downstream reports refreshed, many IT organizations would consider themselves successful.

Merely supplying data and content to users without any regard for whether or not it is adopted and provides value through improved outcomes is simply not enough. Modern BI requires updated processes to support self-service analytics across the organization. It also
requires the definition of new success metrics for which IT and the business are jointly accountable and are therefore equally invested.

Where processes and technology intertwine, there is tremendous opportunity. Technical innovations, especially with AI, will continue to make it easier to automate processes and augment users of all skill levels throughout the analytics workflow. And while process can
accelerate, rather than inhibit, successful analytics outcomes, it’s important to recognize that this relies on a system and interface that people are eager to use. If processes aren’t supported by the right platform choice, they will stifle adoption.

Platform
Since BI has been historically viewed as an IT initiative, it is not surprising that IT drove virtually every aspect of platform evaluation, selection, purchasing, implementation, deployment, development, and administration. But with drastic changes required to modernize the people and process components of a BI and analytics program, IT must change the criteria for choosing the technology to meet these evolving requirements. Perhaps the most obvious change is that IT must intimately involve business users and analysts from
across the organization in evaluating and ultimately deciding which modern platform best fits the organization and addresses the broad needs of the users. For more information on selecting the right analytics platform, check out the Evaluation Guide.

A modern platform must address a wide range of needs and different personas as well as the increased pace of business and the exponential growth in data volume and complexity. IT requires that the chosen platform enables governance and security while end users require easy access to content and the ability to explore and discovery in a safe environment.

The chosen platform must also be able to evolve with the landscape and integrate easily with other systems within an organization. A centralized EDW containing all data needed for analysis, which was the cornerstone of traditional BI, is simply not possible in the big-data era. Organizations need a platform that can adapt to an evolving data landscape and insulate users from increased complexity and change.

The most critical aspect is the ability to meet these diverse needs in an integrated and intuitive way. This integration is depicted on the following page as the modern analytic workflow. The diagram highlights the five key capabilities that must flow seamlessly in order for the three personas depicted in the center to effectively leverage the platform.

The BI and analytics platform landscape has passed a tipping point, as the market for modern products is experiencing healthy growth while the traditional segment of the market is declining with little to no net new investment. IT leaders should capitalize on this market
shift and seize the opportunity to redefine their role in BI and analytics as a far more strategic one that is critical to the future success of the organization. Adopting a collaborative approach to recast the foundational aspects of the BI program and truly support self-service is the key to changing the perception of IT from a producer to a strategic partner and enabler for the organization.

Promise
In today’s era of digital transformation, IT leaders are increasingly expected to take on digital business initiatives in their organizations, including identifying cost savings and finding new revenue streams. Realizing the value of data for these transformational efforts, many businesses are modernizing and increasing their analytics investments to innovate and accelerate change.
Everyone agrees that putting data at the center of conversations promises change. However, most organizations are failing to successfully implement an enterprise-wide analytics program.

IT is well positioned for a leadership role in these efforts, and is essential for the task of giving people the relevant data they need for decision-making. Modern analytics shifts IT’s role to a more strategic partner for the business, empowering users to navigate a trusted, self-service environment. But beyond access to the data, everyone needs the motivation and confidence to properly make decisions with it. You need to identify the relationships between job functions and data and change behaviors that run deep into the fabric of your organization’s culture.

This also means expanding your definition of self-service so that business users participate in some of the traditionally IT-led responsibilities associated with data and analytics—like administration, governance, and education. With the right processes, standards, and change management, business users can help manage data sources, analytics content, and users in the system, as well as contribute to training, evangelism, and the internal community. When users value and participate in these efforts, IT can manage strategic initiatives like business SLAs and ensuring the security of company assets.

Although every organization’s journey to building a data-driven organization will differ, achieving your transformational goals requires a deliberate and holistic approach to developing your analytics practice. Success at scale relies on a systematic, agile approach to identify key sources of data, how data is selected, managed, distributed, consumed, and secured, and how users are educated and engaged. The better you understand your organization’s requirements, the better you will be able to proactively support the broad use of data.

Tableau Blueprint provides concrete plans, recommendations, and guidelines as a step-by-step guide to creating a data-driven organization with modern analytics. We worked with thousands of customers and analytics experts to capture best practices that help turn repeatable processes into core capabilities to build and reinforce a data-driven mindset throughout your organization.
Learn more and get started today.

About Tableau
Tableau is a complete, integrated, and enterprise-ready visual analytics platform that helps people and organizations become more data driven. Whether on-premises or in the cloud, on Windows or Linux, Tableau leverages your existing technology investments and scales with you as your data environment shifts and grows. Unleash the power of your most valuable assets: your data and your people.

Analytics

When your children, friends, or acquaintances, ask what you do for a living, how do you, a CIO, answer them? “I am the future of our business” sounds a bit megalomaniacal, and “I manage the technology function” does not begin to do justice to the impact of your work. 

Since my team and I spend all day every day helping companies define their technology leadership needs, I have a vested interest in creating some clarity around the CIO role. So, I did what I always do when I am in need of information: I asked a bunch of CIOs. Here’s what they had to say.

How technical does a CIO need to be? 

Last year, I was recruiting a CIO for a large global services business whose IT organization employed more than 600 people. My client, the CEO, was very happy with our lead candidate’s ability to influence, lead, think strategically, establish business partnerships, and execute. Just before moving to an offer, my client asked, “But is he technical enough?” I assured him that our finalist was technical enough, but I thought to myself, “What does that even mean? Will this C-level executive be asked to write code?”

John Hill, CIDO of MSC Industrial Supply, spends less of his time thinking deeply about technology and more about bringing organizational digital agility to MSC. “CIOs do not need to be technology experts,” he says. “Today’s CIOs are the designers of organizations that can keep 25 balls in the air; and they know how all those balls fit into the digital vision years from now.”

When I do “talk tech” with CIOs, I find that we are no longer actually talking about technology. What we tend to talk about now are “platforms.” But what are these platforms and why are they so important? For Wafaa Mamilli, CIDO of animal health business Zoetis, platforms are at the heart of her role. “My job as CIDO is to lead a team that uses platforms to power our existing businesses and create new lines of business,” she says. “My role is less about technology and more about finding the next area for revenue and value generation.”

The ascent of CIO as value creator

Mamilli brings up an important point about the changing role of the CIO. After so many years of “IT is a cost center,” it is refreshing to see so many technology leaders describe their role as value creation and even business model change.

As Sanjib Sahoo, chief digital officer of Ingram Micro, sees it, “Once a company has transformed from traditional IT to a platform-driven business, the technology leadership role must shift to value creation,” he says. “The technology leaders of the future will have the technology depth and business acumen to be the bridge to value. Maybe the CIO, CTO, or CDO becomes the chief value officer, but whatever the title, the focus is not on developing an AI engine or bringing a new tool to market. It is in improving EBITDA and the experience of everyone involved in the journey. The focus is on business model change, not just another technology tool in the bag.”

CIOs at the center of digital transformation

Even as I write this, I realize that my first three quotes are not from chief information officers, but from chief information digital officers. These “digital” executives typically manage the IT organization, but their title signifies something more. As long as we are asking some fundamental questions about the CIO role, let’s poke at this “digital” concept a bit. What is digital and what does it mean for the CIO?

Regardless of whether you have digital in your title or not, as CIO, you have significant accountability for creating a digital business, but you do not own digital the way you own IT.  “Digital is not an IT function,” says Irvin Bishop, CIO of Black & Veatch. “Digital is sales, marketing, finance, legal, and operations — everything. I spend significant time evangelizing, carrying the digital torch, and collaborating with my business partners on how to shift our investments from run, to grow and transform.”

Deepak Kaul, CIO of Zebra Technologies, reinforces the critical role that CIOs play in driving digital literacy: “Digital transformation is not a one-time event,” he says. “By the time we are done implementing one wave, there will be a new one. CIOs are evolving from technologist and strategist to catalyst. Future CIOs will be evangelists of digital dexterity.”

The CIO’s evolving data role

Data falls into a similar category as digital. CIOs are responsible for building an enterprise data and analytics capability, but they do not own data as a function. If that is the case, where should the data and analytics function sit? Some companies put it under finance, others marketing, and others operations. In this humble executive recruiter’s opinion, most companies will wind up with a hub and spoke model, which Kaul is employing at Zebra.

“In IT, we have traditionally focused on protecting the single source of truth, but our business functions want to experiment with the data,” says Kaul. “So, at Zebra, we created a hub-and-spoke model, where the hub is data engineering and the spokes are machine learning experts embedded in the business functions. We kept the data warehouse but augmented it with a cloud-based enterprise data lake and ML platform. The core customer data stays pristine in the data warehouse, but once the data goes into the lake, the business functions can experiment. This model allows us pivot from a data defensive to a data offensive position.”

The CIO’s new remit regarding business risk

Now I’ve got it. The CIO role is less about technology and more about platforms, value creation, data, digital literacy, and business model change. But wait! What about risk? What about security? What is the CIO’s responsibility for the other side of the digital investment coin?

This is a question that Rhonda Gass, CIO of Stanley Black & Decker, faced head on. For a while at Stanley Black & Decker, the product group led the commercial technology roadmap, manufacturing led operations technology investments, and IT led business technology. “Individual risks in a particular silo might seem minor, but as those risks stack up, they can lead to a major impact on our customers, employees, or brand,” says Gass. “We recognized that the company needed an enterprise view of digital risk, so my team has taken on that leadership role. As CIO, I look across the entire company and drive digital risk management.”

CIOs as catalysts for culture change

Whether focused on digital, data, platforms, or value, all of these CIOs, it seems, are actively connecting the dots. With most leaders laser focused on their own business or function, someone needs to look across the entire business at opportunity, risk, and perhaps most importantly, cultural change. There is some irony in the fact that CIOs, with their technology background, are accountable for much of the people side of cultural change, but increasingly, that is the case.  

For Madhuri Andrews, CIDO of Jacobs Engineering, creating cultural change is at the heart of her role: “My role is both as a consultative partner to the business and as a mentor to the IT organization,” she says. “If I can connect people to the purpose, they will think more creatively. I can go into the weeds on any technology, but my more important role is to ensure that the work we are doing in IT is connected to the overall Jacobs strategy.”

The CIO of the future

So, there you have it! The simple definition of the CIO role is to have accountability for digital, data, cultural change, business model transformation, platform strategy, and value creation. Or as Will Lee, CIO of The Hanover, puts it, “For years, CIOs have worked hard to make IT a utility where, like electricity, it just works. But now, CIOs are shifting from running a utility to being thoughtful business partners focused on business solutions. Our role will be to work with our business leaders to co-create the dream.”

Well, when you put it that way, “I am the future of our business” might not be so off the mark, after all.

CIO, IT Leadership

Introduction
Since its inception decades ago, the primary objective of business intelligence has been the creation of a top-down single source of truth from which organizations would centrally track KPIs and performance metrics with static reports and dashboards. This stemmed from the proliferation of data in spreadsheets and reporting silos throughout organizations, often yielding different and conflicting results. With this new mandate, BI-focused teams were formed, often in IT departments, and they began to approach the problem in the same manner as traditional IT projects, where the business makes a request of IT, IT logs a ticket, then fulfills the request following a waterfall methodology.

While this supplier/consumer approach to BI appeared to be well-suited for the task of centralizing an organization’s data and promoting consistency, it sacrificed business agility.

There was a significant lag between the time the question was asked, and the time the question was answered. This delay and lack of agility within the analysis process led to lackluster adoption and low overall business impact.

The emergence of self-service BI in recent years has challenged the status quo, especially for IT professionals who have spent the better part of the past two decades building out a BI infrastructure designed for developing top-down, centralized reporting and dashboards. Initially, this self-service trend was viewed as a nuisance by most IT departments and was virtually ignored. The focus remained on producing a centrally-managed single source of truth for the organization.

Fast-forward to today and IT finds itself at a crossroad with self-service BI as the new normal that can no longer be ignored. The traditional approach to BI is becoming less and less relevant as the business demands the agility that comes with self-service to drive adoption and improve organization outcomes. This, paired with the continued exponential growth in data volume and complexity, presents IT with an important choice.

As organizations begin the transition from a traditional top-down approach driven by IT to a self-service approach enabled by IT and led by the business, a new framework and overall strategy is required. This means that past decisions supporting the core foundational components of a BI program—people, process, and platform—must be revisited. Adjustments are needed in these three core areas to support the shift from a model of top-down BI development and delivery to a self-service-based modern BI model which is driven, and primarily executed on, by the business.

People
A successful transition to self-service business analytics begins with people and should be the top priority for IT when considering changes required for BI modernization. In a traditional BI model, people were often considered last after platform and process. The widely-used mantra “if you build it, they will come” exemplifies the belief that business users would gravitate toward a well-built system of record for BI that would answer all of their business questions.

This desired end-state rarely came to fruition since there was little to no collaboration between the business users and IT during the process of building the solution after an upfront requirements-gathering phase. In the absence of active engagement and feedback from the business during the time between requirements gathering and project completion, there are many opportunities for failure that typically emerge. A few of the most common include:

• Business or organizational changes occur during the development process that render the initial requirements obsolete or invalid.
• Incomplete or inaccurate requirements are given in the initial process phases.
• Errors are made in the process of translating business requirements into technical requirements.

The end result of these situations is often that business users disengage from the BI program completely and an organization’s investment in time and resources are wasted due to lack of adoption. Business users and analysts need to use analytics in order for it to have any impact and deliver organizational value. A BI model that embraces self-service puts these users first and allows them to explore, discover, and build content that they will ultimately use to make better business decisions and transform business processes.

Collaboration between the business and IT is critical to the success of the implementation as IT knows how to manage data and the business knows how to interpret and use data within the business processes they support. They have the context within which analytics and the insight derived from it will be used to make better business decisions and ultimately improve outcomes. This collaboration of the groups early on will not only lead to the deployment of a platform that meets the needs of the business but also drives adoption and impact of the platform overall.

Process
Self-service analytics does not mean end users are allowed unfettered access to any and all data and analytic content. It means they have the freedom to explore pertinent business data that is trusted, secure, and governed. This is where process comes into play and represents the component that requires the most significant shift in traditional thinking for IT. A successful modern BI program is able to deliver both IT control and end-user autonomy and agility. A well-established and well-communicated process is required for an organization to strike this delicate balance.

A top-down, waterfall-based process only addresses the IT control part of the equation. A traditional BI deployment focuses primarily on locking down data and content with governance. This means limiting access and freedom to only a few people with specialized technical skills who are expected to meet the needs and answer the questions of the many. This typically involves developer-centric processes to design and build the enterprise data warehouse (EDW) model, build the ETL jobs to transform and load data into the model, construct the semantic layer to mask the complexity of the underlying data structures, and finally build the businessfacing reports and dashboards as originally requested by the business.

The unfortunate reality is that this approach often fails to deliver on the vision and promise of BI—to deliver significant and tangible value to the organization through improved decision making with minimal time, effort, and cost. Top-down, IT-led BI models often have an inverse profile of time, effort, and cost relative to the value they deliver to the organization.

Tableau

A modern analytics solution requires new processes and newly-defined organizational roles and responsibilities to truly enable a collaborative self-service-based development process. IT and users must collaborate to jointly develop the rules of the road for their secure environment that each other must abide by in order to maximize the business value of analytics without compromising on the governance or security of the data.

IT’s success is highlighted, and its value to the organization realized, when the business can realize significant value and benefit from investments in analytics and BI. Should IT still be considered successful even if not a single end-user utilizes the BI system to influence a single business decision? Traditional processes intended to serve top-down BI deployments are too often measured by metrics that are not tied to outcomes or organizational impact. If the ETL jobs that IT created ran without failure and the EDW was loaded without error and all downstream reports refreshed, many IT organizations would consider themselves successful.

Merely supplying data and content to users without any regard for whether or not it is adopted and provides value through improved outcomes is simply not enough. Modern BI requires updated processes to support self-service analytics across the organization. It also requires the definition of new success metrics for which IT and the business are jointly accountable and are therefore equally invested.

Where processes and technology intertwine, there is tremendous opportunity. Technical innovations, especially with AI, will continue to make it easier to automate processes and augment users of all skill levels throughout the analytics workflow. And while process can accelerate, rather than inhibit, successful analytics outcomes, it’s important to recognize that this relies on a system and interface that people are eager to use. If processes aren’t supported by the right platform choice, they will stifle adoption.

Platform
Since BI has been historically viewed as an IT initiative, it is not surprising that IT drove virtually every aspect of platform evaluation, selection, purchasing, implementation, deployment, development, and administration. But with drastic changes required to modernize the people and process components of a BI and analytics program, IT must change the criteria for choosing the technology to meet these evolving requirements. Perhaps the most obvious change is that IT must intimately involve business users and analysts from across the organization in evaluating and ultimately deciding which modern platform best
fits the organization and addresses the broad needs of the users. For more information on selecting the right analytics platform, check out the Evaluation Guide.

A modern platform must address a wide range of needs and different personas as well as the increased pace of business and the exponential growth in data volume and complexity. IT requires that the chosen platform enables governance and security while end users require easy access to content and the ability to explore and discovery in a safe environment.

The chosen platform must also be able to evolve with the landscape and integrate easily with other systems within an organization. A centralized EDW containing all data needed for analysis, which was the cornerstone of traditional BI, is simply not possible in the big-data era. Organizations need a platform that can adapt to an evolving data landscape and insulate users from increased complexity and change.

The most critical aspect is the ability to meet these diverse needs in an integrated and intuitive way. This integration is depicted on the following page as the modern analytic workflow. The diagram highlights the five key capabilities that must flow seamlessly in order for the three personas depicted in the center to effectively leverage the platform.

Tableau

The BI and analytics platform landscape has passed a tipping point, as the market for modern products is experiencing healthy growth while the traditional segment of the market is declining with little to no net new investment. IT leaders should capitalize on this market shift and seize the opportunity to redefine their role in BI and analytics as a far more strategic one that is critical to the future success of the organization. Adopting a collaborative approach to recast the foundational aspects of the BI program and truly support self-service is the key to changing the perception of IT from a producer to a strategic partner and enabler for the organization.

Promise
In today’s era of digital transformation, IT leaders are increasingly expected to take on digital business initiatives in their organizations, including identifying cost savings and finding new revenue streams. Realizing the value of data for these transformational efforts, many businesses are modernizing and increasing their analytics investments to innovate and accelerate change. Everyone agrees that putting data at the center of conversations promises change. However, most organizations are failing to successfully implement an enterprise-wide analytics program.

IT is well positioned for a leadership role in these efforts, and is essential for the task of giving people the relevant data they need for decision-making. Modern analytics shifts IT’s role to a more strategic partner for the business, empowering users to navigate a trusted, self-service environment. But beyond access to the data, everyone needs the motivation and confidence to properly make decisions with it. You need to identify the relationships between job functions and data and change behaviors that run deep into the fabric of your organization’s culture.

This also means expanding your definition of self-service so that business users participate in some of the traditionally IT-led responsibilities associated with data and analytics—like administration, governance, and education. With the right processes, standards, and change management, business users can help manage data sources, analytics content, and users in the system, as well as contribute to training, evangelism, and the internal community. When users value and participate in these efforts, IT can manage strategic initiatives like business SLAs and ensuring the security of company assets.

Although every organization’s journey to building a data-driven organization will differ, achieving your transformational goals requires a deliberate and holistic approach to developing your analytics practice. Success at scale relies on a systematic, agile approach to identify key sources of data, how data is selected, managed, distributed, consumed, and secured, and how users are educated and engaged. The better you understand your organization’s requirements, the better you will be able to proactively support the broad use of data.

Tableau Blueprint provides concrete plans, recommendations, and guidelines as a step-by-step guide to creating a data-driven organization with modern analytics. We worked with thousands of customers and analytics experts to capture best practices that help turn repeatable processes into core capabilities to build and reinforce a data-driven mindset throughout your organization. Learn more and get started today.

IT Leadership

Technological disruptions continue to redefine the CIO role within corporations. As innovators and value creators, CIOs are charged with managing developments like low-code/no-code (LCNC), which is revolutionizing user-generated innovation by enabling people with little to no coding experience, or “citizen developers,” to quickly and easily deliver new capabilities on demand without having to rely on established development teams.

We are experiencing an undeniable shift toward this kind of democratized technology. Industry research shows that in 2021, LCNC platforms accounted for 75% of new app development, and Accenture’s own research says that 60% of LCNC users expect their use of the platform to increase. But sustaining this type of development in a declining talent market isn’t easy.    

With nearly one in five business leaders experiencing constraints due to the decline in tech talent, CIOs need to look beyond their traditional pool of IT professionals to a broader community, and cultivate and nurture new talent networks that bring together citizen developers with their professional counterparts.  

As the borders between business and IT blur, there’s a massive opportunity for forward-thinking CIOs to rethink how they work and lead their organizations, and accepting LCNC platforms to operate smarter and faster achieves sharp breakthrough gains in corporate profitability and efficiency.

What’s accelerating LCNC adoption

Diana Bersohn

The main areas fueling LCNC adoption are ease of use, ease of integration with existing solutions and technologies, and faster value creation. Corporations are under pressure to innovate and solve problems quicker, and those that focus on delivering experiences outperform their peers by six times in year-on-year profitability over one, three, five and seven years. So how do SMBs utilize LCNC platforms and stay relevant among larger businesses?

Tech waves have shown to accelerate SMB business growth, and LCNC will have an equal, if not larger, impact on SMBs. Today, there’s a growing set of SMBs utilizing LCNC delivering value in every facet of the business by enabling and simplifying everything from customer acquisition to back-end processes. This comes at a time when SMBs are looking for ways to compete and differentiate against larger companies and other SMBs.

There are three factors that make LCNC relevant for SMBs in today’s business environment:

Digital maturity as a competitive necessity: More than 70% of small businesses worldwide are accelerating digitization, and 93% say COVID-19 made them more reliant on technology.Challenging access to digital talent: One in five SMBs surveyed said their LCNC platform search was driven by the scarcity of digitally fluent staff.Enterprise IT solutions do not meet SMB needs: Up to 47% of SMBs think enterprises don’t understand the challenges they face and movement towards LCNC illustrates that point. 

New people are engaging with technology within the enterprise and broader ecosystems, and “bring your own” is fast becoming “make your own” as citizen developers take advantage of rapidly advancing LCNC tools.

Embracing a new operating model

Putting the power into people’s hands requires careful management. LCNC operating models must simultaneously balance the need of innovation, stabilization, and scaling for the business and technology so the CIO and IT teams can better enable crucial business change and innovation, rather than act as technological gatekeepers.  

Christian Kelly

CIOs should also think of capabilities falling into different categories, particularly those that are customer-facing, enterprise-wide or departmental. This categorization will help determine optimum team structures, like determining the right mix between new citizen developers and pro-code developers within the IT organization.

Plus, there’s a need to create new engagement models to enable better collaboration with CISOs and chief data officers for security and data governance. To do so, those teams must have clear roles and responsibilities to deliver user experience and foster innovation. The technology portfolio should also be segmented to work within the new model by evaluating existing applications to be migrated into LCNC.

Another model includes creating a new pool of funding for innovation with LCNC. CIOs should take charge in this way and drive LCNC platform providers to expose more of the inner workings of the platform, create joint options for supporting the citizen developers, and simplify the effort to address CISO’s concerns.

Over time, CIOs need to develop operating models by balancing a mix of pro-code and citizen developers within LCNC platform providers to drive maturity. CIOs will continue to be the guardians of technology, but they must become stewards and co-innovators as well, guiding others, including citizen developers, to realize the promise of innovation at scale. This change requires new operating models designed to support co-innovation, enable personal productivity, and ensure that access to data by LCNC platforms is managed and backed by robust governance and security. Companies with a clear approach to LCNC that empower their people with the right tools and systems will achieve innovation at the next level and beyond.

Sriram Sabesan, senior manager, Technology Strategy, Software and Platforms at Accenture also contributed to this article.

CIO