Drive Your Business
The Data
Ecosystem
Becoming a more
innovative and efficient
data enterprise

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Introduction
The rise of ubiquitous data collection and analysis has fundamentally shifted the way companies
do business. As data-oriented processes, products, and systems come to dominate, every
company needs to reassess its technology strategy and implement new processes to facilitate
data-driven decision making and automation. In today’s workplace, companies must strive to
integrate their own practices and business model into an increasingly data-driven ecosystem.
This requires significant leadership from the CIO and IT department, who must work closely
with business leaders to develop data strategies that meet the needs of the business.
Creating intelligence and interconnectedness
For years, companies have been struggling to transform
into organizations that are informed and driven by data
insights. Some industries have been more successful
than others, resulting in business disruption and creating
entirely new customer revenue and operating models.
These companies have achieved stunning success and
proven to the business world that data has immense
potential. In order to remain successful in the coming years,
companies need to adopt these strategies. At the heart
of every modern business should be a ubiquitous data
ecosystem. This will provide the opportunity to strengthen
organizational intelligence and interconnectedness across
the enterprise, customers and external stakeholders.
There are many business drivers influencing the need for a more dynamic, enterprise-wide
data ecosystem, including globalization, speed to market, and competitive product or service
differentiation. Data insights have always been paramount to decision-making at all levels of the
organization. Now more than ever, they are informing and changing business interactions from
problem solving to creating new conversations around innovation and the “art of the possible”.
Data ecosystems are not perfect. There are many dimensions and challenges that can make
a successful transformation difficult. But with new technology and practices, businesses
have the opportunity to gain insights that can connect the data and draw inferences,
patterns, and predictive elements that will inform and influence their future. This paper will
explore the ways in which companies can use data ecosystems to drive business goals.

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Leveraging
next-generation
technologies
In order to take advantage of the power of data, companies must leverage next generation
technologies that make it easier and more cost effective to gather, analyze, and act on information.
Data ecosystem capabilities for the 21st-century knowledge worker continue to rapidly evolve,
fueled by frequent advances in technology. Our technology savvy workforce is creating a
revolution that demands richer data-harvesting capabilities. Big data, sensory IoT, cloud, mobile,
and sophisticated analytics technologies are creating an interconnectedness in driving new
value and transforming business. Companies must learn how best to use these technologies
to drive business goals by improving efficiency, reducing costs, and capturing new markets.
Advanced analytics
Statistical analysis and science-based analytical methods have a large role to play in the
future of business. As companies begin to realize that these tools can be used to make
accurate forecasts, better understand customers, and develop more effective practices,
they are becoming a critical component of the data ecosystem. But it’s not enough to simply
make analytics a component of the overarching business strategy. It should be a leading
component. It is increasingly possible to use data to identify better customers, optimize the
workforce, and increase profitability. The days of acting on a gut feeling are over. Data-based
and science-based analytics must be at the core of every successful business strategy.

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Data has the power not only to help humans make better decisions, but also to make
machines smarter. Progressive organizations are unlocking new value through machine
learning and artificial intelligence, seeded by structured and unstructured data. These
technologies can form the foundations for tools that allow companies to significantly increase
their efficiency. Already, many tasks previously performed only by human workers can be
done by machines. IT help tickets, for example, are rapidly becoming a thing of the past as
new tools automatically resolve issues, while automated assistants become a reality.
Machine learning also has significant potential in product development. Google and IBM
are already using data-driven machine learning to develop disruptive technology (self-
driving cars and the Watson Analytics platform, respectively). These examples show
how wide a range of industries could be disrupted by artificial intelligence and machine
learning. Companies that aren’t evaluating these technologies and taking steps to
make them part of their own digital DNA will likely be disrupted by those that do.
Machine learning and artificial intelligence
Progressive organizations use
machine learning and artificial
intelligence to dramatically improve
their efficiency.
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Data visualization
Data’s value is seriously limited if it’s not
in a format that makes intuitive sense to
human employees. Powerful visualization-
communication platforms have emerged as the new common language for explaining
the story the data is revealing. Interactive charts, maps, and other visual aids can take
big data and make it manageable. These tools allow humans to more easily interpret and
act on complex sets of data, allowing it to be better used to drive business goals.
The Internet of Things (IoT) often gets more attention in the media for flashy consumer novelties
than business-oriented technologies. But those who overlook its power to revolutionize the way
companies do business are ignoring substantial opportunities. Sensors allow business to collect
data in a wide variety of areas, including production
lines, retail displays, and vehicles, while actuators
allow businesses to act on that data in real time. The
potential of this technology is practically limitless, as
companies can use it to develop new products, make
better decisions, and improve processes. Connecting
physical items to the network allows data to have
more direct real-world implications. This makes IoT
a key connective element of the data ecosystem.
The Internet of Things

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CIO and IT
leadership priorities
Given the immense importance of the data ecosystem, many CIOs may wonder what their role will
be in ensuring that the company is positioned for data success. IT leaders need to assess their
people, processes, and technology and provide the leadership that underpin these contemporary data
ecosystems. This means having a clear understanding of both business goals and the technology that
can help drive them. The CIO’s role is one of IT leadership and business advisement to ensure that the
company uses the data ecosystem effectively. It is critical that the CIO ensures that the data ecosystem
evolves as the business evolves. As an “ecosystem”, it is never static, but rather always changing.
One of the most important roles for the CIO is serving as a connection between business leaders
and the technology world. A company cannot effectively use the data ecosystem unless it has
strong buy-in from business leaders. This means that the CIO must strive to show the real value
of data and data-driven processes and tools. Building a coalition of partners in business and IT
units is critical to ensuring that every facet of the company is using data to drive insights and
innovation. The CIO must work with business leaders to motivate collaboration at all levels.
Connect with business leaders
IT’s role is one of business support. It works to ensure that the business is using data in a way that
allows employees to work more effectively and innovate. This means that the CIO must constantly
build relationships both within and outside of IT. The data ecosystem should be a part of every
business unit and every decision made within the company. The CIO needs to listen to the needs
of the business and collaborate with other units to implement solutions that work for everyone.
• Build relationships
Developing the infrastructure necessary for companies to fully embrace the data ecosystem
means significant time and resource investments. Many business leaders will be hesitant to make
significant outlays without a strong business case. It’s the responsibility of the CIO to make this
case and work with business leaders to develop solutions that meet the needs of the company.
• Make the business case for data

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The CIO must ensure that time, resource, and cultural investments are made into making a
company data-driven. The forward-thinking CIO needs to invest in IT skills and technology
partners that will foster a culture that is motivated to understand the business data at deeper
levels and that will be able to collaborate with business at a data-context level. IT must play a
major leadership role in enabling the necessary frameworks, architectures, and governance of
the data ecosystem. The CIO needs to harness core competencies in managing data-ecosystem
services that consume both structured and unstructured data, providing analytics “sandboxes”
that allow for exploration, hypothesis modeling, and prototyping. These new structures require
agile technologies and methodologies that don’t demand “perfect” quality scrubbed data.
Implement self-service
Shadow IT is becoming increasingly
common as workers go outside of the
CIO’s purview to implement solutions
that meet their needs. This can cause
problems for the IT department, as
they must often fix technical issues
and security breaches introduced
by these solutions. However, the
CIO cannot afford to simply pretend
these outside needs do not exist.
The knowledge worker is demanding
self-service tools that facilitate
using data environments very quickly without long lead times and eliminating the dependence
on IT organizations. IT should focus on building self-service frameworks that liberate the
knowledge worker, providing more independence for experimenting, data exploration, and
modeling, but in a way that works with the company’s overarching technology goals.
Invest in the data ecosystem

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Ensure data readiness
Today’s data-driven organizations need secure, clean, and in-context data. These are high
hurdles for most IT organizations, due to a lack of data centralization and the challenges
around data integration when connecting disparate structured and unstructured data sources.
Implementing master-data management and other similar solutions can help organize, centralize,
and clean data, ensuring greater accuracy and consistency across the business. The CIO
must spearhead these initiatives, working with business leaders to collect and collate data,
reducing duplicate records, and improving the overall cohesiveness of the company’s data.
Increase compatibility and connectivity
Collaboration across the enterprise is a critical element
of the data-driven workplace. Technology tools and
flexible infrastructure, such as cloud and mobile, have
emerged and are becoming more commonplace.
This allows for the connection of these complex data
ecosystems to enable more natural data exploration
in serving the dynamic, interdependent needs of
organizations. However, it is the responsibility of the
CIO to ensure that these tools are adopted and that
data is cross-compatible between platforms. Ensuring
that data is clean and consistently formatted requires
significant oversight and governance. The IT department
must help guide the business to ensure an effective,
overarching strategy for data across the enterprise.
Ensuring clean and
consistently formatted data
requires significant oversight
and governance.


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Business-first approach
IT’s role is to support the business in its endeavors. To that end, it is critical that any data-ecosystem
strategy makes business goals the top priority. Data ecosystems are formed from well thought-out
business cases that are prioritized based on potential value and business impact. It is important not to
be driven by the technologies, but rather approach opportunities from a business perspective and allow
data ecosystem needs to emerge from a deeper understanding of business-use cases. The CIO must
take the lead and work with business leaders to ensure that strategies meet the goals of the business.
Developing a business-first data-ecosystem approach requires the development of a cohesive,
enterprise-wide strategy designed to meet business goals. IT leaders must work with and
advise business leaders to create a solution that works effectively for the business.
Develop a data strategy
It is important to approach data-ecosystem business opportunities as a collaboration between
the business stakeholders and IT. Use integrated teams that are agile and driven by common
goals. Focus on the business-use cases first, not the technology. Use these end-goals to
drive technology decisions, not the other way around. This ensures that the initiative will
work to for the business, instead of simply being ineffectual drains on valuable resources.
• Work collaboratively
The data initiative should first and foremost meet the needs of end-business users. Before
making steps towards implementing an initiative, workshop the details of the business-
use cases defining unstated, unmet, and unseen needs in the context of driving the value
propositions. Sort out fact from fiction, uncovering insights through interviews, ethnography,
and other exploratory approaches. Take a methodical, fact-based approach to identify
what will help the business, what is cost-effective, and what is technologically feasible.
• Identify needs
Create a plan that seeks to start with a “series of small victories.”
Start small, iterate, and reiterate to drive early business value.
• Start small

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Before implementation it is important to look at the internal, external, structured, and
unstructured data and technologies to understand the inventory of what the organization
already has and where the gaps are to support driving the business opportunities. Take
steps to determine what data already exists, how clean this data is, and what data can be
gathered and analyzed with existing systems and processes. Coupled with business-driven
end goals, this will inform what the initiative needs to accomplish in order to be successful.
• Assess the data landscape
All initiatives in the business should be held accountable to predefined quantifiable
metrics. It is important to set these metrics before implementation has begun so
there is always a standard by which to judge progress and success. Identify the
hypotheses around the value propositions, so outcomes can be clearly measured,
enabling opportunities to be accelerated or killed based on objective criteria.
• Set metrics

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Implement
Implementation of data ecosystem initiatives may be rolled out over a significant period
of time, depending on the strategies outlined in the planning phase. It is important to stay
committed to the plan by building and maintaining relationships with key business leaders,
setting well-defined goals, and regularly reviewing progress. This helps ensure that the
strategies outlined in the planning phase result in the desired business outcomes.
It is likely that shifting a traditionally oriented business to a data-driven business will take
a significant amount of time. For this reason, it is important to set smaller goals to roll out
critical elements more quickly. Execute plans including people, process, and technology
that deliver results in short time intervals (less than three months) that are measurable
against the stated metrics. The company also should incorporate the learnings from
the results into future plan iterations and continually evolve the data ecosystem. This
progressive rollout ensures that the business can begin benefiting from the data ecosystem
almost immediately and that it continues to become more effective with each interval.
• Set progress intervals
Once the initiatives begin progressing, it is important to continue listening to the business,
paying close attention to how the efforts are being received. Keeping business support is
critical to long-term success, so it is important to maintain relationships with key stakeholders
and continue making the business case for the data ecosystem. It is also important to rapidly
correct any problems that may arise and constantly strive to improve based on past results.
• Keep listening to the business
Data initiatives are only valuable if they drive real, quantifiable business goals. The
metrics set forth in the planning stage are the guide by which to judge the progress
and success of projects. Use these to make adjustments to ineffective strategies
and to prove to business leaders that the initiatives are having real results.
• Hold initiatives accountable

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Conclusions
Understanding the data ecosystem and incorporating data-driven people, processes, and
technologies into the enterprise is critical to the success of every modern business. As a greater
number of companies begin to use data to innovate and make better decisions, those that
don’t will increasingly be left behind. In order to stay competitive, it is important that companies
take steps to integrate the data ecosystem into every business unit. This means taking a
business-first approach to new data-oriented initiatives and involving key business leaders
in the effort. Data makes companies more efficient and more effective. The CIO must take a
leadership position and be the foundation for these initiatives. That requires working closely with
business units, listening to their needs, and developing strategies that drive business goals.
Key points:
• Data-driven processes and technologies
are critical to future business success.
• The data ecosystem is comprised of
people, processes, and technology.
Having a strong foundation in each is key
to achieving a data-driven enterprise.
• The data ecosystem is always
evolving as the business evolves. It
is always changing, never static.
• Several advancements in technology,
such as IoT, machine learning, and
analytics, are driving the data ecosystem
and enabling companies to become
more intelligent and interconnected.
• It is important for the CIO and IT to take a
leading position in data initiatives, make
the business case to IT leaders, and help
to develop effective technology strategies.
• Companies should take a business-first
approach to the data ecosystem. That
means listening to business needs and
using them to develop a data strategy.
• Initiatives should be measured against
quantifiable metrics. Projects that aren’t
meeting benchmarks must be adjusted.
• The CIO must continue to work
closely with business units to develop
strategies that drive business goals.

Drive Your Business
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Management and Execution Services to optimize business performance, minimize cost and create
value. Our consultants have years of experience both as industry executives and trusted advisors
to help clients think through complicated and pressing challenges to drive their business forward.
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