Introduction
In today's digital world, more and more companies are
leveraging data to drive their RevOps success. However, many organizations
still face challenges in making the most of this data due to silos and
overload. This whitepaper discusses how you can overcome these challenges
through a combination of standardized processes, data governance, and a unified
view on performance analytics.
Breaking the silos and the data bottlenecks
- Silos
and bottlenecks are a problem for RevOps teams. They don't have to be, but
they often are. The root causes of these issues can be traced back to
three things: technology, organizational structure, and people.
- To
break through this problem and achieve faster cycle times and better
business outcomes, you'll need to understand how training data silos form
within your organization as well as how to address them at each stage in
the process (from initial asset creation through deployment). To do that
effectively, you'll need access to all of your data at one point in
time—and this means breaking down those barriers between your different
teams' systems of record.
The "data bottleneck" problem
The "data bottleneck" problem is one that
plagues many companies. You may be familiar with it:
- Data
silos are a source of the problem, as data is not easily shared or
available across teams and functions. This can lead to bottlenecks in your
company's RevOps process when information needs to be accessed by
different teams.
- Another
source is overload—too much data being generated from multiple sources within
an organization, which makes it difficult for employees to keep up with
new insights and updates as they come in. The result? Delays in RevOps
caused by delays in determining what actionable insights are needed for
making decisions about products or services.
The "siloed data" problem
- Let's
say you're managing a department in your organization that handles order
fulfillment. Your team has been trying to increase orders placed on its
website by 15% over the course of the year, but it's not working. You have
a lot of great data available—the number of visits to your site, which
pages they visit, what they click on—but when you look at all this
information together, it still doesn't tell you why people aren't buying
more often or what would motivate them.
- The
problem might be that you're operating in different silos. And if those
silos exist within your company's larger IT infrastructure and other
business units' responsibilities, then it could mean that each group is
collecting data independently without knowing how their efforts fit into
the overall picture. In this case, "siloed data" refers
specifically to having separate systems for collecting different types of
information from users as well as storing that information differently so
it can't easily be compared across platforms (and even departments).
- In
addition to causing operational issues like bottlenecks or lost
productivity due how long it takes employees to find answers about their
jobs across multiple systems; financial issues like wasted money spent on
duplicate processes; compliance issues if one team isn't aware of
another's actions affecting corporate policy compliance standards;
security problems from insufficient access controls between departments;
and so forth...
The RevOps approach provides a solution to silos and data
bottlenecks, but only if it is enabled with the right technology.
- Data
integration is the key to a successful RevOps approach. It's not enough to
have a robust data warehouse, or even an optimized data lake. You need
technology that can bridge the gap between all of your disparate systems
and silos, bringing together all of your disparate forms of data so that
it's available in one place for everyone who needs it--no matter where
they are within the organization.
- If
you're looking for the right solution to help you overcome silos and
bottlenecks in your organization's RevOps approach, look no further than
Data Integration Platforms (DIP). DIP will enable you to leverage all of
your current investments by connecting disparate systems and eliminating
silos between teams.
Getting operational excellence and revenue operations to
work together
- If
you follow the news, you may have heard that operational excellence and
revenue operations are two distinct functions. However, this is an
oversimplification of what RevOps is ultimately about: improving revenue.
Though it's true that having a strong focus on cost control is important
since it helps reduce expenses and ensure profit margins, RevOps also
focuses on collaboration between other departments such as sales and
marketing to drive revenue.
- In
fact, according to Forrester Research's 2018 North America CPO Survey
Report: "Most companies consider their CPOs [chief revenue officers]
to be functional leaders who manage revenue-generating operations."
In this light, it becomes clear that rather than focusing solely on cost
control or revenue generation alone (or worse still—both), RevOps should
instead balance both elements for optimal results without getting bogged
down by silos within your organization.
The key to operational excellence and revenue operations
working together is data integration.
- As
your business grows, you will no longer be able to rely on a single point
of integrative or operational excellence. There is an increasing need to
build resilient systems that can operate at scale as well as support
multiple business functions. However, integrating these systems is not
just about technology – it's about data, and it's about people.
- The
key to operational excellence and revenue operations working together is
data integration. For example, if you provide product management with an
opportunity in their CRM system but don't have any inventory available for
the sale order they want to place, they won't be happy with the experience
they get from your company or its products!
- Data
integration isn’t just about pushing information between systems; it’s
also about understanding how this information has been captured in each
system so that it can be used correctly throughout the organization
(whether by humans or machines).
Data integration is about more than just technology.
- Data
integration is about more than just technology. It’s a process that
requires people, processes, and technology to work together in order to
deliver valuable insights into your business.
- In
fact, it’s this combination of people, processes and technology that can
help you overcome problems caused by data overload or silos. By
integrating multiple sources of information into one single source of
truth (that includes all relevant data), you can reduce the number of
operational errors caused by inconsistent data across systems—a win for
both end users who are working with this data and IT teams who spend their
days supporting such systems.
Data overload is an existential threat to your business.
- Data
overload is a problem for all businesses. It's the result of a lack of
data integration, which can cause business decisions to be based on
incomplete or inaccurate information. In addition to making it harder for
you to make informed decisions, data overload can slow down your business
by forcing you to spend time unearthing information that could have been
easily accessed and leveraged in the first place.
- For
example, John wants to know what his company's sales were last quarter so
he can prepare his financial reports for the board meeting later this
week; however, Alice has been tasked with generating customer segmentation
reports for this same meeting and doesn't have time right now because
she's trying her best just keep up with all of the requests coming at her
from other departments within their organization—and also handle some new
projects she took on recently but didn't have time before now because
everyone else was too busy!
- By
making sure your teams are working from one system rather than many
disparate ones (which increases overhead costs), you're able to avoid
duplicate workflows between departments while also creating opportunities
across teams thanks to shared access privileges within one platform
instead of several siloed ones, where they would otherwise be limited by
specific permissions granted by department leaders only."
How you can use data integration to drive RevOps success.
- Data
integration is about more than just technology. It's about strategy and
process. It's about people, culture and governance. And yes, it's about
compliance and risk management.
- Data
integration involves the ability to seamlessly access and deliver
information from one or multiple sources in real time across various
systems—which is critical for success with RevOps projects because it
allows you to:
- Quickly identify gaps in your data so
you can develop appropriate solutions;
- Start working on a problem before you've
even analyzed all the related problems;
- Get actionable insights without having
to wait until all the relevant data has been collected;
- Make informed decisions faster so that
you can act on them sooner than your competitors do
You need data integration to succeed at revops because it
can help you avoid the problems caused by data overload and silos.
- Data
integration is a key part of revops because it can help you avoid the
problems caused by data overload and silos.
- Data
integration can help you make better decisions, get more value from your
data, and avoid bottlenecks that keep you from making progress.
Conclusion
In conclusion, when you look at the entire process of
revops and how it can be improved by data integration, it becomes clear that
this is a problem that needs to be addressed. Data overload and silos are not
just an issue in RevOps but also in other departments as well. This is why
companies need to address these issues now before they become too big for them
to handle