Companies are moving toward more intelligent data processes. Here
are three steps to take your DataOps strategy to the next level.
By Ramesh Vishwanathan
Data
can provide a vital resource for enterprises of all sizes looking to increase
revenue or differentiate themselves from competitors. It's also more plentiful
than ever, produced in increasingly large volumes by devices and systems
connected through the Internet of Things (IoT). How does business go about fully
leveraging this vast trove of data? Implementing a sound DataOps strategy offers
a best-case solution, yet it can be easier said than done-especially for businesses
struggling to translate their technology investments into tangible business
value.
To overcome this common obstacle and get the most out of their
data, enterprises should consider following a "backwards journey" approach. Outlined
in the following three steps, this common-sense process advises leaders to start
with their business goals and work backwards, leveraging principles of clarity
and pragmatism in creating an effective and sustainable data strategy. Here's
how it works.
Step 1: Identify Your Business Goals
The
first question you should ask is "Why?" It may sound trivial, but many
organizations do not have a clear reason why they want to deploy a DataOps
strategy or invest in new technology. What are your business end goals? Are you
looking to attract or retain customers? Increase your ROI? Meet expected sales targets?
Once you have identified your end goals, it is important for
business and IT leaders to align on what success looks like for their
organization. All too often, technology objectives are set too high, only to
come crashing down due to a lack of data, time, technical capabilities, or a
combination of all three. This is the time to think critically about the intended
role of data and identify potential issues, including the availability of
resources to analyze and make sense of it all.
Step 2: Determining the Processes to Get There
Approach process selection with an open mind by asking yourself, "What does my
organization need to achieve its desired outcomes?" Be sure to assess business
agility (your ability to sense and react to the needs of your customers) and
delivery agility (the ability of your IT department to sense and react to the
needs of the business). These factors, along with other considerations, such as
data availability, time constraints and budget capacity should influence how
you get the job done.
For example, as a nationwide restaurant chain, a client needed to measure
the effectiveness of their sales promotions and improve their customer
engagement. Identifying inherent challenges stemming from their use of on-premise
database technologies and an outdated enterprise business intelligence system, we
partnered with our client to build a next-generation data and analytics
platform leveraging Amazon Web Services (AWS) to uncover new value from their
data. The end result? An increase of average store sales and total customer
transactions, as well as improved average speed of service.
Step 3: Introducing the
Strategy and Approach
So you've selected a strategy
and begun to execute processes. Now what? At this point, key performance
indicators (KPIs) are needed to measure the success of your program and make
necessary adjustments.
Say, for example, your organization
is implementing a strategy that is cloud-service reliant. You'll likely want to
measure usage, performance, reliability, and maturation of that service. With
this information in hand, you should be well-prepared to consider the impact of
your chosen strategy on your business. Be sure to reference back to your
original goals and stay flexible-this will make it easier to introduce new
strategies to meet new goals, as well as achieve higher levels of success.
The Bottom Line
When
executed correctly, this type of "backwards" approach can be immensely valuable
in supporting enterprise end goals, while limiting the divide between deployed
technology and business success. Just remember to be realistic with
expectations and anticipate "bumps in the road." These bumps are normal and should
not impact your overall success, provided you stay flexible and address
challenges head on.
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ABOUT THE AUTHOR
Ramesh Vishwanathan is a practice consulting director with
TEKsystems Global Services, an industry leader in full-stack technology
services, talent services, and real-world application. Ramesh is a data
insights leader, innovator, and AI evangelist. He leads TEKsystems' data
insights practice, focusing on cloud, big data, and AI strategy. He is an
expert at helping customers adopt and mature AI and helps lead them to
data-driven automation and intelligence-driven business processes. You can
contact the author via email or LinkedIn.