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In the modern, fast-paced and digitalized
business world, it is crucial to use data science to your company’s advantage.
New and improving analytics technologies make using and understanding complex
data easier – but a lot of companies are still behind the curve.
In fact, one study from Gartner estimates about
87% of organizations have low Business Intelligence and analytics maturity.
That means most companies are not taking advantage of the data technologies out
there and leaving themselves at risk of falling behind their competition due to
a lack of access to critical, crucial insights like market trend analysis and
Fortunately, that does not have to be the
case for your company. This post will cover a few simple, manageable steps
toward improving your company’s BI and analytics maturity, to improve your data
assets and gain a competitive edge.
Business Intelligence has been defined in
several different ways. In essence, it refers to a business’s awareness of their
market environment, and their capacity to plan, engage and act accordingly
using all resources available.
BI maturity can be understood as to how
current or modern a business’s methods of BI is. The same can be said for
analytics maturity. The tools your company uses to access and analyze data are
a reflection of the maturity in both areas – capitalizing on data to improve
your business’s decision making and keep up with a competitive market starts
with understanding BI and analytics maturity and why it is necessary. It is
important to know where your business stands on the spectrum of maturity, to be
able to implement change and improve.
Businesses with a low BI maturity are
likely to have a much older, outdated IT structure than those with higher
maturity. There is also likely going to be limited communication and
collaboration between the IT sector and other sectors of the business, and
individual units will conduct fragmented analytics projects.
Additionally, low analytics maturity generally
indicates data plays less of a factor in decision-making. To put it another
way, it is less clear amongst businesses with low maturity that proper data
analysis is actually helping to improve business function and decision making.
That means the resources spent on analytics are largely wasted. This can be a
dangerous cycle for a business that does not fully understand the concept of BI
and analytics maturity – the less a business is seeing improvement as a result
of analytics, the less likely they are going to be to invest in new
technologies and improved analytics.
Again, it is common to have a low measure
of BI and analytics maturity – this is an issue a lot of businesses are facing
right now, especially as analytics technology continues to advance. However, businesses
can easily improve in both areas, mainly by following the lead of businesses
with higher maturity.
Businesses with a low BI and analytics
maturity tend to have a fragmented analytics structure, with different sectors
conducting their own analytics projects and poor coordination between IT and
the rest of the business.
One result of this fragmentation is what is
commonly referred to as data silos, or fragmented, stored data in different
areas not contributing to the overall efficiency of the business. You can
imagine this concept exactly like a grain silo on a farm; data is stored in
one, isolated place, and only used for one or two specific purposes, rather
than being spread across the business where everyone can have access to it.
Another dangerous result of the
fragmentation of analytics products is the cost in wasted time, money and
resources. With multiple analytics projects operating within the same business,
and poor communication between them, it is possible for two different teams to
be using different strategies on the same data. That means someone’s effort and
the cost of analytics tools is being wasted.
There is also a high possibility of error
when there is poor communication between analytics projects. Teams of analysts
may have different standards according to their department, and therefore vet
data differently – this can result in significant errors which could wind up
severely costing the company in the long run.
The solution to all these problems? Develop
a holistic, company-wide system of analytics and build a unified strategy for
problem-solving. The less fragmented a business’s analytics projects are, the
more efficient and effective analytics will be.
Better communication between business units
is crucial for raising your company’s BI and analytics maturity. That entails
adopting the same analytics strategies across departments, using the same
platforms to exchange data more easily, and working toward a common goal, while
still allowing individual projects to focus on market-specific data.
Implementing this change is not as
difficult as it sounds. Consulting with analytics professionals is a good first
step into adopting a company-wide strategy and improving holistic analytics
within your business.
As we mentioned at the beginning of this
post, one of the most troubling features of a business with low BI and
analytics maturity is that they are not taking advantage of modern advancements
in the field of analytics.
The reason for this, generally, is business
leaders do not believe they have the resources to do so, or they do not see it
as a worthwhile investment. That reservation is understandable – data science
is an emerging and relatively poorly-understood field. Up until the past few
years, investing in advanced data analytics technologies has not been common
However, it is important to be aware a lack
of modern analytics capabilities can actually be damaging to a business in the
long run, especially as more and more of their competitors begin to adopt them.
You should also remember modern analytics software and platforms are becoming
increasingly automated and easier to use, even for someone without much tech or
Experts recommend building a virtual BI
team within your business – this will help connect unit leaders in a more
holistic strategy, and allow shared access to technologies and platforms.
Skills and strategies can be shared throughout the team, helping everybody to
learn together and ensuring all business units are on the same page with their
In addition, implementing continuous
training for data and analytics teams across the business will help everyone
stay up to date. Because modern software is so automated and intuitive today,
high skills are not as necessary as they used to be. With minimal training,
anyone can understand modern analytics software. It is a small investment in a
huge, helpful change for your business.
This goes in part with improving the
collaboration of analytics projects across business units and developing a
It is important to have a system of
governance for data analysis across your business. For analytics to be as
effective and unified as possible, there should be a set of rules and
regulations for analysis projects. Data analytics leaders can monitor and
implement rules, to ensure all analytics are working in the businesses best
interest and prevent wasting resources and funds on unnecessary projects.
There is software available to help you
implement a system of data governance. This is a good way of lowering the risk
of error caused by different systems of data vetting, as mentioned earlier. It
is also a good way for analytics leaders to keep track of analytics
business-wide, helping expedite a positive impact on decision making.
Another aspect of capitalizing on modern
analytics technology is to create analytics platforms the whole business can
Data analytics leaders in your business
should be able to build integrated platforms that function for a variety of
uses. If everything is operating on one or two main platforms, there is less of
a chance of data silos building up or of errors occurring from
miscommunication. It can also help to make sure analytics teams for all
business units are well trained – if everyone is using the same platform;
teaching the skills to use it is easier.
For a platform to be integrated means it
involves multiple aspects of BI at once. An integrated platform should include
a large data repository – whether a data lake or a more traditional data
warehouse, where company-wide data can be stored and accessed. That way, tools
and strategies for analytics can be collaboratively built onto that platform. This
big data strategy may seem like a tough job at the outset, but it will help to
fast track BI throughout the business, improve holistic communication and allow
for the sharing and transfer of skills and strategies.
As mentioned above, a lot of business leaders have
reservations against investing in improved analytics technology, training, and
resources because it does not seem like it is worth the cost. Businesses may be
frustrated with the lack of connection between data analytics and improved
decision making, or simply be more focused on other sectors.
The reality, though, businesses that do not work to improve
their BI and analytics maturity are at risk of falling behind. As advanced
analytics technologies become more and more accessible, other businesses within
the same field will be making use of them and gaining a competitive edge with
the insights derived from data.
Here are a few ways improving your business’s BI maturity by
implementing the steps above will help your business stay competitive:
With a higher BI and analytics maturity, your business will
be better equipped to utilize big data to track and understand the customer
experience in your field. Have a better idea of what customers are looking for,
what sort of tactics have been working with them and what has not, as well as
changing trends in customer behavior and inclinations.
Of course, every business is already working hard to track
customer experience. A higher BI maturity will help you to make use of the data
faster and more reliably.
Using big data appropriately can help a business to stay
ahead on trends in their field.
BI and analytics maturity can directly impact effective
predictive marketing strategies. Having an older IT infrastructure and poor
communication between business units means trend analysis is not as effective
as it could be – businesses with better BI maturity will make better use of
available data and have more effective predictive marketing.
Perhaps the most important consequence of improving your
business’s BI and analytics maturity is its effect on decision making. Better,
more efficient big data analysis will lead to more detailed insights, improved
forecasts and a better understanding of competitors, which will, in turn,
result in informed decisions limit risk to your company.
Better decision making is the ultimate goal of data
analytics. The higher your business’s BI and analytical maturity, the more
accessible that goal is.
The vast majority of businesses have a low or improvable BI
and analytics maturity. That means the vast majority of businesses are not
making use of the data can improve their performance and give them an edge
above the competition.
The steps listed in this post were recommended by experts,
based on a Gartner report on raising BI and analytics maturity and improving
the use of data in any business. They can be implemented without much risk or
cost to your business and can have a significant impact on data analysis and
decision making in the long run.
A high BI maturity is a necessary step in keeping up with the
modern world – every business should take the chance to improve theirs now
before they fall behind.
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