Accelerating Growth and Business Performance in Middle Market Companies
About This Report
Analytics is not new, but it is only now coming into
its own as a business capability and strategic weapon.
In a January 2000 Harvard Business Review article, Thomas
Davenport, the President’s Distinguished Professor in
Management and Information Technology at Babson College,
described how a handful of companies including Amazon,
Harrah’s, Capital One, and the Boston Red Sox, were at the
time “dominating their fields by deploying industrial-strength
analytics across a wide variety of activities.”1 These pioneers
were among the first to learn and exploit the value of using
data to make better and more strategic business decisions and
propel themselves to the head of their industries.
Since then, the analytics industry in the United States has grown
to employ roughly three million people, according to estimates
by PricewaterhouseCoopers and others. International Data
Corporation (IDC) puts the total market for analytics-related
hardware, software, and services at $189.1 billion. Many companies
have learned to use analytics as a strategic weapon, wielding the
insights gained to innovate offerings, improve processes, and
“outsmart” their competitors. As business analytics increasingly
becomes a “must have” for organizations that wish to remain
competitive and make more informed decisions across all areas
of the business, these numbers will continue to escalate.
ANALYTICS IS A CRITICAL CAPABILITY WITHIN
THE DIGITAL TRANSFORMATION FRAMEWORK
This report represents one of the first outcomes of the Center’s
ongoing and comprehensive exploration of digital transformation
in the middle market. It illustrates how analytics is an essential
capability within the Digital Transformation Framework
presented in The Case for Digital Transformation. As this report
demonstrates, analytics has implications for every element of the
framework and can help inform decisions at the enterprise level
as well as within each of the functional areas of the business.
HOW THE RESEARCH WAS CONDUCTED
To better understand the analytics landscape in the middle
market, the National Center for the Middle Market worked with
its partners and Ralph Greco, Senior Lecturer and the Director
of the Nationwide Center for Advanced Customer Insights, The
Ohio State University Fisher College of Business, to query 1,000
middle market CEOs, CFOs, and other C-suite executives about
the importance of analytics to their business and the analytics
capabilities and tools they deploy. We asked about the kinds
of business questions they answer with analytics solutions and
explored the challenges associated with adopting and using the
technologies. These questions were part of the Center’s quarterly
Middle Market Indicator survey.
This report shares the results and explores the characteristics
of strategic analytics users as well as the impact of analytics on
growth and business performance.
EXECUTIVE SUMMARY
Analytics unlocks stronger
middle market performance
KEY TAKEAWAYS
- ANALYTICS AND GROWTH GO HAND-IN-HAND
There is a strong positive correlation between company growth and the use of analytics
solutions. There is also, however, a large gap between current and potential use of
analytics in the middle market.
- ANALYTICS TOOLS IMPROVE CORE FUNCTIONAL CAPABILITIES
Analytics investments in specific areas (such as workforce optimization or marketing
effectiveness) produce demonstrable performance improvements in those areas.
- POSITIVE SYNERGIES RESULT FROM USING MULTIPLE ANALYTICS TOOLS
Middle market companies that use both outward-facing tools (demand planning and
forecasting, marketing effectiveness, etc.) as well as inward-facing tools (such as workforce
optimization, quality improvement) enjoy faster growth rates than firms that use only one
type or the other.
- ADOPTION CHALLENGES FALL INTO FOUR CATEGORIES
Formidable resource, cultural, and talent challenges stand in the way of full-force
adoption of analytics, but these difficulties become significantly less pronounced as
companies gain experience. Poor quality data is also a formidable obstacle, leading to
both direct and opportunity costs for businesses. But good data has the potential to
transform business performance.
WHAT DO WE MEAN BY ANALYTICS?
Analytics is an essential capability within a middle market
company’s digital transformation journey. For this report, we
have adopted the definition from INFORMS, the world’s largest
professional association dedicated to best practices and
advances in operations research, management science, and
analytics. The organization describes analytics as “the scientific process of transforming data into insights for the purpose of making better decisions.”
The INFORMS definition of analytics includes three noteworthy
elements:
- Science: Analytics follows the scientific method of question-hypothesis-
experiment-observation-analysis-conclusion.
- Insights: Analytics transforms data into insights—“aha!”
moments that reveal something not known before.
- Actions: Those insights lead to decisions that are better than
they would have been without analytics.
Analytics capabilities are themselves agnostic. Their value
emerges when they are used to advance a defined strategic
purpose and, as INFORMS says, “empower an organization’s
vision.” Given the investment in technology and talent analytics
requires, middle market executives must be especially mindful
of how they allocate their limited resources to make sure they
are investing in tools that will help them make smarter decisions
about key issues for their businesses. Analytics makes sense
when it makes an impact.
Consider the New England Patriots, a middle-market-sized
organization that uses analytics in novel and effective ways to
help build and maintain a championship-caliber football team.
The Pats have developed a proprietary database that the team
uses for scouting purposes and to assess the effectiveness
of its individual scouts. The organization also employs the
NFL’s only Player Personnel Engineer; when the team found
the right candidate to staff the role, it was someone who was
also entertaining an offer from Google. While the Pats’ use of
analytics in its business office has been heralded in numerous
publications, during an interview early in the 2019 season,
Coach Bill Belichick said he relies on analytics “less than zero” when making on-field decisions like whether or not to “go for it” on fourth down. This comment might have been somewhat
disingenuous—hiding the football, so to speak; Belichick is,
after all, the recipient of a lifetime analytics achievement award
from MIT. Still, when he contends that “football is ultimately
determined on the field,” he is highlighting a crucial point:
Analytics is an input to decisions, not the decision itself. Teams
still need strategy and leadership to win.
In the game of business, too, analytics appears to affect results,
particularly when executives use its insights strategically. Overall,
the more a middle market company invests in analytics, the
faster it grows. And when businesses use analytics for clear
purposes—optimizing the workforce, demand planning, or
optimizing revenue from a new product launch, for example—
those areas of the business improve. Analytics also positively
affects operational competencies, resulting in improved machine
uptime, quality control, and supply chain management, as well
as risk and compliance. And the benefits of analytics appear to
compound; companies that use analytics for both outward-facing
purposes (to gauge marketing effectiveness, for example) and
inward-facing purposes (i.e. workforce optimization or quality
improvement) grow faster than peers that use analytics for just
one objective or the other. Heavy analytics users also predict
much more aggressive growth for the year ahead than companies
that use analytics sparingly or not at all.
However, there is an enormous gap between the current use
and value of analytics and its potential contribution. Most
middle market companies use at least one type of analytics
tool. However, no one capability or tool type that we explored in
our study is currently in use by a majority of all middle market
firms. Embracing analytics full force, it appears, may take more
effort than many companies have been willing or able to give.
Indeed, many executives express desire to use more tools and
expand their analytics capabilities, but issues such as data quality,
resources, culture, and skills stand in the way.
Still some companies have found a way: Every one of the tools
and capabilities in our study is currently in use by 50% or more
of the subset of middle market organizations that consider
themselves to be digitally strategic firms. And the performance of
these companies consistently outpaces their peers.
By exploring solutions to adoption challenges, pinpointing the
business goals where analytics can deliver the greatest value, and
investing strategically, middle market organizations can unlock
performance gains, increase profitability, and accelerate growth.
Overview: Middle Market Companies
Use Analytics to Inform a Wide Range
of Business Questions
Analytics can be used to study anything for which data
exists. As this framework from MIT Sloan Management Review
illustrates, the science can be leveraged for operational or
strategic purposes and can be used to monitor and control
processes and systems, or to provide input and context for
decisions. Most companies first employ analytics in operational
areas, to monitor and control equipment and processes. As
they gain experience, executives discover opportunities to use
analytics to gain insights that shape strategic decisions. The
more uncertainty exists around a decision, the more valuable
analytic input becomes. Indeed, many experts suggest that
analytics should always be action-driven, providing insight for
the purpose of making better decisions.
The Center looked at the middle market’s use of analytics across
a number of inward-facing, outward-facing, and foundational
analytics tools and capabilities and explored how analytics can
help business leaders answer questions within each area with a
greater degree of accuracy.
Most firms use analytics now and plan on using more in the near future
CURRENT USE OF ANALYTICS
Most middle market leaders believe analytics is important to
business and will become increasingly so over the next five years.
The vast majority (85%) of middle market companies currently
use analytics to some degree; and most have adopted multiple
tools. Analytics is most popular for outward-facing activities, such
as demand planning, forecasting, and marketing effectiveness.
However, no one capability or tool is currently in use by a majority
of middle market companies.
FUTURE USE OF ANALYTICS
Many companies plan to begin using analytics technologies
within the next 18 months. But for now, it appears that most
mid-sized companies are in the beginning phases of analytics
use or are focusing on one area or another rather than deploying
tools across many activities. Even foundational tools like business
intelligence reporting and data visualization are only in use by
a little more than a third of middle market organizations, and
roughly another 30% have no plans to pick up these foundational
tools in the near term, which may put them at special risk of
falling behind in their digital journeys.
Industry and company size shape analytics adoption and priorities
Middle market companies benefit from analytics in different ways
and, accordingly, make different choices about what capabilities
to use. Some of these decisions depend on the type, size, and
digital attitudes of a firm:
- The digital intensity of the organization appears to be the
single greatest factor in analytics use. Companies that say
their digital vision is clear and comprehensive are by far the
heaviest users of analytics. Among this subset of firms, every
one of the analytics solutions we explored is in use by a
majority of the firms.
- Industry, too, has a profound impact on analytics use and
specifically influences which business questions are answered
and the types of tools deployed to glean those insights.
- Larger middle market firms are much heavier users of analytics
than their smaller peers.
- Younger companies—those born in the digital era—are no more
likely to be analytics users than older ones.
Digitally strategic firms combine vision with the right toolkit to drive growth
While size and industry correlate to analytics use, another
factor supersedes these: the digital intensity of the
organization. Across revenue and industry segments, middle
companies that have a clear, comprehensive digital vision to
guide strategic decisions grow, on average, 75% faster than less
digitally sophisticated peers.
Companies with this vision and those that are pursuing digital
transformation as a strategic priority place much greater
importance on business analytics than others. They use more
tool types and they are heavier adopters of each type of tool
they use. Among those companies saying their digital vision is
clear and comprehensive, every one of the analytics solutions we
explored—inward-facing, outward-facing, and foundational—is in
use by a majority of the firms. These companies use technologies
not only to drive efficiencies or automate manual processes,
but also to better connect with and serve customers and set
themselves apart from the competition.
FOUR KEY INSIGHTS
While analytics drive growth and value,
there are challenges to adoption
As we’ve seen, the use of analytics tools by middle market
firms, as well as the specific types of capabilities used, vary
considerably based on a firm’s digital intensity, industry, and
size. While most middle market companies are at least dabbling
in analytics and many have plans to expand use, the majority of
mid-sized companies can be categorized as moderate analytics
users; they have ground to cover to fully exploit the capability
and achieve a state of analytics maturity. The exception to this is
the subset of digitally-strategic firms, which have found ways to
integrate the power of analytics throughout their businesses.
The next section of this report will focus on insights related to
the impact of analytics as well as the challenges middle market
companies must overcome in order to increase analytics use and
take advantage of the benefits that come with it.
INSIGHT 1
Analytics and growth go hand-in-hand
FAST GROWERS INVEST MORE IN ANALYTICS
Middle market companies growing revenue at 10%+ per year
are more likely to place high priority on business analytics than
slower-growing peers. The correlation runs both ways: Businesses
that say analytics is extremely important boast a revenue growth
rate that is more than double the rate of companies that pay little
attention to their data. And they add employment nearly four
times faster.
Current use of analytics will fuel tomorrow’s growth
Fast growers use more analytics tools. They are especially more
likely to use business intelligence reporting, a foundational
tool, and somewhat more likely to have invested in many of the
inward- and outward-facing analytics technologies.
Pronounced differences show up when looking at growth
projections. Middle market companies with the most aggressive
revenue growth expectations are much more likely than others
to be current users of outward-facing analytics capabilities.
This suggests that middle market leaders have a high level of
confidence in the insights they are gaining from their tools and
the power of those insights to generate sales.
Those with the highest growth projections also use inward-facing
analytics much more than their peers. The implication
is that leaders of these companies have a more sophisticated
understanding not just of their market, but also of the resources
they need to mobilize to satisfy demand.
INSIGHT 2
Specific types of analytics tools
improve core functional capabilities
Use of analytics appears to strengthen capabilities within the
functions where it is used. For example, workforce optimization
analytics makes companies stronger in many dimensions of talent
management; marketing analytics improves both marketing and
sales effectiveness.
WORKFORCE OPTIMIZATION
Workforce optimization helps companies get the most from their
employees by having the right labor at the right place and time
to meet the needs of customers and the business. Workforce
optimization can include tools for helping managers develop
staffing plans and determining the best times to schedule certain
types of work, such as restocking or receiving inventory. It can
help plan seasonal work. It can help with assessing employee
performance while also driving higher employee satisfaction
through tools that monitor employee engagement and help
promote work-life balance. And it can help companies better
respond to and prepare for the ways their customers want to do
business. For example, in the retail industry, shifts to BOPIS (buy
online, pickup in store) as well as BOSFS (buy online, ship from
store) have required store staff to become pick/pack/ship experts.
Retailers and other service businesses can also use analytics to
determine the best mix of live, person-to-person interaction verses
self-service activity and kiosks, such as offering customers the
option of ordering different sizes off iPads in the changing room.
Like many tools, workforce optimization can be used for
good or ill. Starbucks was heavily criticized in 2014 for its
(software-driven) scheduling practices; but it has since made
improvements, including adopting software that helps ensure
employees get adequate breaks in between shifts.
Across all industries, companies that invest in workforce
optimization analytics grow both revenues and employment
faster than their peers and have much stronger predictions for
future growth. They are also significantly more likely to rate
themselves as very good or excellent on talent management
metrics, including attracting top talent. However, even heavy
analytics users report facing both long- and short-term talent
management challenges. While analytics can and does help,
companies still need strong leadership and vision to address
strategic issues related to talent, including upskilling, outsourcing,
and developing forward-looking versus reactive talent plans.
CUSTOMER-FACING ANALYTICS
Customer-facing analytics is a complex set of outward-facing
tools that includes demand planning and forecasting, sales and
marketing effectiveness, and churn prediction and prevention.
These tools allow companies to understand customer behavior with
unprecedented detail, identify the most profitable customers and
those most likely to jump ship, and make smarter marketing plans
and pricing decisions tailored to different customer segments.
Netflix provides a textbook example. A digitally-born company,
Netflix used analytics from the get-go to disrupt and transform
the entertainment industry, almost singlehandedly putting
Blockbuster out of business before moving into streaming
content, and finally, original content generation. Today it uses
what it learns about customers through analytics to gain and
retain subscribers by suggesting microtargeted genres—they have created 76,897 different ways to describe types of movies specifically for this purpose!—and pretest series ideas to ensure
their success.
Middle market companies, too, perform better when they
leverage customer-facing analytics. The online stylist, Stitch Fix—
which recently graduated from the middle market—has made
it a critical component of its business model. Founder and CEO
Katrina Lake wrote in a 2018 Harvard Business Review article,
"The part of me that loves data knew it could be used to create
a better experience with apparel." She built her business around
data with a human touch. Customers supply Stitch Fix with
millions of data points each year by completing an initial style
profile and subsequent reviews of each order. This information,
along with data and measurements on each garment, are fed into
a set of algorithms. The results are interpreted, reviewed, and approved by a stylist, who is algorithmically matched with each
client. The combination of the right data and the right expertise
allows the company to successfully deliver personalized boxes
of clothing and accessories to each of its two million-plus clients,
driving the company’s revenues up each year.
Like Stitch Fix, middle market companies that use customer-facing
analytics grow faster than those that don't. And they
self-rate themselves as more adept at customer acquisition and
business performance competencies.
NEW PRODUCT LAUNCH REVENUE OPTIMIZATION
Another outward-facing tool, revenue optimization analytics
focuses on maximizing revenue over the long term by looking at the
relationships between pricing, inventory, demand, and distribution.
It seeks insight into demand patterns and how pricing and other
factors can help to influence and shape that demand. For example,
retailers today use analytics to selectively distribute targeted
ecommerce incentives. They use the data to understand what offers
will entice which groups of consumers to sign up for their emails or
rewards program and what offers are most likely to result in trial and
repeat purchases. Over time, as they learn what a customer’s email
address is worth and analyze the behavior of individual customers,
they are able to refine these offers even more.
Such knowledge becomes especially important when launching a
new product and making decisions about where, how, to whom,
and for how much to sell it. Among middle market companies,
over a quarter (28%) currently use new product revenue
optimization analytics tools. That percentage rises to 40% among
the largest middle market companies.
The insights these companies gain drive innovation and growth:
Users are significantly more likely than peers who do not use
revenue optimization analytics to have plans for introducing a
new product service in the next year. They are more than twice
as likely to have plans to increase their investment in R&D. They
consider their businesses to be much more advanced than their
peers in both innovation and customer acquisition.
INSIGHT 3
Analytics increases in value
when it is used organization-wide
Middle market companies have many options when investing their
analytics dollars. As we’ve seen, many companies are beginners,
testing the waters by choosing to start with one type of tool or
another rather than deploying analytics full force across business
functions and activities.
Where they start often comes down to the types of business
questions a company wants to inform as well as the company’s
overall objectives. Businesses looking to maximize revenue
growth may naturally gravitate toward outward-facing tools. And
the data suggest that’s a smart move: Companies that use only
outward-facing analytics grow revenues considerably faster than
business that use only inward-facing tools. On the other hand,
companies looking to expand their workforce or improve labor
productivity may fair better by choosing inward-facing tools.
Employment growth is higher among companies that only use
inward-facing analytics compared to those that use only the
outward-facing set of tools.
Combining the tool types, however, may increase the return
on investment in each of the individual tools. Businesses that
invest in both outward- and inward-facing tools post the highest
revenue and employment growth rates. This suggests that positive
synergies exist between different types of analytics tools and that
the value and impact of analytics compounds and accelerates in
a virtuous circle. As we will show in the next section, the more
analytics tools a company uses, the more it reduces the challenges
to analytics adoption, and the more it improves overall data quality,
ultimately making the outcomes more valid and more useful.
So, while many companies appear to want to start slow, it is worth
considering the impact of a broader approach to analytics adoption:
Use the right outward- and inward-facing tools (i.e. make an
investment in analytics across your organization as opposed to one
specific area, or, better, include analytics at the Enterprise level of
your Digital Transformation framework) and you can position your
business for improvement across multiple dimensions, unlocking the
full potential impact of analytics as a strategic digital capability.
INSIGHT 4
Challenges with adopting analytics fall into four
categories: data, resources, culture, and skills
Growth and business performance data make a clear case for
the adoption of analytics to improve both outward-facing and
inward-facing decisions. However, no more than 50% of middle
market companies currently leverages any one analytics tool;
there is not a majority even for foundational tools like data
visualization and business intelligence reporting. It’s not that
executives don’t want access to data for analysis and action. So
what holds them back? Middle market executives point to four
groups of challenges standing in the way of analytics adoption:
data, resources, culture, and skills.
DATA
Assessing and aggregating multiple sources of data is a challenge
for companies of all sizes, but data quality issues appear to
compound as a company grows. This is likely because larger
middle market businesses have more customers, more employees,
and, as a result, more data to manage. Quality issues can be
as mundane as variances in how customers are listed—IBM, vs.
I.B.M. vs. International Business Machines, for example—which
can keep a company from seeing a comprehensive view of its
business with a particular organization. Other problems, such as
incompleteness, or, worse, inaccuracy, also detract from the value
of analytics.
RESOURCES
From our digitization trends study, we know that middle market
companies are most likely to give themselves average scores in
terms of digital readiness. Interestingly, large and fast-growing
companies are more likely than their smaller and slower-growing
peers to say limited IT resources hold them back—perhaps
because they also are the companies with the biggest analytics
appetite. As companies do more analytics, the costs also grow
faster as strategic complexity, computational requirements, and
the need for more talent escalates. Only 12% of all middle market
companies point to budget as a deterrent to analytics adoption.
But this percentage jumps to 20%, or 1 out of 5 companies,
with revenues between $100M and $1B and 16% for companies
growing revenues at an annual rate of 10% or more.
CULTURE
In general, companies that don’t see the business need for
analytics, have a siloed as opposed to an organization-wide
approach to technology, or look for the immediate ROI instead
of appreciating the strategic, long-term benefit afforded by
the insights, will have a harder time justifying an investment in
analytics. In companies that just are not digitally intensive, the
culture obstacle exacerbates all of the other challenges—data,
resources, and skills—and makes each harder to surmount.
Curiously, culture-related issues appear to be bigger challenges
for faster-growing firms, particularly the ability to measure ROI.
The explanation for this, too, might be a question of priorities
all jostling for management and employee attention: Open a
new facility or invest in analytics? Analytics can help companies
make smarter growth decisions, but when you are head-down
running the business, it can be difficult to look up to examine
ways to change it.
SKILLS
Study after study of digital transformation shows that lack
of digital skills is a challenge for middle market firms. Forty
percent of middle market companies claim that talent gaps
slow their adoption of analytics. The problem is most acute for
the largest middle market firms, which, again, have the biggest
appetites for analytics. Companies that are growing at a modest
rate feel the greatest pinch when it comes to the skill level of
their current workforce.
Analytics use can help solve analytics-related challenges
The more essential executives say analytics is, the more
challenges they say they face in adopting and utilizing analytics
solutions. Perhaps this is because they take a more strategic
approach to analytics and, like teachers who demand more of
a student with great potential, they ask analytics to do more
complex things, and they place more value on the outcomes.
However, as companies integrate analytics into their businesses,
using a greater overall number of tools as they do so, virtually
all the challenges become less pronounced. It appears that the
very act of using analytics can help with issues such as improving
data quality, measuring ROI, and improving a company’s ability
to aggregate its data. The more the data is used, the cleaner it
becomes, and the more useful the outcomes, creating both a
learning curve and a virtuous circle.
The major exception to this trend is the resources problem. The
more analytics solutions a company adopts, the more resources
it needs.
The High Cost of Bad Data
Data quality is an issue for middle market firms, regardless of
which end of the revenue spectrum they fall on or how quickly
they are growing. Middle market firms are not alone in this
challenge. According to findings from Dun & Bradstreet’s B2B Marketing Data Report, only 51% of respondents are confident of
the current quality of sales and marketing data, down from 75%
the previous year. Findings from IBM data scientists reveal that
one out of three business leaders don’t trust the data they use to
make decisions and that more than a quarter are unsure of the
“veracity” or accuracy of their data.
These misgivings are well-placed. According to 2017 Deloitte research, data provided by U.S.-based big data brokers is only 50%
accurate at best. Across categories, including economic, vehicle,
demographic, interest, purchase, and home, 71% of consumers
judged that the data collected about them was somewherebetween dead wrong and only half right (0-50% correct).
The impact of bad data is significant. Gartner’s Data Quality Market
Survey put the average annual financial cost of poor-quality data
at $15 million in 2017. Inaccurate data can cause companies to miss
opportunities or, worse, to offend or alienate their customers. In
healthcare, inaccurate data can lead to errors in as many as one in four explanation-of-benefits claims, degrading the patient
experience and leading to confusion and delayed payments.
Good data, on the other hand, can transform a business and give
it insights to more accurately forecast demand, optimize revenue
and workforce, target and build customer relationships, manage
risk, identify fraud, and comply with regulatory requirements.
Validating the quality of data, then, should be a key part of any
company’s analytics journey.
CONCLUSION
Finding ways to embrace analytics
is vital to continued growth
Analytics adoption does not always come easy to middle market
businesses. Formidable challenges associated with a company’s
data, available talent, culture, and resources stand in the way of
widespread use of analytics in both outward-facing and inward-facing
areas of the business, where the insights could surely lead
to better decision making and, ultimately, improved performance
and faster growth.
However, companies that take a slow or scattershot approach to
analytics do so to their own detriment. Our data show that middle
market companies that use analytics outperform those that don’t,
and the more capabilities they use, the faster they grow and the
better they cope with the challenges of using analytics.
Those middle market companies that have found ways to
overcome the hurdles and put strategic analytics capabilities and
tools into place have seen the impact in their top line revenue,
their employment growth, and their key business functions. And
they are anticipating even stronger growth in the year ahead,
likely fueled in part by the knowledge they will gain from their
data analysis efforts.
Next Steps in Your Analytics Journey
Middle market businesses looking to increase their investment in analytics, or to derive more values
from the analytics investments they have already made, can start by taking the following steps:
-
SELF-ASSESS WHERE YOUR COMPANY
STANDS ON THE JOURNEY THAT IS ANALYTICS.
Several tools exist that will provide your company with its
current analytics “maturity” rating, typically on a scale from
1 to 5. One such model is the Analytics Maturity Model from
INFORMS. This assessment can be completed at no cost. The
questions focus on three areas: Data, Skills, and Corporate
Structure, which align with the challenges most middle market
companies face in adopting analytics. Once you have completed
the AMM, you can benchmark yourself against others in your
industry to see what gaps exist. The results of this exercise can
go a long way in gaining C-suite support for the use of analytics
in your business and further investment in the area.
-
IDENTIFY YOUR SKILLS GAPS AND FIND
WAYS TO ATTRACT AND RETAIN EMPLOYEES
WITH THE RIGHT DIGITAL SKILLS TO SUPPORT
YOUR ANALYTICS JOURNEY.
Measure the skills of the employees currently working in
analytics as well as the skills of the employees who will be
utilizing the output of the analytics. This will take time and
effort; however, it is key to ensuring success with analytics.
Again, there are multiple tools available to assist in this step.
Once you have an understanding of your in-house skills, you
can better determine where you may need to upskill current
workers or look for new hires. And you can start to flesh out a
plan to build and maintain the digital skills your firm needs.
-
VALIDATE THE QUALITY OF YOUR DATA—
AND THE PROCESSES FOR COLLECTING
AND STORING IT.
Companies need to be vigilant about understanding data
sources. This starts with determining what business questions
you want to ask, and then seeing if data are available to help
you answer them. Leaders then need to get a sense of how
accurate a data set is before relying upon it to inform critical
decisions. For most middle market firms, financial and systems
data tends to be strong, especially data that needs to be
reported per any regulatory requirements. Customer and HR
data, however, can be weaker.
Leaders can use their business acumen and expertise to help
gauge if a specific data set is valid or not. If the insights you’re
receiving seem “off,” consider evaluating your processes for how
you collect and store data, looking for weak spots that could
compromise its integrity. External data experts can help with
your assessments as well as with putting processes in place to
help improve overall data quality. Keep in mind, however, that
just because the data don’t gel with what you were expecting
doesn’t mean they’re wrong. Analytics could simply be doing its
job—opening your eyes to issues that need to be examined.
-
DETERMINE WHICH ANALYTICS PROJECTS
YOUR COMPANY WILL HAVE THE MOST
SUCCESS WITH COMPLETING AND
IMPLEMENTING RIGHT NOW.
Since analytics use in and of itself appears to mitigate
many of the challenges associated with adoption, simply
getting started may be the best place to start. You’ll want to
strategically select an analytics solution or two that can inform
issues that are critical to your business and industry, and then
ensure that you have the right skills and data available in order
to effectively use these tools. Once you begin the journey, the
benefits will compound from there in several ways. First, the
more you use your data, the cleaner it gets. And second, you’ll
begin to generate important insights that inform new business
decisions, including where to best invest future analytics or
digital dollars, ultimately driving analytics maturity and making
your business smarter and stronger along the way.