Stax was founded with an approach of bringing specialized data and analytics
teams and proprietary
technology to our corporate and private equity clients. It is part of our
DNA. While we’ve been doing this for almost 3 decades, it is still early days for PE sponsors and their
portfolio companies and opportunity abounds. We see a handful of natural entry points for bringing data
and analytics to private equity sponsors and the management teams of portfolio companies.
Markets and customers
Market penetration and
growth, risk, and unlocked value
Profitability and pricing
Product bundling or
Marketing and sales, and
Geo-location expansion or
Forecasting, whether of the industry, company, customer needs, or product specific
Operations and logistics optimization
Most PE deal teams are working in Excel,
taking weeks to compile seller data and often without the ability to match external data with
data, within the deal timeframe. Stax’s analytics teams and proprietary
technology can rapidly
and turn data into insights in short order. Early identification of key risks and potential profit
levers provide both a knowledge and timing advantage.
We further leverage proprietary
bring in outside data to compare the inside view and the outside-in view. Stax’s Data
Due Diligence (DS-CDD) can be delivered as a standalone offering and is frequently integrated with
Stax’s scaled due diligence and market studies, which includes the array of understanding market
and primary research with customers, competitors and channels. This combination which allows client
teams to see rapidly assess unknown risks, and more importantly, identify and quantify growth, and
develop conviction on a deal.
The Stax Value Creation journey with data science over the PE-hold period
Stax helps corporate clients and
portfolio companies rapidly drive value with data and analytics, across three types of
In all we’re helping clients answer significant questions with rigor, freeing up a lot of
and by reducing frustration from the unknown.
Why? Most organizations have important questions, but their data resides in multiple data
systems often with data integrity issues which prevents clients from taking action.
Similarly, while organizations believe there is external data to match, they do not have the
resources to bring them together for insights. Stax brings a PE-mindset, specialized teams,
with deep expertise in data extraction, ingestion, cleaning,
data science, and strategy consulting, to bring these elements together in an offering that
fast, agile, outcomes oriented, and cost effective for mid-cap and private equity-backed
Private equity backed executives and their investors know there should be enough data on
externalities that can be analyzed together with company performance data, to gain insights
inform key operating and investment decisions. Such scenarios often require real data
and technical skills for acquiring and managing large data sets, an experience-based
in sourcing data to test, industry perspective, and the intellectual curiosity and
to get to the answers that matter.
Our data science projects are staffed with experts across our specialist teams. Using this
unique structure and an agile process, we help clients who can hire any firm in the world,
answer incredibly valuable questions for major investment and operating decisions. For
management teams, we answer their important and historically nagging questions, helping them
focus on what matters more, clearing away what matters less, and driving better overall
Most organizations either want to better leverage data to manage their business or they are
already on a data journey. When clients ask the best way to set-up analytics platforms, we
first suggest choosing important questions to answer and building agile platforms, utilizing
mostly off-the-shelf technology to answer those questions.
Why? Because we deliver what you need. We find it’s an easier lift for the organization to
quickly drive ROI and learnings, and the organization generates internal energy to continue
along with a better view as to what might need scaling up. This also minimizes the risk of
trying to install new, large-scale analytics platforms before demonstrating the answers and
insight you can derive.
As the CFO, COO, CEO, or any CXO in a company planning for exit, you have a tremendous amount of
financial, operating, and customer data and information to prepare and explain multiple times to
advisors and a variety of potential investors, each with different specific questions. Ideally, all of
the data could be connected to explain the story and highlight the profit opportunities, and in a format
that doesn’t require you to run new reports to answer all of the questions on a case-by-case basis.
You could probably use an experienced hand amassing all the data and putting it into an easy-to-use
format, and the resources to develop the insights and answers to questions that you have wanted to know,
those that should be answered within an investor presentation, and those that will probably come up as
reasonable questions from a buyer’s due diligence.
Questions may include the drivers of performance, e.g., how they correlate to markets and competition,
labor or costs of materials, trends in customer acquisition, pricing and margin, and the pockets of
profit opportunity that you think could be improved, whether through pricing, sourcing, working capital
management, logistics, etc. You may not need to share all this information with potential investors, but
better to be well versed and ready.
Stax brings specialized teams and extensive buy-side experience to the table. We have a good sense of
what the next investors are going to ask given 25 years on the buy-side, knowing the sectors, the
assets, and a lot of the deal teams personally. Our role is to help you identify, explain, and highlight
opportunities for growth with the new investment.
The Analytics Edge is a data enablement platform comprised of our
proprietary software as well as
industry-leading technologies. The
platform allows our Data Teams to rapidly move from problem to insight by enriching data, populating
analyses, generating models, and
deploying reporting mechanisms, all regardless of industry or business size.
MDM automates the audits of data
rooms and document archives
allowing analysts to quickly tag
files for investigation, search for
and extract relevant datasets, and
put together analysis plans that can
be shared with clients and deal
Powered by Natural Language
Processing, Stringer enables our
analysts to quickly match and unify
datasets of textual information. It is
an algorithmic systematization of
our past learnings from semi automated attempts at string
SocialSense is an approach to
understanding the reasons behind
customer sentiment at any given
time. Powered by a machine
learning model trained on company
and product reviews, the tool
intelligently arranges information
into topics and sub-topics.