Data-driven Decision Making:  The Age of Analytics

Mohammed Zakir

President of Acustrategy Analytics is a gradued from MIT Sloan School of Management.


Data-driven decision making:  The age of analytics

An overwhelming majority of organizations today invest in data assets.  Be it spreadsheets, accounting software, enterprise systems, or the cloud, companies spend precious resources in collecting and storing their financial, operations, marketing, sales, and customer data.

As with any investment, the question naturally arises: What is the ROI on data?  In other words, there is a realization that data collection and storage are only worthwhile when the data are made to work for the business and generate profits.

Consequently, organizations ranging from family-run outfits, small businesses, global conglomerates, government, and non-profit entities are all looking to extract a return on their data investments.  They are doing so by using analytics to draw insights from their data to help them make strategic decisions and implement day-to-day tactical actions. There is thus an increased push toward what is called “data-driven decision making.”

What exactly is data-driven decision making?

Every business must continually ask some key questions.  These include, for example, how do we minimize our operational costs and increase our profitability? Or, how do we retain and grow our customers? Or, what is the best product portfolio at the right price for the right customer?

Not so long ago businesses answered such questions using valuable management intuition built on past experience and anecdotal evidence.  A data-driven approach does not seek to replace this intuition; rather it seeks to confirm it to ensure that important decisions are always grounded in fact.

Consider a business that is contemplating a price increase.  Some managers may oppose the move because of the belief that some large customers will walk away. An analysis of customer data can help the decision makers find out whether these customers (1) have responded negatively to past price increases, (2) are representative of the entire customer base, and (3) are worth keeping given the business’s strategic goals.

Examples of management beliefs that are ripe for data validation:

  • Customers who buy multiple products are more valuable.
  • Larger customers are more price sensitive and more likely to switch vendors.
  • Customers who buy more are also more profitable.

In doing so, the business will validate management beliefs and hypotheses and ensure its pricing decision is “data-driven” and not based on instinct alone.     

Who can benefit from data-driven decision making?

The simple answer is every organization and every level of an organization can benefit from data analytics and data-driven decision making.

Businesses have access to two types of data: its internal data and publicly available data.

Management can use their internal data (such as financial, operations, marketing, sales, and customer data) to understand trends in key performance indicators, conduct performance optimization of labor and assets, identify emerging opportunities for pricing and product bundling, segment the customer base and create marketing and sales strategies to target each segment, predict customer behavior, and so forth.

Publicly available data are databases that the federal, state, and local governments make available to their citizens.  These include census, climate, consumer, education, energy, geospatial, government spending and vendor payments, healthcare, intellectual property, labor, law enforcement, public safety, public health, trade, and transportation data.

Public data can help businesses know more about their target market and untapped business opportunities. For example, a healthcare business can study census, healthcare, public health, and transportation data to determine where to best locate new facilities.  Or a minority-owned construction company can analyze government contracting data to target government agencies that have a large construction spend as well as an underrepresentation of minority vendors.

How can my business become data driven?

A data-driven organization is one in which every person who can use data to make decisions has access to the data when needed.

Businesses often hire analysts who work with spreadsheets and create basic reports on a daily or weekly basis. Although spreadsheet analysis is a great starting point for analysis, it is not analytics and often provides little insight into business needs or decision making.

A data-driven firm needs three essential ingredients: (1) integration of key datasets, (2) cutting-edge analytics talent and tools, and (3) people to create business value from the insights.

The power of data comes into play when different datasets are combined to get a holistic picture of a business and the market.  A business cannot make the best decision by using its financial or operations or customer data alone. Instead, it is when financial, operations, and customer data are combined and tie up neatly that a business has a complete and accurate view of itself.

While businesses have access to internal and public data they frequently do not have the bandwidth to take on the labor-intensive tasks of integrating and cleaning large, messy datasets to ensure that the critical inputs required for any analytics exercise are both included and checked for accuracy and quality.

Similarly, many businesses invest in the leading analytics tools yet because of a limited talent pool are unable to find recruits who have the skillset to ask pertinent questions of decision makers, frame business hypotheses, and fully exploit the tools to extract the necessary business insights from data.

Finally, converting analytics to strategic plans and tactical actions requires a relatively rare mix of business experience and analytics knowledge. Businesses need the right people to translate analytics into business insights that are delivered at the right time to decision makers and incorporated into business decisions.

Businesses have responded in different ways to these challenges.  Those without budgetary constraints choose to create dedicated analytics groups or departments.  Others rely on external providers such as Acustrategy Analytics that bring a rare and powerful combination of data science and business expertise to help bridge the analytics gap.  Yet others have a blended approach in which they will bolster internal resources with external providers to fuel their data-driven decision making process.

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Acustrategy Analytics has been helping companies become data-driven by providing data integration, visualization, analytics, and data science services and solutions since 2008.  Our clients range from small and mid-sized businesses to Fortune 500 firms and cover several industries including agribusiness, consumer goods, education, energy, government, healthcare, information technology, intellectual property, media, private equity, retail, and software.

For more information visit us at  You may email us at or reach us via telephone at (281) 819-0051.