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Big Data, Small Data, & Trickle Down Metrics© for Small to Mid-size Businesses

Posted by Jeff Bruno, CEO on Jun 24, 2020 4:56:18 PM


Big Data vs. Small Data and trickle down metrics©

The term Big Data has been coined by many economists as having transformative powers for many large corporations. Amazon, Facebook and Google have been able to transform and even merge industries by compiling, analyzing, and utilizing big data. The outcomes can be seen in the form of intermarket acquisitions, hyper-targeted advertising, and integrated product launches.

Jeff Bruno, Trilogy Alliance Partner and CEO of Your Outsourced CFO, agrees that all small and mid-size businesses today are extremely sensitive to the big and small data we monitor and how the correct metric analysis is critical. Today’s companies MUST use big data and small data to analyze trends to stay competitive and manage growth effectively.

Big Data vs. Small Data for Business Intelligence

The analysis of big datasets can be an incredible tool for large companies with multi-billion-dollar market capitalizations, but what about those small-to-medium-sized-businesses (SMBs)? How can this market size benefit from the same data focused trends? 

Big Data steals the spotlight these days, but SMB owners can still ride the data wave by utilizing Small Data, identifying what Trickle Down Metrics© drive their business, and using them both to help achieve short and long term goals.


The Difference Between Small Data and Big Data

Big Data is defined by the volume, variety, and velocity of the data being collected.

  • Volume is quantities larger than 1 Terabyte (TB) of data.
  • Variety is indicative of the types of data being collected and the methods of collection, before piecing the raw data back together in different combinations and permutations to allow for analysis.
  • Velocity is characterized as being real-time data that often requires real-time response and heavy management.

The ultimate goal of Big Data is to create complex, algorithmic, and intelligently predictive insights and is most often personified by Artificial Intelligence (AI).

Small Data is defined as well along the same lines.

  • Volume = quantities less than 1 Terabyte (TB) of data, Variety is significantly less and Velocity is still near-real time, but the need for immediate response and management is much less critical.

The ultimate goal of small data is to create an ongoing analysis that provides business intelligence to drive operations towards the end goal of the CEO or owner or their “Why”.

The outcomes of Big Data and Small Data are to provide impactful insights, however at very different scales (corporations vs. SMBs). The key for an SMB owner is to be able to clearly identify what Trickle Down Metrics© are the most critical drivers for their business and to focus their limited resources on monitoring the right metrics for the right outcomes.

How Small to Mid-size Businesses can use small data and Trickle Down Metrics©

The Trickle Down Metrics© of a company are the metrics that permeate throughout all aspects of an SMB and which drive the company towards the ultimate goals of the CEO and/or organization.

The CEO or Organizational goals can vary wildly while discovering their Trickle Down Metrics©:

  • A Veteran non-profit might have an overriding goal to service as many homeless veterans as possible in a specific region.  This could drive hiring, expense management, program alignment and planning for donation drives.
  • A Tech-Services company might have a product that brings cost advantages to the consumer resulting in eroding market share from the larger competitors.  This might involve a market penetration metric at all costs to hit scale and profitability.

Bottom line, this will always be an iterative process to determine and manage:


How to determine your company’s Trickle Down Metrics:

1) Target the Trickle Down Metrics© derived from the WHY

2) Identify Supporting Down Stream Metrics,

3) Collect Data,

4) Monitor Outcomes,

5) Take Action,

6) Repeat,

7) Grow

Information = Power that Drives Growth (See below)

For Example:

Consider ABC Company, an application development company that creates custom software and applications for SMBs at a fixed fee rate. The CEO has built the company up to $2MM in revenue and $200K in annual net income within a few short years with grit, direct sales, and gut calls. The CEO would like to expand his team and diversify product offering within two years by increasing revenue, maintaining or increasing profitability, and reinvesting those profits into the new revenue channels.

ABC Company Trickle Down Metrics©

  • Utilization Rate of Direct Labor – the percentage of a person’s total hours are being used to generate revenue and how much money is lost via unutilized hours
  • Gross Profitability by Project – the much gross profit of each project available to satisfy overhead expenses (total billed per project less all direct costs)
  • Booked Sales – total value of contracts closed won in a given period, more pertinent to long term business health and long-term cash flows
  • Billed Sales – total of value of contracts billed within a given period, more pertinent to short term cash flow

Operating WITHOUT identifying the Trickle Down Metrics©:

The CEO expanded his or her direct labor force in anticipation of revenue growth, hires a VP of Sales and a Sales Administrator to increase revenue of main product and test market for new offerings, and installs a new project management software in preparation for hiring a project manager.

The CEO grows revenue to $2.8MM within twelve months, but sees profitability decrease to break-even levels. The CEO was correct in assuming he needed more direct labor ahead of the increase in sales and successfully avoided the issue of a contract backlog, but twelve months later, even with revenue up to $2.8MM he has no profits to reinvest into new revenue channels. Even worse, he does not know why his actions resulted in some wins and some losses.

Operating WITH identifying the Trickle Down Metrics©:

The CEO analyzed billable versus non-billable labor hours exported from the billing software and found that his Utilization Rate of Direct Labor was around 90%, higher than industry average and an indicator that they would soon be overwhelmed. The CEO used this knowledge to confirm his decision of hiring new direct employees.

The CEO then hires a VP of Sales and a Sales Administrator hoping to increase Billed Revenue and keep his new direct employees busy! The two new hires spend six months closing an acceptable number and revenue level of deals, however they were incorrectly projecting how many hours of labor the projects would require and thus had been miscalculating the fixed fee contract.

This pricing error began to eat into gross profitability of individual projects and the smaller projects weren’t even profitable at all! However, by monitoring the issue over time, the CEO was able to isolate the issue, why it was occurring, and take action to correct it before it worsened. The CEO decided to hire a project manager sooner than originally planned to handle the estimation duties and keep labor costs down.

Billed Sales had increased overall to $2.8MM, but they lost slight profitability in the short term due the estimation issues. Outside this slight bump, they are now on track to continue growing towards the CEO’s goal of maintaining profitability and reinvesting excess cash into new revenue channels.

As this example illustrates, it is essential for businesses of all sizes to monitor the data that is relevant to their end goals. This CEO was able to isolate the pricing error (a seemingly small issue) that was having an outsize effect on his business; with Trickle Down Metrics©, your company can do the same. There is no need for small businesses to be left out of the Big Data wave. With the right guidance, you too can benefit from data analysis—and translate those small-but-critical insights into action. 

Ready to get started, or have questions? The team at Your Outsourced CEO (YOCFO) can help. Get in touch.

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