Is Data Science of Value for Small/Medium Size Business?
The New Data Analytic Paradigm of Small Business
When small/medium sized business leaders hear terms like data analytics, business intelligence and data science, many break out in a cold sweat. It seems like these methods should apply to their business, but the terms are so vague, many don’t see a connection to their business context.
Data science is such a new field, there are a lot of ambiguities as to what these various terms objectively mean and what people actually mean when they use various data related terms. Lets start to move past the cross currents of confusion and find the still water.
Main Idea: Successful businesses transitioning to the new era of Industry 4.0 already regard data as the second most important strategic asset, following right behind people as a strategic asset.
Business Intelligence
While seemingly common sense, many business leaders do not value the analysis of historical data. Using intelligent methods, the analysis of historical data can create huge opportunity. When coupled with an understanding of system theory, the opportunities are endless:
Time series evaluation of operational performance and its root cause
Feedback opportunities to dynamically adjust to changes in the business environment
Establishing metrics of to monitor key business functions
Mature projects can produce dashboard for real-time monitoring of business functions.
The goals of business intelligence is to apply statistical and system analysis methods to historical data. Understanding clearly what happened is the beginning of data analytic thinking
On the one hand, the market place of small business requires unprecedented sophistication as compared to decades past. The old patterns will simply not provide the sustainability needed to survive, much less prosper. On the other hand, acquiring new skill sets can be daunting. At their own peril, many regard advanced analytical skills sets as the luxury of big business. What skills do I invest in, and how can I be sure there will be a return on the investment? What is the common sense thing to do?
Paradoxically, it is the obligation of every business leader to know as much about their organization as they can. Are the decisions being made taking into account all the best information from their business? Is the information knowledge tribal or data based? Are trends known in real time, or is there an adverse trend that may compromise the effectiveness of critical decisions. There’s a big difference between having exhaustive knowledge before making a decision and flying blind.
Predictive Analytics
Tell-Tale Signs of Opportunity
There are at least two litmus tests as to whether even a small, family owned, business is leaving opportunity on the table:
Volatile EBITDA performance
Q1, Is the Earning Performance of the business well behaved from month to month? Are there stochastic patterns of large fluctuations month to month or year on year?
Q2. Are variations in EBITDA known before they occur, or is there frequently scrambling to figure out what happened when previous monthly financial results are finally available?
Cash Flow Expectations
Q3. What are your cash flow forecasts 60 to 90 days out?
Q4. Beyond macro annual forecasting, do you have time series trending data of descriptive (historical) cash flows and predictive (future ) cash flows based on reasonable assumptions?
If you don’t have the answers to any of these questions, or if the answers are frequent pain points, there is opportunity for you to take advantage of financial data analytics
Internal Rate of Return of Financial Analytics
With all the investment options available, if some can make north of 10% per year on a consistent basis, they are considered to be wise investors. Small businesses typical see 100% to 500% first year returns from Initiating a project in Financial Analytics. The investment is small and potential gains are very attractive