Six Analytical Models for Producing Different Business Insights
“SMBs that capture and analyze data realize a 29% increase in profits.”
“Only 12% of aggregate data—structured and unstructured—is used by businesses.”
“Tactical and strategic objectives are placed on top of the type of business outcome to produce six analytical models.”
Top-performing small and mid-sized businesses (SMBs) are capturing data and analyzing it through business intelligence (BI). The results are quite impressive. They see a 29 percent increase in profits, seven times the industry average. However, few SMBs have a big data strategy. The vast majority run their businesses on gut instinct.
Not Simply for the “Big Boys and Girls”
Too many SMBs mistakenly believe big data is only for “big” businesses. The reality is that businesses of all shapes and sizes capture data on their operations, finances, partners, and customers—from marketing campaigns, to website traffic, to in-product interactions, to financial performance. Yet, much of this data goes unused: only 12 percent of data is analyzed for actionable intelligence today.
Being small may actually put SMBs at an advantage over big businesses. More agile than their larger counterparts, SMBs do not have as many data sources and can quickly act upon insights in a timely manner. Fortunately, with technology disruption, which includes software-as-a-service (SaaS) solutions, big data analytics are accessible to SMBs. The most-often-cited objective SMBs have when it comes to data analytics is better-informed business decisions, followed by improved customer interactions and satisfaction.
Figuring Out Where to Start
Knowing where to start in capturing and analyzing your data is not easy. SMBs are not configured to boil the ocean when it comes to the vast universe of data. Data more than doubles every two years, and it is expected to grow to 40 zettabytes by 2020, a 50-fold increase since 2010.
SMBs that are successful in their big data endeavors pick data areas where business impact is most possible. It is important to cross-reference internal data repositories with external sources to develop accurate and meaningful insights. The following are some of the ways SMBs can analyze data to formulate actionable insights that result in tangible outcomes:
- Identify business trends—financial and operational—through data patterns
- Locate ways to manage capital and resources more effectively
- Pinpoint ways to source, develop, and manage talent (full time and contingent) better
- Improve customer service across all engagement channels
- Increase sales through campaign and content performance analytics
BI can be either strategic or tactical in nature. When placed on top of descriptive, predictive, or prescriptive outcomes, the result is six different areas of business insight:
- Tactical-Descriptive Analytics. These are real-time metrics and status (e.g., website visits, social media followers, funds depleted for a project, etc.).
- Strategic-Descriptive Analytics. These are also real-time metrics and status, but they span a time continuum, different aspects of the business, etc. (e.g., social media likes based on content, website visits during summer versus winter months, talent retention based on which job boards generated a hire, etc.).
- Tactical-Predictive Analytics. These leverage multiple data sources—sometimes internal and external—to predict future outcomes that can be used for decision making (e.g., an increase in live web chat engagements and a decrease in phone-based support calls, coupled with external market data showing a preference for live web chat over phone, can be used to predict a long-term change in customer engagement channel preferences).
- Strategic-Predictive Analytics. These utilize multiple key performance indictors (KPIs) to predict outcomes used for strategic decision making (e.g., employee retention and performance per job function spread across recruiting source for each individual and groups to predict what recruiting source—paid job board, free job board, staffing agency, employee referral, etc.—is the most effective channel per job function).
- Tactical-Prescriptive Analytics. These examine varied business outcomes to develop prescriptive recommendations and activities (e.g., compares outbound email campaigns and social media promotion for specific market segments and persona types to determine which channel will be most effective for a marketing campaign).
- Strategic-Prescriptive Analytics. Like tactical-prescriptive analytics, these also look at varied business outcomes. However, they are more strategic in their prescriptive recommendations (e.g., examination of customer support cost for specific market segments and personas in concert with sales margins for those same customers, time and cost to close, and average account growth over specified timeframe to identify new product and service development opportunities).
Digging into Your Data
If you are like most SMBs, getting started with big data analytics may require some outside assistance. Working in concert with your team, Reverbant can help identify all of your different data repositories, mark the ones that are most important, and pinpoint how best to capture and aggregate the data. We can then recommend areas where integration of data stores will amplify business insights.
For a more in-depth look at big data and business intelligence, check out our eBook “Digital Transformation Made for Small Businesses: Four Areas of Opportunity.” Or simply give us a call at +1-925-322-0268.