Pauline E. Ranger Most people have heard about Big Data, the latest buzzword in business circles. Gregory Thompson, Finance Expert and Author, takes us on a journey into the world of Small Data.
He explains the market dynamics and players, as well as how to implement analytics into a small business’s arsenal.
The following is a brief introduction to the topic.
Data analytics are fast becoming the buzzword in the business world. You’d be hard-pressed to find a business journal that didn’t mention companies that “intelligently use data” to gain insights into their customers, perform risk analyses, or manage infrastructure more efficiently. Data-driven decision-making has been a part of large, data-rich companies for many years.
But despite its niche origins, data usage has become mainstream. Today, there are a few valid reasons for any company not to use analytics as part of its core business processes or capabilities, irrespective of its size or workforce. The traditional objections of cost, expertise, and resources are no longer valid. Internally generated data is becoming an asset that businesses can leverage in the same way as any other.
This article will briefly introduce its readers to the worlds of Data and Analytics. It will walk you through the unique market dynamics, players, and solutions for both before dedicating the second half to a practical implementation guide and framework.
The Layman’s Guide To Big Data and Small Data
The internet, eCommerce, social media, and interconnectedness of devices have all led to an explosion of data that those with the right tools can analyze. Each tweet, post, or like, as well as every left swipe, right slide, double tap, text, or transaction, is a data point that can be used to map out our digital footprints, which tell us who we are and how we make decisions. These data, which are aptly called “big data” because of their vastness, complexity, and depth, have opened up a world of possibilities for prescriptive and predictive analytics. This has enabled hyper-personalization to be possible in so many products that we use every day.
Big data is a term used to describe large data sets that can be computationally analyzed to reveal patterns and trends. These are often related to human behavior and interaction. To be considered “big,” the data set or bank must be large enough to require complex data systems and advanced methods to extract any value.
In a 2001 report, the META Group, now Gartner, framed big data into three dimensions called the Three VS. These are as follows: Volume (quantity), Velocity (speed of generation/transmission), and Variety (range of type and source). IBM expanded these three V’s into The Four Vs to include Integrity as the final dimension to capture value.
You’ve probably heard about big data. Small Data is a subclass deemed modestly enough to be accessible, informative, and actionable for people without the need for overly complex analytic tools. Best reduced by ex-McKinsey consultant Allen Bonde, “Big data is about machines, while small data is about people”–specifically, meaningful insights organized and packaged for the derivation of causations, patterns, and the reasons “why” about people.
SaaS Analytics
With the growth in the availability of data and its usefulness, a separate Integrity industry emerged. Once the exclusive haunt of Masters and PhD level statisticians, data scientists, and analysts, analytics has evolved into an industry of functionally robust but low-cost, self-service software-as-a-service (SaaS) platforms that enable even the most novice of users to extract value from their data. The smaller companies who previously did not have the budget or expertise to perform this type of analysis can now compete on an equal basis with their larger counterparts.
Research from the Aberdeen Group, an IT and services research firm, shows that SaaS users have twice as many employees that instinctively use data for decision-making and reach their ROI targets 40 percent faster than non-users. Most companies already use Google Analytics and third-party web analytics tools, as well as internal reports generated by accounting, marketing, and ERP systems, to monetize their small data.
IDC estimates that the global business intelligence and analytics tools market will be worth almost 14 billion in 2017. It has grown at a rate of 11,7% year-over-year. Forrester Research, an international market research firm, predicts a growth of 15% by 2021.
Market Share Data
It’s not surprising that old-guard software companies, such as SAP, dominate the market for analytics solutions and tools. IBM, Oracle, and Microsoft. In 2015, SAP dominated the market, with a 10% share and $1.2 billion in revenues in analytics and BI products. SAS Institute came in second with 9%, IBM third with 8%, and Oracle and Microsoft fourth and fifth with 7% and 5 %. The market share of five of the largest vendors is declining, largely due to the growth of startups like Sentiment Strategy and Tableau.
The Data Analytics Implementation Guide for Small Companies
A data-centric culture gives management the greatest confidence in its ability to make the right decisions often and consistently while using the same version of the truth – a transparent, quantifiable reality. Most of us have been in sessions where conflicting executives used different fact patterns, anecdotal evidence, and interpretations to support or refute their arguments. This quickly brought into question the integrity and accuracy of the inputs. The first decision a small business must make is whether it truly wants to be a data-driven company.
After this decision is made from the top down, a framework needs to be created in order to maximize the potential and utility of the new priority. A few questions are required to begin. First, what are the objectives, both short-term and long-term, of a given company, project, initiative, or department? Who should be accountable for the outcome and effort? Third, which specific problems are the company, project, industry, or department trying to integrate data? Fourth, what tools will be used to support the industry?
After answering these questions, the next step would be to create an execution strategy. With a little planning, an organizational structure, top-down direction, and bottom-up enthusiasm, this will enable the organization to produce real and measurable outcomes more consistently. The diagram is intended to be a framework for considering the different elements of a simple analytics approach.
