The power of Big Data lies in uncovering actionable and profitable insights by combining company‑internal data with public social media and purchased databases and applying sophisticated analytical machine learning technology.
Businesses are generating vast amounts of proprietary data from their online transaction, CRM, Salesforce management, lead gen, billing and other systems. Typically, they also purchase data about non-customers from vendors such as D&B, Equifax, and InfoUSA, which is often outdated and increasingly inferior to freely minable internet data. Vast amounts of unstructured, self-reported, real-time data can now be scraped from Social Media sources such as Linked-in, Facebook, Twitter, etc.
Facing this data avalanche, many companies try to do too much and are overwhelmed with data quality and analytical approach challenges, dooming potentially high ROI projects. We believe that there is a tremendous opportunity for business to deepen customer relationships, improve sales success, reduce churn, optimize pricing, etc. Even very small improvements in these ratios along the “sales funnel” have a tremendous impact on operating performance.
Successful business analytics requires an unusual combination of skills and experience that is hard to assemble for most organizations:
We are not data miners. We are highly skilled, experienced executives, data scientists and consultants who have a unique ability to drive fast-paced, highly hypothesis and data-driven projects with quick and measurable financial results.
1. Organize internal data for analysis. While this is hard to do retroactively, most large companies generate enough data in a month or two, that if this data is organized and captured properly, powerful models can be built upon that data.
2. Combine all data sources. The real power of Big Data and Business Analytics lies in combining the three main sources of data: Internal Proprietary, Purchased Public and Social Media / Internet. Each has it’s own strengths and weaknesses and they can never be perfectly matched, but powerful insight can be derived from their interactions.
3. Build Machine Learning Model with clear ROI. Any Business Analytics effort should have a clear and realistic ROI objective that is within the company’s ability to execute. There are usually more opportunities than a company’s ability to execute them. We advise our clients to not pick the “sexiest”, but rather the most executable machine learning projects.
We typically partner with clients to deliver earnings improvements of 20-30% over a nine months time frame. Our track record is unmatched in the consulting industry: 20 years and over 2,000 projects around the globe that have delivered documented performance improvements of well over 20%.
Our strategy combines our broad global perspective and economic insight with executive experience ranging from operations optimization to corporate and business unit strategy. Our recommendations are practical and grounded in actual operating experience of many of our consultants.
Some clients require ongoing, “light-touch” analytical support to make important initiatives work. Because we partner with our client to achieve lasting success, we often supplement client resources for analytically intensive tasks in a low-cost onshore / offshore model.