Data Science + Creativity
Magian is a data research firm partnering with investors and deal professionals. Through methods of econometrics and analytics we are testing behavior and quantifying business areas such as branding, marketing, operations, and product category synergies. A new level of digital consumer data-capture, afforded by online information, and acquired by omnipresent sensors, is changing lives and the capabilities offered in tracking and predicting impact in a variety of areas such as purchases, searches, and even aspirations.
Whether the data generated is passive (via sensors) or active (via individual direct participation), and even the dark data (that’s unused data), it all offers a cache of material for research and predictive insights in the context of two businesses coming together. And that’s our core focus: measuring compatibility and synergies that can come of the strategic merger of two businesses.
Companies that capture copious data- “intelligent companies”- have at their disposal a wealth of information that shed light on vital elements of business (e.g. stakeholders, operations, target market, and mass market, just to name a few). And leveraging that data through research and channels of descriptive, predictive and prescriptive analytics methods can unlock hidden value and set a trajectory that most likely will impact the target’s investment price. During negotiations, being armed with more data driven, objective intelligence can facilitate a smoother path toward deal agreement.
We are going beyond traditional finance, and the limitations of EBITDA and valuation. With data science, we are testing and measuring elements such as: buyer value, market disruption, synergies and sustainability, to name a few. Moreover, we are measuring intangibles such as intellectual properties and brand recognition, which are receiving more and greater importance in deals. Especially in early stages of such companies, EBITDA might not provide a sound basis for valuing the company.
Some of the key value points for data analytics in investment research and analysis include:
Provides competitive advantage in sourcing, evaluating and prospecting for integration and management
Gives better handle on revenue components of a target, and forecasting
Helps organizations predict customer response and behavior
May reveal other marketable opportunities within the target
Identifies what is chiefly material to deal success: focusing on what is important and not casting too wide a net
Allocates risk between parties
Offers scenario testing by employing a dynamic uncertainty-modeling approach
With the leadership of professionals with domain and data expertise, we are combining creativity with data science to test…what comes next.