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Lekhnath

HIKE

To think big is to think from small

All IT companies could grow as a technological giant like Google.  But with growing size of information many new companies are introduced while the old successful businesses  are gearing down. There is something that they lack which stops them from growing up or sustain the growing information needs. One of the major lacking part is the lack of data model study. Mostly their design decisions are driven by the choice of framework or underlying platform rather than designing and studying on their own data and structure of the data.

Core asset of large or moderate IT companies are their data and the most important factor is how to use and structure that data. Most of the companies lack technical expertise or research in designing their own data model. Also, the strategic decisions are rarely entitled for modeling data structure rather are focused on UI experience of their clients. So, they lack a clear picture of their ever expanding data. When their growing information need demands some structural change,  often they end up choosing the wrong side and end up to a struggling business.

Mostly companies are afraid of experimenting with new model or some how lack the expertise. In the end they adopt commercial model that claims its applicability in similar businesses which has different data needs. So they end up in using the commercial applications that can never fit all the way for their needs at least when it comes to growing changes in their own business. The result is, a concept being noble at inception ends up as hot fix when it comes to implementation and they are not themselves aware what next if the business evolves somehow unpredictably.

They adopt open source product only if fully compatible with their needs and full enterprise support is available. This does not happen in most cases or even if it happens, the vendors do not claim this strongly. Or, in some cases a lot of customization is needed which they do not prefer to go through or bear the risk by themselves. So, mostly they drop open source adoption when it comes for very core business needs like data modeling, web server selection and so on.

What is needed thus is through analysis of the core business parts at least to identify the best model among the available ones if could not do research for new one. Only then select the candidate solutions from commercial or open source. And finally, they have to up lift themselves to think about doing some sort of analysis and customization while adopting the open source solution and do some domain or data model research. So, thinking to be big is to think from the very small parts of the business like presenting the data this way or that way, representing this particular information this way or that way, deriving key structures of the small data components, and so on.