Data scientists, fast computers, and advanced softwares are replacing traditional decisional making processes and disrupting tried-and-trusted traditional consulting methodologies, with Big Data being one of the main forces of disruption. Disruption, or fundamental changes to an industry, has affected many traditional businesses over the past years.
Over the years we have witnessed a complete change in the business models in industries like retail, travel, media, telecom, to name a few, by the arrival of internet based services. Internet giants such as Google, Amazon, and eBay have built their success largely by using Big Data as the core of their businesses. Disruption in consumer markets is getting most of the attention, but B2B sector is now heading for the change. In addition to market forces, digital challenges such as connectivity, digitalization, technology and huge volumes of data are affecting trade, transportation, manufacturing and other industries.
Consulting, though thought to be immune to disruption (typically because consultants promote change in the respective industries), needs to be ready for data explosion. Big data has now reached every sector in the global economy. Like other essential factors of production such as hard assets and human capital, it has become necessity for the consulting industry to develop frameworks for critical business problems through and around big data.
Imagine if you could analyze every transaction, capture insights from every customer interaction, and gather information from public databases, websites, web communities and your smart assets. All of these create data inundation, commonly referred to as big data. Big data has transformational potential to create value and have implications on how organizations will have to be designed, organized and managed.
The answer to some of the key questions for which organizations reach out to consulting firms can be answered by the several ways in which big data analysis can create value.
Data driven decision making
Sophisticated data analytics coupled with advanced data visualization can substantially improve decision making, minimize risks, and unravel valuable insights that otherwise remain inconspicuous. Such data analytics have applications for organizations from tax agencies that can use automated risk engines to flag candidates for further examination to retailers that can use algorithms to optimize decision making processes such as the automatic fine-tuning of inventories and pricing in response to real-time in-store and online sales.
Finding customer needs, exposing vulnerability and improving performance
Useful insights to boost productivity and expose system infirmities are being generated with information about customers, employees, business processes etc. being collected from structured and unstructured data sources on a real time basis. Associative algorithms and real time marketing have been adopted by ecommerce companies to cross sell products and boost revenue. With the plethora of social media data being generated, real time analysis of sentiments (positive/negative mentions) and behavioral predictions make the product and service evaluation process more efficient compared to traditional methodologies like focus groups and phone interviews.
Making data accessible to relevant stakeholders in a timely manner will create tremendous value. For example in manufacturing, integrating data from R&D, engineering and manufacturing units to enable concurrent engineering can significantly cut time to market and improve quality.
Customer segmentation for customized actions
Big data allows organizations to narrowly segment customers for better targeting and selling customized products or services. This method is widely used in marketing and risk management and can be revolutionary elsewhere.
Creating new business models, products and services
Big data can be used to improve the development of the next generation of products and services. For instance, manufacturers are using data obtained from sensors embedded in products to create innovative after-sales service offerings such as proactive maintenance (preventive measures that take place before a failure occurs or is even noticed).
The value that can be created from the current data revolution is enormous. Industries like retail, telecom, finance, insurance, media, healthcare, manufacturing, ecommerce and few others have already used big data analytics to improve productivity and growth potential. In the years to come, data analytics will become a key basis for competitive edge and growth for firms. Consulting firms thus need to reinvent their strategies and build framework revolving around big data and agile analytical solutions.
The arrival of data scientists and Big data analytics doesn’t eliminate the need for the traditional business consultants. As consultant one needs to ask the right questions to arrive at the right answers. Deep knowledge of business processes, markets, and customer behavior is required to ask the right questions and pose the right hypotheses, which can then be tested and validated through analytical abilities. With the current accelerated pace of technology and business change, adopting a data driven business model will drive consultancy firms and shield them from the disruptive forces.
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