Big data has encompassed many concepts and has become a buzz word over the years. Even though everyone seems to agree on its potential to create value, many companies still struggle to understand how to adapt it to their own business.
As more and more enterprises move towards a data-based decision making approach, it has become urgent to evaluate how organisations can leverage on this opportunity or take the risks of being outperformed.
Undeniably, businesses gain huge value of getting clear and real time insights from data. This is giving them a competitive advantage to get an idea of the impacts and ROI of the actions they have led but also to influence their future decision making.
Hence, this disparity between digital natives players and traditional companies , is creating winner-take-most dynamics.
« Data-driven companies are 23 times more likely to acquire customers, six times as likely to retain those customers, and 19 times as likely to be profitable as a result ». Forbes, based on McKinsey Global Institute report, 2016.
Understanding business analytics
In simple terms, business analytics offer the precious means of making sense of the exponential volume of data generated and collected within an enterprise to drive business planning. It is a key corporate asset as it includes all the domains of a business (finance, sales, marketing, operations… ).
While we previously supported our strategies on reporting (What happened?) using spreadsheets and dashboards associated with « gut feelings », we now have the possibility to gain more relevant insights.
Indeed, the function of business analytics has transitioned from providing information to providing insights, and now to providing solutions.
- predictive analytics answers the question why did it happen? assessing current and historical facts to make decisions based upon statistical techniques (machine learning, data mining…),
- prescriptive analytics answers the question what is likely to happen? and suggest decision options based on the corrolation of historical and . which involves the use of data science and algorithm.
Advanced Analytics by Gartner
Hence, making a constant and pro-active analysis allows businesses to continuously enhance their operational efficiency & performance, revolutionizing the way they business is made.
Yet, many organisations have still not reached this advanced phase. Today, only a small portion of the potential value that is being captured from data and analytics. Mostly, large tech companies such as but not limited to Google, Amazon, Apple or Microsoft can capitalise on their leadership, becoming the most valuable companies.
A company cultural change: adopting an agile approach
Firstly, in order to implement a data-driven approach, the importance of data analysis needs to be understood by all the stakeholders involved in decision making of an organisation. Therefore it requires to be adopted by all and accessible to all. Which means that this will lead to major managerial change. Especially if some of the leadership was based an an exclusive approach of “information ownership” .
.Initiating a full fledge digital transformation of the company is a must to better apprehend this change. Part of it, implementing the right data technology allowing business to get the required valuable insights to achieve business goals.
Illustration for big data
Aligning business strategies
Companies needs to decide which of the many options to consider and which of the numerous metrics to analyse that would make the most sense to their respective business to innovate and capture value.
This mean starting by setting up their own practical approach to start exploring and exploiting their data based on their strategies. Deciding on why they would need data for is a step forward to setting objectives.
Therefore business strategies need to be implemented and aligned with the business intelligence strategies. This also implies that the same would be continuously re-assessed to provide significant and tangible insights, allowing changes and improvements.
Trash in- Trash out
However, gathering huge amount of data or isolated in silos would not be effective to drive critical business decisions.
Best practice is also critical to obtain relevant results through quality data.
Due to the wide diversity of data, the quality and veracity of data is prime. This allows obtaining quality outputs as its value is tied to its ultimate use.
It is also important to use data-driven insights in the day-to-day business processes through workflow integration.
« Whilst 81% of organizations support the notion that data should be at the heart of everything they do, the vast majority continue to keep data in silos » Forbes, Ernest & Young report, 2016.
The process towards becoming a data-driven company is quite complex. It requires to be ready to rethinking the overall organisation of the company. That also implies potentially accepting to make drastic changes to their business models.
The main withhold to reach the deployment of a business analytics strategy is finding and attracting the right talents (eg. data scientists). It remains a major challenge. Yet with more and more programs opening up in universities, time will eventually play its part. In the meantime, companies need to keep experimenting and learning.
*Forbes.com « Becoming A Data Driven Organization » Oct 28th, 2016
***https://www.mckinsey.com/The-Age-of-Analytics-Executive-summary.ashx
**** https://www.gartner.com/newsroom/id/2881218