The big fours Google, Facebook, Amazon, Apple have infiltrated our lives so much so that its almost impossible to avoid them. Today, they rank among the world’s largest companies, likely too big to be easily challenged. By fully harnessing the power of data, they have turned it into a competitive advantage. They have demonstrated to the world that data is the new oil, fueling their innovation and growth. This is also quite true for many cloud born digitally native companies. However, most small businesses face significant analytics barriers that prevent them from leveraging data to the same extent.

Traditional companies struggle to prioritize data-driven decision-making and revenue generation. According to Gartner, over 95% of business leaders will still rely on intuition for decisions, underestimating risk, even by 2020. One of the main issues they face are analytics barriers that hinder effective decision making.

Analytics have been one of the key corporate agenda for the last 10 years, still most companies are still struggling to raise the bar beyond traditional BI or self service BI.

Making analytics really work in an organization has more do with the behavioral aspect of decision making than deploying tools and setting up of warehouses/data lake etc. As companies gear themselves to cross the chasm between traditional BI and true analytics, they will be faced with the following barriers :-

• Leadership Awareness and sponsorship : With all the hype created around analytics, people are mostly aware about the power of data. However they find it extremely difficult to apply the same in their own context and to envision what it takes to make it work. It takes time and patience to reap the true benefit and one needs to be continuously at it. Unless it comes from the top, driving cultural change required is difficult. Its important to evangelize the possibilities in the organization’s context and push to make analytics the agenda of the top management. Overcoming leadership-related analytics barriers is crucial for cultural change.
• Aligning analytics goal with organizational goals : Analytics can do wonders, but unless its aligned to the key organizational goals, it will be just one of the things that keeps the employees busy. It always helps to publish an analytics vision statement that is aligned to the organizational vision. As an analytics leader, its important to link each initiative to the strategic objective that the business function which in turn links to the organizational goal. It is also important to assess the maturity of the function and plan accordingly, reducing analytics barriers along the way.
• Skill Gap : An organization needs to have a core team that drives this agenda. One can always augment the core team with external consultants, but the outsourced team cannot replace the internal team. In order to build the analytics team, look internally first. Invest in skill building. A formal structure is must to make analytics work. This structure can be virtual or a real. Following are some of the models (or a mix of them) that one can adopt. Addressing skill-related analytics barriers is essential to driving success.

• Lack of proper technology ecosystem : This one is relatively easier to solve. Aligning IT (systems dept) is important. It may need an upfront investment, however if the first two points are through, this will fall in place.
• Lack of Strong data management practice : Most analytics projects fails because of the poor data quality and the data silos that exists within the organization. Its important to bring analytics communities together. Overcoming these challenges is not about technology — it’s a human problem. Silos do exists and will require some change management to make data accessible and collaboration seamless. These data management issues are often significant analytics barriers.

A typical analytics project cycle will look somewhat like the following flow chart.

An analytics project requires the Insights team, Systems department, and LOB team. Success depends on clear roles and aligning outcomes with strategic goals to overcome barriers.

Companies that fail to invest in analytics will find themselves at a competitive disadvantage against those that do.

Clearly, it takes a lot to make analytics pervasive and probably that is why traditional companies are finding it difficult to move beyond just POCs. This is a journey that most companies have already started and it will be interesting to see how it unravels.

Happy Analytics !!