There are multiple reasons why your analytics strategy might not be working. Here is the overview of why is it so and how you can overcome them.
(1) Delivering Analytics is NOT about the Data or Analysis
Often, the data managers and analysts get caught up in data systems, analysis tools and reporting rather than concentrating on bringing faster, better, and more insight into business decision making. Business partners cannot consume big data and they certainly do not have time to handle the complex analysis. They need simple answers to their everyday business challenges. Analytics is best delivered in small, clear, relevant bites, just like the Smart Phone Apps that we use every day.
(2) Building Analytics is NOT a Big Bang event
Why does every Analytics team want to begin with a full organization and a multi-million dollar contract with a supplier to deliver analytics to the whole organization? Building Analytics should be a series of small successes that each garners its own scale through the demand from your analytics teams business clients. If there is a lack of demand for an initiative, it should die. Ongoing budgets should be contributed to internal business partners benefitting from and demanding the Analytic services. Why don't we run our internal services more like client-provider relationships, starting with Analytics?
(3) If you build it does NOT mean that they will come
Many Analytics teams make the same mistake just because an idea seems like a good one, it does not mean that internal business team members will flock to use it. Try making great products and then engage internal stakeholders just like you do the consumers of your products. This means internal marketing, stakeholder support, and most importantly, products that make your business users excited to use them. Did anyone have to put you through a change management program to get you to use your Smart Phone?
(4) Data Scientists do NOT equal Analytics
Many folks believe that hiring a couple of Data Scientists means that they are creating an Analytics organization. There are multiple skills that are required for success across IT, data science, statistical modeling, analytic consulting design and delivery to your business stakeholders.
(5) You can NOT create it all internally
The world of data and analytics is innovating at a blistering rate. How can you be great at what you have done for dozens of years and then expect to suddenly invent analytics internally by hiring a couple of data scientists and buying some new technology? How can you possibly keep up with the innovations created by hundreds or thousands of startups that are competing every day to do more with your data? Go out and partner with the best and constantly challenge all parties to be the best or replace them. Network economies are the future those who systematically do the most with the best and most partners will be the dominant competitors in their industries over the coming years.