“Not everything that can be counted counts and not
everything that counts can be counted.” – Albert Einstein
Analytics is at every
forward-thinking business’s agenda and many organizations invest significantly
to deploy Big Data. However, very few businesses achieve high expectations
result. Indeed, analytics is not an onetime project, but a journey on continually
improving the organization’s analytics capability, but how?
Analytics is at every
forward-thinking business’s agenda and many organizations invest significantly
to deploy Big Data. However, very few businesses achieve high expectations
result. Indeed, analytics is not an onetime project, but a journey on continually
improving the organization’s analytics capability, but how?
It all starts with the data. Garbage in, garbage out. To improve your analytics ROI, spend the time upfront
organizing and unifying the data you collect across systems and services, so
you can build common analytics tools that allow your analysts and data
scientists to spend their time investigating data instead of wrestling with it
across formats (over and over again). The major improvement includes: - Pull head out of the tactical sandbox and start
thinking strategically.
- Conduct a comprehensive assessment; not just
data exploration, but thorough getting feedback from all team members: those
who contribute to or benefit from, the modeling effort.
-THEN,
after checking for political/environmental/mechanical /adoption conflicts,
see if the data even supports the objectives. Otherwise, you'll be like all the
other technically proficient 'data scientists' who play with the data, but
never deploy the model (they wrongly believe that analytics metrics = business
metrics).
One of the key metrics to the success of any Analytics
implementation is support from key organizational stakeholders/business owners. Business owners first need to understand the role of analytics in competitive positioning.....once this is in place, it becomes easy
for analytics units to deploy an end to end solutions that are bound to
maximize ROI.
1) A top-down approach should be used to implement analytics across the organization
2) Identify the needs of analytics across different functions and map out to understand how it would benefit them.
3) Now comes the part where you get your hands dirty. Build a very robust Master Data management system across systems and services.
2) Identify the needs of analytics across different functions and map out to understand how it would benefit them.
3) Now comes the part where you get your hands dirty. Build a very robust Master Data management system across systems and services.
Build a Center of Excellence Analytics to make continuous
improvement. In most business organizations there is a
lacuna in identifying business problems where analytics could be applied. A
center of excellence was a continuous and scientific approach toward people
skills development that will go a long way in enhancing the organization's analytical
maturity. Then
- Monitoring and challenging the analytical models and mapping with returns is important
- To enhance the perception of better ROI, Visualization of insights & Graphical data representation of analytical results to stakeholders are key.
- Monitoring and challenging the analytical models and mapping with returns is important
- To enhance the perception of better ROI, Visualization of insights & Graphical data representation of analytical results to stakeholders are key.
There is no shortcut to building any
differentiated business capability such as analytics, the journey is thorny,
organizations just have to experiment, learn, tolerant of failure, invent in
talent, be flexible on processes, focus on entire division and organizational scope, and measure right, to build the analytics capacity for the long term
prosperity.
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