We live in an era of data driven business where data, actionable insights and intelligent decision
automation hold the key to the future of corporates in any domain.
Businesses that do not adapt to the data driven technology find it difficult to sustain
themselves in the market for a very long time. With the advent of analytical decision making,
there is also a plethora of basic and advanced BI and Analytics solutions in the market.
According to Gartner, the market for BI and Analytics platforms will remain one of the
fastest growing software markets in the industry. However when it comes to the
question of “which solution best serves the needs of a business?” corporates are often in a
dilemma regarding the right product for their requirements, the costing, the features of the product,
cross platform usage, building in-house or outsource and customization. Customization of the current
tools as per their business needs is often the key to addressing the pain points of the customers and
most of the BI/Analytics solutions out in the market fail to offer this.
Danger of not doing anything
Data driven insights can very much accelerate the business progress.
Most of the organizations that don’t adopt analytics shows one of these characteristic:
- Data Latency - The organizations don’t collect the relevant data required for data analysis.
- Analytics Latency - The organizations collect data but they don’t perform analytics. Often the analytics are restricted to basic reporting/dashboards.
- Action Latency - The organizations perform analytics but they don’t adopt analytical insights. Probably the business is not convinced of the ROI.
No matter, what characteristic they exhibit, they need to adopt data driven insights.
However there seems to be no compulsion to adopt sooner.
Why adopt analytics? Well, if you don’t, your competition will. Survival in the digital world calls
for effective means to get insights. Analytics can do a world of difference there!
Gauging Analytical Maturity
The organization has to mature to analytics in stages. Exactly five stages!
- The “Initial” stage organizations are qualified by adhoc practices.
The organizations have “champions” who does things in ‘their’ own way.
These organizations don’t have any processes established and standardized.
- The “Collected” stage organizations have data collection processes streamlined.
These organizations could be termed as “spreadsheet” organizations as business
would rely more on spreadsheets and other simpler tools to derive insights.
The depth of analysis, complexity would vary from individual to individual based
on their skill sets.
- The “Integrated” stage organizations are characterized by Business intelligence
reports/dashboards implementation across the organization and just not any particular departments.
The Key Performance Metrics (KPM) are well defined to qualify the effective performance of
the business. In simple sense, these organizations have an “integrated” view of their
- The “Elevated” stage organizations can further reap the benefits on
accomplishing the previous “Integrated” stage. These organizations can perform
statistical analysis, analytical models to qualify their business process better.
Often organizations don’t establish this capability at org level but rather at a
sub-org level (Business Units, Departments, etc).
In such cases, the departments only get qualified to become the “Elevated” stage
but not the entire organization. These organizations (or their qualified sub-units)
can perform real-time analysis as they have a very good understanding on their business performance.
- The “Mastered” stage organizations (or their qualified sub-units) are fairly
matured entities that would have implemented advanced analytics like machine
learning techniques, artificial intelligence, etc. These organizations have fully
functional team to design and develop complex models to discover data-driven insights.
The model development is an ongoing processes as the data models need to be very frequently
validated for their relevance. In simple terms, these organizations have setup their
“Analytical Centre of Excellence”.
Analytics Maturity Model - The geni way!
The Analytical Maturity Model assessment begins with the understanding of the
organization’s Business Analytics Maturity (BAM)! Understanding of the organization,
its domain, competition and market dynamics are very crucial for this phase.
Analytics Maturity Model focuses on four essential pillars that is built on the organization’s
Business Analytics Maturity. Click on each pillar to understand their significance
Fill all the details to derive actionable Insights
What good is an assessment without clear deliverables and a roadmap!
The assessment brings thorough understanding on:
- Organization Analysis: 4 pillars – Data, People, Process, Platform
- External Influencers: Competitors, Industry factors, Geographies
- Analytics Roadmap with various initiatives classified as:
- Do it yourself – Ready to adopt
- Low hanging fruits – Build it yourself or with a Partner
- Long term – Think COE