Article written by Jun Lee, Senior Consultant at Analytica Consulting
In 2017, data analytics has taken huge strides in innovation. Cloud analytics, in-memory data computing, big data storage, enhanced data encryption – these are all the available tools, should you decide to get involved. However, even with all these tools, many companies continue to spend exorbitant amounts to maintain their traditional methods of collecting and analyzing their data. What is the issue?
Priority. Analytics is pervasive across every operation in a business. No longer should analytics be solely handled by the business or data analysis teams. Instead, analytics should take a more active role in each division within a company. Each team (whether customer services, engineering teams, business & finance) can contribute to the efficiency of the team performance, can link and derive errors, and predict modular solutions by using analytics. Analytics is a priority at each level of the company, and should be integrated into both distributed and local work.
Innovation. Having the latest tech and infrastructure is only a tool to reach your end goal: analyses that drive a business successfully. Adopting the proper analytics infrastructure is more than setting up the right technology, it’s creating a learning culture that evolves data sets and analytics applications. People who are data driven and embrace the many solutions Business Intelligence (BI) technology offers, are a necessity for any company looking to create an effective analytics environment. The company needs the mindset to create a cohesive ecosystem, with exchanges of data and structured ideas that build a package of knowledge. Only with this mindset can we fully capture and realize the impact of analytics.
How do we get there?
The road to efficient analytics varies case by case. Here are a couple of ways to launch innovative analytics:
- Receive feedback from your teams and decide how to centralize the management of your data.
- Create granular levels of operation for analytics (Trainings, consistent meetings and presentation sessions, organized request and task structures, scoping of high level analytics projects).
- Present a model example of a data visualization and explain how the data leads to new business insights. Preferably, each team should receive a model data visualization to see how they can utilize analytics. Focusing on an outcome can inspire others to try innovative methods and open minds to create insightful analytics.
- Recognize the tools and experience your company needs. Often times, innovative analytics and ideas are spurred by the lack of proper tools for data insights. Analytics projects are decided based on the traditional methods and applications available to them. However, many available BI tools excite innovation, improve efficiency of the extraction, transformation, and loading (ETL) process, create appealing data visualizations, and reduce the time to make core and detailed analyses. Provide your company with a robust BI tool and trainings to break past limits.
Let’s talk about the financial details:
|Initial Upfront Costs||Recurring Costs|
|Server set up||Security and data governance|
|BI tools purchase (Tableau, Qlik, Splunk, etc.)||BI tools subscription|
|Training sessions and development strategy||Analytics development|
The risks of staying behind your competition, losing potential insights on your data, and lacking efficiency in data analysis far outweigh the costs to correctly set up an effective analytics environment. If you’d like to take your analytics to the next level, please consider Analytica Consulting. Feel free to contact us at: 858-272-8260 or email@example.com.