One of the most powerful resources today is big data. Blindly going after potential customers will not yield any results.
To gain that X factor, you need to know where you are going, the reason behind you going there, and the effort that you are willing to put into the journey.
A clear vision, strategic planning and approach, and use cases are required to move ahead with the big data discoveries. This is where advanced analytics comes in to give you a holistic view of your business.
In order for this to be accomplished, the procedure of processing data should be redefined as well as the benchmarks as to how that data will be used should be redefined.
Strategic analytics determines the driving forces behind your customer and the market’s behavior using a data-driven analysis of your whole system. The key to ideal strategic analytics implementation is doing it in the right order:
- Step 1 — Identify capability strengths and weaknesses with competitive advantage analytics.
- Step 2 — Obtain diagnostics at the business process, business unit, and enterprise levels using Enterprise Analytics
- Step 3 — Individual level diagnostics in order to get actionable insights using Human Capital Analytics
The data that is generated should be able to answer a few key questions like:
- The key decisions that provide maximum value to us – What are they?
- There is new data that hasn’t been mined yet – Where is it and what is it?
- There are new analytics techniques yet to be explored – What are they and can they be incorporated
Platform analytics helps you infuse analytics into your decision making with the aim of improving your core operations. This will allow your company to harness the power of data to uncover newer and better opportunities.
In this process, the important questions should include:
- The integration of analytics in everyday processes – How can it be done?
- Real-time analytics, predictive analytics, repeatable analytics – Which processes will benefit from this?
- Can big data analytics be of use to your back end systems?
Platform analytics shouldn’t just be a stack of technologies. Due to the many channels and formats it is available in, the pulse of your organization can be checked with this.
Key decisions across customer service, sales, supply chain, marketing and other business functions can be made more effectively with the incorporation of data analysis.
Enterprise Information Management (EIM)
Unmanaged repositories contain about 80% of all vital business information. Once your strategic and platform analytics are in place, setting up your EIM will help make use of data from social, analytics, media, and cloud to be used across the company.
An agile data management operation should be built with tools for creation of information, capturing it, distribution and consumption. This will help:
- The streamlining of business practices
- Collaboration of efforts to be enhanced
- The employee productivity to be boosted
Before implementing your EIM strategy, business requirements should be defined; issues and opportunities should be identified. The identification of processes and projects which will benefit greatly from EIM implementation should also be identified.
Business Model Transformation
New opportunities for customers, revenues, and services are created by companies who adopt big data analytics and transform their business model in parallel.
This allows for every aspect of your business to be reinvented: from sourcing raw materials and forecasting their demand to accounting to recruitment and training of staff.
For this to take place, the following are the pre-requisites:
- Capitalize on new opportunities with a big data strategy and vision that helps to do the same.
- Data experimentation and innovation in techniques should be encouraged.
- New skills and technologies should be leveraged in the right way. At the same time the impact they have on data should also be monitored as data safety and security is important.
Making Data-Centric Business
If you generate a large amount of data, you need to realize that it needs to be maintained in a data warehouse and analyzed for you to gain actionable insights.
Data isn’t just an asset; it’s a currency that is worth its weight in gold! Data is the source of any businesses core competency.
Data analytics is split into 3 categories:
- Insight: Understanding customers along with their networks and influence using mining, cleansing, clustering, and segmentation of data.
- Optimization: The analysis of processes, business functions, and models.
- Innovation: Growing your customer base using new disruptive business models.