I had met up with yet another prospect last week who was not aware of difference between reporting and analytical solutions. I would blame reporting tool vendor for this who has started confusing customers by positioning reporting tools as analytical solution. There are several differences between reporting and analytical solutions.
1. Business Objective
Reporting: Reporting solutions will help you measure performance of various business entities relative to business plan or target. It will help you convert data into information
Analytics: Analytical solutions will help you identify new products, customer segments, reduce cost, risk & fraud. It will help you convert information into knowledge.
Example: Reporting solution will tell you number of stock outs by items by store whereas Analytical solution will tell you about optimum amount of quantity that you need to keep in your store to minimize stock outs and opportunity cost.
2. Information output
Reporting: Reporting solution output will help you quantify past performance.
Analytics: Analytical solution output will help you infer unknown facts and relationships. It will also help you quantify future probabilities.
Example: Reporting solution will tell you about best selling products in your portfolio whereas analytical solution will tell you about probability of buying a particular product when your customer visits your store next time.
3. Output
Example
Reporting: Top 10 products by revenue, Top 10 customers by region
Analytics: Cross Sell/Up Sell Model, Forecasting by Product by Region by Time
4. Queries
Reporting: Known, simple queries which can be easily optimized.
Analytics: Queries that become very complex as they evolve via iteration.
Reporting solution will help you answer the following questions
1. What happened? When did it happen?
2. How many? How often? Where?
3. Where exactly is the problem? How do I find the answers?
2. What if these trends continue? How much is needed? When will it be needed?
3. What will happen next? How will it affect my business?
4. How do we do things better? What is the best decision for a complex problem?
Davenport says organizations successfully competing on analytics exhibit a set of common attributes, including:
1. Business Objective
Reporting: Reporting solutions will help you measure performance of various business entities relative to business plan or target. It will help you convert data into information
Analytics: Analytical solutions will help you identify new products, customer segments, reduce cost, risk & fraud. It will help you convert information into knowledge.
Example: Reporting solution will tell you number of stock outs by items by store whereas Analytical solution will tell you about optimum amount of quantity that you need to keep in your store to minimize stock outs and opportunity cost.
2. Information output
Reporting: Reporting solution output will help you quantify past performance.
Analytics: Analytical solution output will help you infer unknown facts and relationships. It will also help you quantify future probabilities.
Example: Reporting solution will tell you about best selling products in your portfolio whereas analytical solution will tell you about probability of buying a particular product when your customer visits your store next time.
3. Output
Reporting: Historical standard reports, dashboards, KPIs, cubes for OLAP.
Analytics: Predictive models, scores, forecasts.Example
Reporting: Top 10 products by revenue, Top 10 customers by region
Analytics: Cross Sell/Up Sell Model, Forecasting by Product by Region by Time
4. Queries
Reporting: Known, simple queries which can be easily optimized.
Analytics: Queries that become very complex as they evolve via iteration.
Reporting solution will help you answer the following questions
1. What happened? When did it happen?
2. How many? How often? Where?
3. Where exactly is the problem? How do I find the answers?
Analytical solution will help you answer the following questions
1. Why is it happening? What opportunities am I missing?2. What if these trends continue? How much is needed? When will it be needed?
3. What will happen next? How will it affect my business?
4. How do we do things better? What is the best decision for a complex problem?
Thomas Davenport has rightly said "Organizations that fail to invest in the proper analytic technologies will be unable to compete in a fact-based business environment."
Davenport says organizations successfully competing on analytics exhibit a set of common attributes, including:
- CEO commitment – To use analytics as a basis for competition requires commitment from the top of the organization. It requires an allocation of resources, long-term funding and, in some cases, a shift in culture.
- Strategic focus – Successful users of analytics don't just use analytics in general. They first define their distinctive capability and then use analytics to support that capability.
- Enterprise application – Firms that compete on analytics don't manage it locally. They eliminate fiefdoms of data, centralize the data and expertise, and manage analytics at the enterprise level.
Really good post. This will help me a lot in explaining the prospects.
ReplyDeleteThanks
Rajen
Nice Post. I would say report is about the present and analytics is for the future. :-)
ReplyDeleteYou make good points. But, I would add that you need the reports in order to produce good analytics. It's more the difference between just reporting what is happening versus figuring out why is has happened and how you can work to fix or better the results.
ReplyDeleteGood insight Sir.
ReplyDeleteI have found that business leaders often think of a report when they talk about analytics. However, the report will only identify facts, as Manish has indicated. When the facts look odd, the fire drill begins to determine the cause.
ReplyDeleteBefore building the report, it is helpful to conduct research to better understand how much variability there is in each key metric and what influencers there are for each metric. This step is analytics, and ultimately can lead to better understanding of the business.
When the report is built, it should include some indication as to whether the measurement is in a normal range or outside the normal range. It may also help to have some of those key influencers incorporated.
Doing this analysis in advance of report development increases the likelihood that the report will add value for the business leader in tracking their business.
Good post Manish. It's simple and very informative at the same time.
ReplyDeleteGreat post Manish. Most articles I've ready give a general explanation that doesn't map well to a use case, or is so ambiguous that you can use the definition interchangeably, causing further confusion. I like your use of examples, it really drives home the true definitions for reporting and analytics and provides context behind each one. now if more marketers used these two distinct yet required tools to make smarter marketing decisions, it would help their case to request resources and budget to run various marketing activities.
ReplyDeleteReporting and Analysis are very different in terms of their purpose, tasks, outputs, delivery, and value. Reporting translates raw data into information. Analysis transforms data and information into insights. business analytics course
ReplyDeleteThanks for the post! What sort of enterprise data model tools would you recommend to address some of the issues you brought up?
ReplyDelete-James
Helpful material
ReplyDeleteExcellent post. Just wanted to mention that if you're interested in learning more about business analytics, and specifically predictive analytics for insurance companies and the insurance industry in general, you should definitely take a look at Modern Analytics and their excellent predictive analytics solutions.
ReplyDeleteVery nice blog...
ReplyDeleteGreat information provided. I appreciate your work.
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Reporting and analytics are both crucial components of data analysis. How Unblock Invites Reporting involves the collection and presentation of data in a structured format.
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