the social metrics

The 3 Point Focus For All Your Business Data

Happy New Year! With all the talk about the promise of Big Data in 2013, and the occasional ”Big Data is silly” post, I wanted to mention 3 pillars that I think are important as the foundation for strong business intelligence. 

The value of data is in its use and application to business problems. There’s not really much point in collecting databases the size of an Amazon warehouse if you don’t do anything with it. 

Or, there’s going to be problems if you’re great at analysing data but the actual data collection phase is full of errors and mistakes. 

So I’d recommend always thinking about the following 3 attributes as you set up a measurement project. They probably seem obvious but hopefully they offer a friendly reminder as we head into the new year and new data analysis projects. 

Like a good story with a beginning, middle and end - data analysis has 3 important pillars for finding insight:

1. The Data Collection

Rubbish in, rubbish out. If your data collection is full of problems, like sales manually entering lead campaigns in SalesForce without any consistency or key, then your analysis is going to steer you in the wrong direction.

There’s a reason there are journals about statistics, research sampling, methodologies and other data collection tidbits. That reason is that your data collection needs to be pristine in order to give you accurate, useable insights. Without good data collection, you cannot be confident in the data analysis. 

Spend a lot of time here and the rest of the project, not to mention your business, will thank you beyond your wildest dreams.

2. The Data Analysis

Every now and then, a new formula or abstract ratio gets thrown out there. Occasionally people over-simplify some data and over-complicate other data bits. I’ve seen it all. A lot. 

So my second pillar is about the data analysis. 

Do you really need a statistical significance test and are you performing the right sig. test? Do you understand what type of regression to use? Does your analysis match your goals or just overcomplicate things?

Sometimes, simply looking at a few percentages can do the trick and get the information you need. Sometimes you need something more robust. 

The trick here is to match your data collection and analysis to your goals. If you just want to know what people like more, you could ask them and look at the percentages. If you want to predict future shopping behaviours based on databases, you might need predictive modelling and formulas. 

Chat with colleagues and be sure you’re using the right tools. Map out your goals and match them to potential metrics. Learn about how others track the same issue.

Performing the right analysis is crucial to giving you the insights you need to meet your goals and improve. 

3. Distributing the Insights

In my doctorate research, I’m finding a lot of research is lost to the sands of time because the authors don’t spend the time telling others about the research or don’t communicate in a way that helps others put the data into action. 

One respondent in my research said “I don’t even read a report if it doesn’t summarize the information for me at the beginning because I don’t have time. But if I read the summary then often I’ll read more in the report because I want to know the details.”

Another finding is that different roles and different job levels expect a different type of summary or report. I’ve talked to managers who want to access data dashboards, or the CEO who wants five summary points and nothing more. 

So there needs to be effort put into distributing the insights and telling the data story in the right way to the different audiences. This helps people digest the information, understand the data and take action on the insights. It also means that people can build on the insights, add information and the business can enable cross functional learning. Anything less will mean that your data or insights aren’t being used to their full potential.

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I see these 3 important components applying to all of your business data, even the smaller projects, because all data offers the chance for the business to adapt and find new insights. 

The promise of Big Data can only really be fulfilled if all of these 3 areas are done the right way. If the data collection isn’t error-free or the analysis is incorrect or no one can understand how to use the insights then the data won’t live up to its potential. 

As always, good luck and happy analysis-ing. 

"Executives expect 6 to 8 pieces of supporting evidence in order to act on a data insight."

— Research findings by the Market Research Executive Board

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Who will own data insights? With big data becoming a huge asset and competitive advantage, I ‘mulled’ over the idea of a central insights group. My thought is that this would be a multi-disciplinary group of insights experts — driving organizational learning across all areas. Different versions of this could cater to a business of almost any size. (Taken with instagram)

Data Integration Is The Key To Growing A Business

Using big data, market research and information in a way that improves efficiency, increases profits and makes a business more competitive comes down to one important idea:

Integration. 

Data, collected from multiple sources like social media, market research and database mining for example, becomes hugely valuable when you can integrate it all together, examine trends and correlate the data points.  

Through integration in a central data hub, businesses get a more holistic view of their customers, their market and information to create knowledge. You can look at trends, get evidence and look for unique findings across the data sets - which has only been available to most businesses in recent years thanks to the real-time web. 

Big data isn’t about overwhelming blobs of data. It’s all about integration and businesses of all sizes can benefit. 

Big Data is More Than You Think

This is a great quote from IDC about Big Data and how it’s much more than you think. 

Big Data is not just about data collection, it’s not just about analytics, it’s not just about Hadoop. 

What is it all about then?

I personally think it’s about the promise of integration. Imagine all the data, relevant to your business, integrated and synthesized into one database. 

Imagine the power of all of that data, interacting and learning from itself. That will not only make business more efficient, it will also improve the commercial sectors ability to meet the supply-demand curve. 

Imagine, for example, what the power of big data could do to help people save money by looking at the supply of tea coming from India and matching that against the demand across US tea stores. 

No more paying for tea that was over-ordered and sitting in warehouse. Or the need to run extended advertising because there aren’t enough people buying that warehoused tea. 

There is so much potential here. Exciting times.