Wednesday, December 28, 2011

Alberto’s Business Analytics Predictions for 2012

Alberto’s Business Analytics Predictions for 2012

2011 was a great year for business analytics across all industries. As business analytics projects proved their measurable value within companies, I believe that in 2012 we will continue to see a mathematical increase in the number of companies that use business analytics. My predictions for 2012 are not in order of importance.

1. Increased utilization of advanced analytics in retail, CPG, healthcare, energy, banking, and healthcare – These industries will continue to lead in incorporating advanced analytics in their day-to-day operations using real-time or near real-time systems. Education and understanding of how advanced analytics can help companies will increase within companies in strategic and tactical areas.

2. 3D visualization techniques used in gaming will become more prevalent in business analytics – Visual analytics will enhance dashboarding and reporting techniques currently used by companies due to its measurable lift in providing better business insights.

3. Decrease in the amount of time that it takes to successfully design, test and implement an advanced analytics project to no more than three months – As companies become more educated in the benefits of advanced analytics, tools, and resources, they will start demanding the streamlining of analytics projects so that they can “turn around in a quarter.”™

4. Enhanced integration of IT and business stakeholders – Business analytics will bring the long- sought goal of better integration between IT and business stakeholders within companies. Business analytics will become the bridge between IT and business stakeholders since it answers specific business questions that are implemented through the enterprise by the IT organization.

5. Resources with analytic skills will continue to be a hot commodity – Companies will seek these resources to incorporate them into their infrastructure. As the demand for these finite resources increases, the marketplace price will increase.

6. Outsourcing and Offshoring of analytic projects and resources – Companies will seek analytic business models that can turn projects around quickly and seamlessly within their infrastructure. They will discover that it takes a combination of analytics, IT, and project management skills to successfully implement an analytics project with measurable business lift. Outsourcing and offshoring models will become a more attractive alternative in terms of pricing and delivery.

7. IT organizations will continue to struggle with analytics projects – The learning curve of the differences and similarities between analytics and IT projects will continue to plague IT organizations, and outsourcing and offshoring delivery models will become more attractive methods to deal with these issues.

8. Analytics tools will continue to thrive in the marketplace – Companies will continue to purchase these tools to give them the ability to predict and segment their big data. Analytics appliances that are industry- and problem-specific will proliferate in the next 2-3 years.

9. Social media integration with transaction data will become a priority for business stakeholders and the IT organizations – Companies have a gut feeling that this data is important and that it will help them to better target their customers and decrease costs. Although companies will struggle with this integration issue, they will ultimately turn to using advanced analytic techniques for successful and measurable business lift integration.

10. Voice recognition and natural language software will become a major data integration issue – As companies increase the use of voice recognition software, integration of these massive amounts of data will become a challenging issue and they will turn to advanced analytic techniques to solve this issue.

11. Big data analytics will become a priority for companies – As companies acquire more and more data, the issue of how to get value of this data will become a priority for many companies. The difference between having big data and getting the most value of this data will become part of the strategic goals for many companies. Big data with actionable and measurable business insights will go hand-in-hand.

12. Continuous improvement and refreshing of predictive models and business segments – As companies implement predictive models and statistical valid segments within their organizations, the ability to improve and the need to know when and how to automatically refresh these models will become an issue for many IT organizations. Initially, companies will move to offshoring and outsourcing these tasks. In the longer term, IT organizations will look to automate these tasks, and they will incorporate techniques such as embedded analytics.
Innovation is alive and thriving in the area of analytics.  Applications in different industries, cross-utilization of techniques in different domains, and new optimization techniques are always improving.  The future belongs to the young generation and the role of my generation is to provide guidance so their dreams are realized.  Let us roll up our sleeves and work for a better and brighter future.  We are unleashing the power of the mind!

8 comments:

Anonymous said...

Great list and spot on.

I have been in the analytics field for 20+ years. When I entered the market, I thought that it was obvious that data was the key to insight generation and the intelligent management of any business.

We had to wait for the world to work through transactional processing before we could realize the benefits of analytics on a widespread basis.

Drucker was right. We spent the first 40 years of computing automating accounting. In my opinion, this was dull, but necessary.

We can know spend the next 15 years building systems to synthesize data, generate insight and utilize intelligence.

Happy New Year to the global analytics community! This is our day. Seize it!

Best,
John K. Thompson
Chicago
jkt@mktng-sciences.com

Edith said...

Alberto,
This is a very nice wrap up. Much agree. Right view of the market needs.
Yet, in view of the fulfillment of previous expectations, maybe we should pay more attention to the theoretical gap - in my eyes it is the theoretical reliance on Statistics gets the analytics stuck. For example, the need to have a prior assumption – it obviously limits the findings.

Edith

Edith said...

Alberto,
This is a very nice wrap up. Much agree. Right view of the market needs.
Yet, in view of the fulfillment of previous expectations, maybe we should pay more attention to the theoretical gap - in my eyes it is the theoretical reliance on Statistics gets the analytics stuck. For example, the need to have a prior assumption – it obviously limits the findings.

Edith

Edith Ohri said...

Alberto,
This is a very nice wrap up. Much agree. Right view of the market needs.
Yet, in view of the fulfillment of previous expectations, maybe we should pay more attention to the theoretical gap - in my eyes it is the theoretical reliance on Statistics gets the analytics stuck. For example, the need to have a prior assumption – it obviously limits the findings.

Edith Ohri
Home of GT data Mining

Olin Hyde said...

Interesting list. I think you are missing a massive item: The biggest problem facing analytics is the inability to process and understand unstructured data -- such as free form comments in social media, etc. The memes, phatics and other idiosyncrasies of human language do not translate into nice little algorithmic plug-ins for COTS BI systems. Rather, artificial intelligence and machine learning tools will likely change the way corporations use analytics.

Rebecca said...

Great post! I especially agree with your last two points regarding the importance of not only collecting data, but having the ability to understand it and make strategic decisions based on it. Predictive modeling is perhaps the most difficult but with the right data - and the right understanding of that data - it is what will set companies apart from their competition.

Matthew Martin said...

A very interesting list, it's good to see (almost) everything brought together in one place. Food for thought for sure.
Matthew

casquette new era said...

We had to wait for the world to work through transactional processing before we could realize the benefits of analytics on a widespread basis.

Drucker was right. We spent the first 40 years of computing automating accounting. In my opinion, this was dull, but necessary.

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