The degree to which businesses gather and analyze information will deepen and expand in 2012. For example, automakers currently have entire marketing divisions dedicated to understanding customer buying patterns and preferences. They build their customer relationship management (CRM) strategies based on this intelligence, and are able to reach the customer with a targeted and relevant product or service offering when their propensity to buy is the greatest.

However, there is a significant lag between the availability and conversion of customer specific information into a timely and relevant marketing initiative. Our data rich environments have yet not enabled an automaker to detect when a customer starts shopping for another, larger, smaller, or more fuel efficient car. Customer conversations (with service reps, dealers and online discussions with other customers) are still not being accessed in a timely manner to generate actionable intelligence. Ultimately, customers are unpredictable, but very expressive, especially when dissatisfied.

Clearly, the more companies understand customer preferences and behavior, the more targeted and relevant their communications can become. As an example, an automotive manufacturer’s customer segmentation would be immensely improved if it could enrich the CRM generated demographic data with its customers’ financial information available in the public domain.

Businesses are already beginning to use multiple information sources to target segments and customers. My prediction is that companies will rapidly supplement their strategies by aggregating discrete databases from different parts of the buyer ecosystem — from banking, retailing and lifestyle choice patterns—developing predictive models of what customers are likely to purchase next.

When you are in the market for a new car, the dealer will determine from your home address the demographics of the neighborhood in which you reside, its value, and who lives in the house. By combining this with your credit card spend, purchase behavior and your current vehicle, the manufacturer can start expanding the lens through which it views you as a customer. It can begin to position products and services based on your lifestyle, needs and preferences.

Rather than increasing marketing spends, businesses will look to syndicate information such as card spend patterns, Google Plus location data, and vehicle telematics. While marketing analytics can conceivably infringe on privacy, the information that may be gleaned from “Big Data” in an increasingly connected world looks too valuable and insightful to pass up! As a recent article in The Economist, “Building with Big Data” claims, “Data equity…will become as important as brand equity.”

Increasingly, businesses will replace static management models with dynamic ones using artificial intelligence (AI) as a norm rather than exceptions. AI’s new value will be in refining operating models that drive “variable” cost structures.

All businesses are routinely subject to fluctuations. For example, when the price of oil goes up, the cost of a produced product also rises. Instead of operating businesses along steady state models, investors will have access to sophisticated projections based on any number of variables. As investors start getting hitherto unheard of visibility into the variability of their business, they won’t be content to sit on fixed costs. They will invest in AI-based, preprogramed algorithms to push work via cloud-based infrastructure to an ecosystem of service partners that will deal with volume spikes and slacks. This will logically lead to service providers becoming more nimble to meet the needs of clients who will demand optimized flexibility, especially for transaction oriented, standardized work.

Companies will adapt their business models and technology platforms to incorporate such ecosystems of on-demand partners compensated on a “per transaction” basis. These on-demand outsourcing services will come as packaged solutions on tightly integrated platforms with applications, making it possible to embed best practices and ultimately deliver greater efficiencies.

We live in a zero latency world awash with real time data. Managers need real time information to make decisions in milliseconds as decision making windows can open and close quite rapidly. Like it or not, in the near future your company may be competing with a computer. In fact, companies with the fastest computers, most sophisticated algorithms, technical know-how and most complete data sets will begin to separate themselves from competitors. Companies that can process information and make intelligent decisions faster than competitors have significant advantage.

When it comes to decision making, too much speed without attention to improvements in logic and business processes can be disastrous. Enter the Event Programming paradigm. In computing, event-driven programming is when the flow of the program is determined by events—i.e., sensor outputs or user actions (mouse clicks, key presses) or messages from other programs or threads. In the AI environment, when an event occurs, it will automatically suggest subsequent actions. We see this logic used in sporting events. In a soccer match, if there are repeated unchecked advances to the goal line, the coach may modify his game plan. To strengthen his defense line, he will likely shuffle some players and positions, maybe even push for an intentional fault to slow the game down. In this case, his game plan is played out as a preprogrammed event in his head, based on “if this, then that” scenarios. Businesses will begin to adopt analogous approaches to their operating plans so that the activities of customers, competitors and other market changes will dynamically trigger certain pre-programmed actions.

I foresee the coupling of Business Process Management (BPM) and Six Sigma driven, event-based programming in a zero latency world. This will further enable the outsourcing of even more complex processes to specialist companies.

2011 was certainly an eventful year. Expect an equally exciting 2012 for business. I see it as the starting line of the race for integrated customer intelligence, an on-demand workforce, and real time and dynamic business models. These technology-enabled scenarios will be key drivers for the business virtualization that companies seek for agility and sustainability. 2012 may thus mark the beginning of new ways forward with technology in the driver’s seat!