Information Technology (IT) tools are here to support your business in the global market. Effective communication is key for IT and business experts to collaborate effectively in search of solutions. Consulting, reaching out for help to a third-party, can bridge the gap between your business marketing experts and IT operations experts, especially with the emergence of big data analytics and its implication on the global market. Having the right consultants equipped with business knowledge and data technology expertise can make a difference.

Your marketing organization is probably familiar with digital tools and conducting global research. Its results can uncover the journey customers take to purchase your products or use your services. It can highlight the pain points and frictions that prevent their experiences with you to be delightful and amazing. Armed with this knowledge and beautiful compelling presentations, marketing executives expect that IT operations leaders will translate these insights into actions.

But people in IT operations are too involved in meeting key performance indicators that have nothing to do with the end customers. Meeting requirements of faster and cheaper don't translate very well into customer satisfaction. A classic breakdown in communication is described in a Harvard Business Review article, “A Technique to Bridge the Gap Between Marketing and IT.” The author goes on to describe how a new CIO at a bank found IT to be focused on the internal organization as their customers, rather than the real end customer. Moreover, no one was looking at the incident reports which clearly showed that incidents were increasing. And nobody looked at what these incidents were doing to the bank’s customers. The startling and scary numbers of incidents were caught and addressed and brought down from 1,000 to 600 or (40%) and later to 450 per week.

Surprisingly, these type of seemingly isolated scenarios are still being discovered within organizations presently, sometimes internally, and through third party insights such as consultants.  By engaging consultants to provide a perspective based on what they’ve experienced before, they can often bring new and innovative ideas or possible challenges to the table that an internal processes probably wouldn’t have been able to see on their own.  Often, third party input can help to provide the translation needed to go from marketing research results into actions that IT operations can understand and make sense in their high-performance culture. When companies understand and use this knowledge to reassess how to improve their customer experiences, they work backward from what customers want to achieve significantly higher improvements. 

IT and business management are more and more being asked to move away from their traditional roles, such as IT being the "technology infrastructure gatekeeper", and instead become enablers across the enterprise of effective collaboration, big data consumers, and key players in driving desired business outcomes. Marketing leaders look to technology as a way to facilitate the customer's journey and his positive experience of it, bring more clients, and meet increasingly higher loyalty goals. They rely on IT projects to enable big data-based behavioral targeting anywhere in the global market. This means projects to analyze search engine results, improve website personalization and optimization, and building of mobile applications for a more personal experience. All these are projects that consultants with their communication, consulting and technical expertise are well prepared to help in order to bridge the expectation gap between IT and other business organizations.

In order to meet these 21st-century business challenges, Information Technology organizations have been transitioning from waterfall stage-gate project management approaches to agile development. The stage-gate method applies a step-by-step approach where waiting, reviewing and approving are required before moving to the next step in the project. Agile management emphasizes collaboration, no decision hierarchies, and few people roles for making quick, customer-focused small changes over time to deliver solutions that delight and amaze customers. Agile development has allowed many businesses to respond quickly to changing customer desires and expectations. But moving to continuous delivery is a struggle requiring focused, dedicated teams that are not well suited to the traditional matrix organization where people are resources whose time must be "chopped" into many pieces and shared among many projects. Agile teams meet frequently as often as daily but never waiting more than a week to do so.

Marketing people are externally focused. IT people are internally focused. The first works with customer emotions. The second works to increase efficiency. Big data analytic tools are used by the first and supported by the second. Consultants can be the glue that helps both come together in effective collaborations that deliver positive business outcomes in both global and local markets.

I suspect that many of you are familiar with the term "hard coding a value" whereby the age of an individual or their location is written into the condition (or action) of a business rule (in this case) as shown below:

if customer.age > 21 and customer.city == 'denver'

then ...

Such coding practices are perfectly expectable provided that the conditional values, age and city, never change. They become entirely unacceptable if a need for different values could be anticipated. A classic example of where this practice occurred that caused considerable heartache in the IT industry was the Y2K issue where dates were updated using only the last 2 digits of a four digit number because the first 2 digits were hard-coded to 19 i.e. 1998, 1999. All was well provided that the date did not advance to a time beyond the 1900’s since no one could be certain of what would happen when the millennia arrived (2000). A considerably amount of work (albeit boring) and money, approximately $200 billion, went into revising systems by way of software rewrites and computer chip replacements in order to thwart any detrimental outcomes. It is obvious how a simple change or an assumption can have sweeping consequences.

You may wonder what Y2K has to do with Business Rule Management Systems (BRMS). Well, what if we considered rules themselves to be hard-coded. If we were to write 100s of rules in Java, .NET or whatever language that only worked for a given scenario or assumption, would that not constitute hard-coded logic? By hard-coded, we obviously mean compiled. For example, if a credit card company has a variety of bonus campaigns, each with their own unique list of rules that may change within a week’s time, what would be the most effective way of writing software to deal with these responsibilities?

Applications are becoming more and more sophisticated as languages such as Python open the doors to the world of programming for people who have the creative vision but always felt actually writing code was beyond their grasp.

A large part of any programs success is based on how well it can react to the events which it has been programmed to understand and listen for.

A good example of an event would be when the user clicks a button on the applications window. What happens when that button is clicked?

Well, the first thing that happens is the operating system sends out a message to let any listening software know that the button was clicked. Next, your application needs to do something in response to that event.

Let’s face it, fad or not, companies are starting to ask themselves how they could possibly use machine learning and AI technologies in their organization. Many are being lured by the promise of profits by discovering winning patterns with algorithms that will enable solid predictions… The reality is that most technology and business professionals do not have sufficient understanding of how machine learning works and where it can be applied.  For a lot of firms, the focus still tends to be on small-scale changes instead of focusing on what really matters…tackling their approach to machine learning.

In the recent Wall Street Journal article, Machine Learning at Scale Remains Elusive for Many Firms, Steven Norton captures interesting comments from the industry’s data science experts. In the article, he quotes panelists from the MIT Digital Economy Conference in NYC, on businesses current practices with AI and machine learning. All agree on the fact that, for all the talk of Machine Learning and AI’s potential in the enterprise, many firms aren’t yet equipped to take advantage of it fully.

Panelist,  Michael Chui, partner at McKinsey Global Institute states that “If a company just mechanically says OK, I’ll automate this little activity here and this little activity there, rather than re-thinking the entire process and how it can be enabled by technology, they usually get very little value out of it. “Few companies have deployed these technologies in a core business process or at scale.”

Panelist, Hilary Mason, general manager at Cloudera Inc., had this to say, “With very few exceptions, every company we work with wants to start with a cost-savings application of automation.” “Most organizations are not set up to do this well.”