A project manager acts as the primary link between business and technical teams. A project manager is responsible for maintaining the project schedule, developing project estimates, working with external teams and tracking project issues. The project manager belongs to either the technical team or the project management office (PMO). The project manager works with business teams, technical teams, business counterparts, testing resources, vendors and infrastructure teams.

A project manager is often challenged with diagonally opposite views from the business side and technical side. A project manager’s success depends on balancing the needs and emotions of both sides.

Understanding the Requirements
A project manager must familiarize with the project’s requirements as defined by the business or product managers. This will help you understand the business vision behind the project. You will need this knowledge while negotiating with the technical teams.

Understanding the Technical Landscape
A project manager must also understand the technical systems, resource skills and infrastructure capabilities available for the project. Business teams come up with expectations that are sometimes beyond the capabilities of the technology team. It is the responsibility of the project manager to understand the technical capabilities available to the project.

Walkthrough of Business Requirements
This is a critical step in the project delivery process. The project manager must invite members from the business team, technical team, testing team, infrastructure team and vendors. The project manager must encourage the various stakeholders to ask questions about the requirements. Any prototypes available must be demonstrated in this meeting. The project manager must find answers to all questions resulting from the requirements walkthrough. The project manager must get the final version of the requirements approved by all stakeholders.

Managing Conflicts in Timelines and Budgets
All project managers will face the conflicts arising from shortened timelines and limited budgets. Business teams typically demand many features that are nearly impossible to deliver within short timeframes. The project manager must work with business and technical teams to prioritize the requirements. If the project is executed in a product development organization, then the project manager could utilize agile methodologies to deliver projects incrementally. In this case, the project manager may be required to act as a scrum master to facilitate scrum meetings between various stakeholders.

The Art of Saying “No”
As a project manager, you may be forced to say “no” to demands from both business and technology teams. However, it is important to create a win-win situation for all parties when you are faced with conflicting demands. You can work with the stakeholders individually before bringing all parties together. Most stakeholders prefer to work together. The success of a project manager depends on how effectively he or she can bring out the best in everyone, driving everyone towards a common goal.

Finally, the job of a project manager is not to satisfy the demands from all corners. The project manager must identify the essential deliverables that will meet the business needs, with a solid understanding of what is possible within the limits of technology.

Related:

Smart Project Management: Best Practices of Good Managers

Is Agism an Issue in IT?

Straight up and full disclosure. I'm prejudiced. As a research assignment, the heading is a joke. I'll give you the answer in two words, and then tell you why.

How does HTML 5 compare with flash? Answer: it doesn't.

Lest you think I dislike Adobe's Flash, let's put the cards on the table. I loved Flash. Long before Adobe was Adobe, they had a competitor called Macromedia. Adobe bought that firm. That made my life simpler. I only had to work with one vendor.

Flash was a pretty compelling solution. I used it to mimic operations in Windows to prepare people for the CompTIA exams. The only bugaboo was that dang right-click stuff. A little bit of code from the Microsoft Visual Studio .Net let me flip the left and right mouse buttons so that the right mouse button instead of controlling the Flash player, emulated doing a right-click in the Windows operating system.

Outsourcing IT needs in the corporate world has become extremely popular because it is cost-efficient and it gives IT resources to companies that may not otherwise be able to afford them. Another positive side effect of IT outsourcing is that it has brought many technology jobs back to the United States.

As convenient and patriotic as IT outsourcing has become, it also have several limitations that have caused many companies to re-think the idea of funding their own internal IT group. It is important for a company to be completely familiar with these limitations before developing any kind of company policy in regards to IT.

The Customer Could Outgrow The Outsource Company

When an IT outsourcing company first takes on a new client, the relationship is beneficial to both sides. But things can start to get inconvenient for the client when the client's business starts to outgrow the capabilities of the IT outsource group.

An IT outsourcing company can become entrenched in the daily routine of its clients, which is great at first. But when the IT company can no longer keep pace with the growth of its clients, then the clients are stuck trying to find a new solution and keep track of its own IT assets at the same time.

The IT Outsourcing Company Lacks The Necessary Technical Expertise

IT outsourcing clients like to believe that their support company knows everything there is to know about computers and the Internet. But every IT support company has its areas of expertise and they have the technical areas where they are not quite as strong. If the client starts to experience needs from the areas where the IT outsourcing company is not so strong, then that can become a significant business issue.

This problem can be amplified if the client is a small business experiencing growth. An IT outsourcing company is not as likely to bring on new personnel for a smaller client, which leaves the client without a solution.

The Client Losses A Measure Of Control Over Its Data

No matter how large or successful an IT outsourcing company may be, there will always be the limitation of client security and the protection of critical customer data. All it takes is one rogue employee of the IT outsourcing company to compromise all of the client's critical data.

Some IT outsourcing companies have safeguards put in place to try and prevent client data compromise, but those safeguards are limited by how much access the IT company has to the client network. In most cases, that access has to be comprehensive for the IT outsourcing company to be able to do its job.

Outsourcing IT responsibilities can take a lot of stress off of a client and allow that client to operate his business by focusing on his core competencies. But there are limitations to IT outsourcing that could make it necessary for a client to do his own IT support and pay the extra costs.

Machine learning systems are equipped with artificial intelligence engines that provide these systems with the capability of learning by themselves without having to write programs to do so. They adjust and change programs as a result of being exposed to big data sets. The process of doing so is similar to the data mining concept where the data set is searched for patterns. The difference is in how those patterns are used. Data mining's purpose is to enhance human comprehension and understanding. Machine learning's algorithms purpose is to adjust some program's action without human supervision, learning from past searches and also continuously forward as it's exposed to new data.

The News Feed service in Facebook is an example, automatically personalizing a user's feed from his interaction with his or her friend's posts. The "machine" uses statistical and predictive analysis that identify interaction patterns (skipped, like, read, comment) and uses the results to adjust the News Feed output continuously without human intervention. 

Impact on Existing and Emerging Markets

The NBA is using machine analytics created by a California-based startup to create predictive models that allow coaches to better discern a player's ability. Fed with many seasons of data, the machine can make predictions of a player's abilities. Players can have good days and bad days, get sick or lose motivation, but over time a good player will be good and a bad player can be spotted. By examining big data sets of individual performance over many seasons, the machine develops predictive models that feed into the coach’s decision-making process when faced with certain teams or particular situations. 

General Electric, who has been around for 119 years is spending millions of dollars in artificial intelligence learning systems. Its many years of data from oil exploration and jet engine research is being fed to an IBM-developed system to reduce maintenance costs, optimize performance and anticipate breakdowns.

Over a dozen banks in Europe replaced their human-based statistical modeling processes with machines. The new engines create recommendations for low-profit customers such as retail clients, small and medium-sized companies. The lower-cost, faster results approach allows the bank to create micro-target models for forecasting service cancellations and loan defaults and then how to act under those potential situations. As a result of these new models and inputs into decision making some banks have experienced new product sales increases of 10 percent, lower capital expenses and increased collections by 20 percent. 

Emerging markets and industries

By now we have seen how cell phones and emerging and developing economies go together. This relationship has generated big data sets that hold information about behaviors and mobility patterns. Machine learning examines and analyzes the data to extract information in usage patterns for these new and little understood emergent economies. Both private and public policymakers can use this information to assess technology-based programs proposed by public officials and technology companies can use it to focus on developing personalized services and investment decisions.

Machine learning service providers targeting emerging economies in this example focus on evaluating demographic and socio-economic indicators and its impact on the way people use mobile technologies. The socioeconomic status of an individual or a population can be used to understand its access and expectations on education, housing, health and vital utilities such as water and electricity. Predictive models can then be created around customer's purchasing power and marketing campaigns created to offer new products. Instead of relying exclusively on phone interviews, focus groups or other kinds of person-to-person interactions, auto-learning algorithms can also be applied to the huge amounts of data collected by other entities such as Google and Facebook.

A warning

Traditional industries trying to profit from emerging markets will see a slowdown unless they adapt to new competitive forces unleashed in part by new technologies such as artificial intelligence that offer unprecedented capabilities at a lower entry and support cost than before. But small high-tech based companies are introducing new flexible, adaptable business models more suitable to new high-risk markets. Digital platforms rely on algorithms to host at a low cost and with quality services thousands of small and mid-size enterprises in countries such as China, India, Central America and Asia. These collaborations based on new technologies and tools gives the emerging market enterprises the reach and resources needed to challenge traditional business model companies.