How To Cope When The Project You Are Leading Fails?

 
Everyone fails at some time or the other. Failures are meant to be dealt with and learned from. Yet, there isn’t a single training course that deals with fears of failure, coping with failing projects or handling failures at work. And this, despite the fact that project failures cost money, maybe losing a client and leaves you despondent and feeling completely at sea. So read on to discover the simple path.

Realization and acceptance of failure:   

Admit the failure and accept the fact. Don’t run away from it and blame others. After all, as a Project Manager, you will realize that there are many factors leading to the failure of projects. Face it that you are not alone and solely responsible. Failures can happen to all of us. How you walk-on is more important than how you celebrate project success.

Know when to let go:

Never get stuck with the sinking boat. There is only the drowning way out if you don’t bail out in time. The tell-tale signs of reduction in buy-ins, missed timelines, apathy from the senior management, costs incurred so far, and last but not the least your ego and knowing when to let go.

Review and review constructively:

The project has failed and it is now your failure. So get to the task of a constructive passionless review of where, why and when the train got off the rails. Take responsibility for your team and the failed project. In part, it is your failure!
Were deadlines missed, were resources competent and timely, were there any tell-tale signs of off-roading, what exactly have you failed at? Well, seek and you will find. Recognize your mistakes and be sure that they will ensure you don’t go the path of failure again.

Bias will color your sights:

Reviews often seek reasons for project failure. Seek them without bias. Have an outsider audit the process, don’t look for reasons that confirm the easy way out, and avoid blaming others when things don’t go, as you planned. If you knew along it was doomed, why did you not act? Optimism is positive when in moderation as is bias and playing the blame game.

Don’t play the blame-game:

The PM has to bear the brutal brunt of a failed project. It’s the job, not the person that is being blamed. Check to see what lessons you can learn, what were the signs you did not see, how can you prevent the same one happening again, how can you get your team up and running, what really was your role in the error. Now that it has happened, move on. Do what you can as the PM and do it best, is a great policy to follow, now more than ever!

Plan to better implement projects rather than produce better products:

Let your focus be on doing things differently the next time around. As leader of the team, concentrate on implementation practices rather than a high-velocity release of products. Your team will produce results when you lead from the front and help implement projects better on time and within the budget each time, every time. There will always be so much beyond your control to complain about another day.
In parting, let’s remember failure is a great teacher. Great lessons are learned and success implies always trying to gain control even beyond what you can actually control.

AI for IT Services Firms Backup Recovery And Cybersecurity

The coming of the Age of Artificial Intelligence is an apt way to describe how IT services like cyber-security, recovery of data and backup of data has been impacted by AI developments globally. Any event on cybersecurity throws up newer requirements in cyber-security and a bouquet of innovative solutions using artificial intelligence, cloud storage, and data recovery tools.
Virus detection is a challenge-area that about 29 percent of surveyed professionals look to AI for as per ESG research. Besides speedy discovery, 27 percent of the surveyed professionals in the security field look to AI to hasten the response time of reported incidents.AI is being touted as today’s technological marvel that can analyze huge volumes of code in very short time periods. This is rightly true and the mind-boggling speeds and analysis of data have made AI all pervasive and the panacea to almost all ills in the IT sector.
AI Vs ML:
The terms AI and ML are being used oft interchangeably. In reality, both are useful tools that differ in their thinking abilities. ML uses algorithms to detect breaches in security which restricts their use to think outside the set framework. On the other hand, AI does not need algorithms or any further data when it comes to terms with any issue. It arrives at an unassisted intelligent conclusion.Both AI and ML techniques are the focus areas of dealing with advances in cyber threats. These techniques when applied can transform the scenario from defence to early detection and quick response to cyber infections.
Areas, where ML makes a huge difference, are

  • In scouring huge data volumes across thousands on nodes looking for potential threats.
  • In firewall applications, gateways, and APIs where traffic patterns need to be analyzed.
  • In classifying data objects and governance of data
  • In access-control and authorization systems and practices using auto-generate policies, and analysis of the regulatory measure, rules etc
  • In detecting anomalies and setting baselines for user behavioural analysis and SIEM events of cybersecurity.

Hacker’s too can use ML and AI:

Alongside the new developments in AI, cyber-security, and ML there is a the all real possibility of hackers also using the same infection-detection technology and malware samples to advance the technology of cyber-threats. It is reasonable to predict that the very same techniques are used by hackers to create modified code-samples depending on the way AI detects infections. This then leads to a situation where the infections last longer and since the code is smaller it becomes near undetectable.

Storage challenges and Cybersecurity:

The feasible option for safe storage of data today is by backing data to a reliable disaster recovery cloud which enables rapid recovery of files while ensuring the data stays protected, safe and encrypted. The market has many technological options like Avast, CA Technologies secure, Keeper, etc that can help keep data copies out of reach by hackers and yet available on an easy-to-use platform.
In conclusion, the use of ML and AI can help resolve issues and challenges faced in cybersecurity, data recovery, and storage. The evolution of threats and detection techniques continue in tandem in a seemingly unending fashion where users and hackers are both looking to AL and ML for solutions.