Republicii Street, No. 9, TM, Romania +40-256-201279
Leadership

ZDNet takes a look at the AI and Machine Learning predictions, in what the business environment is concerned. Expected to surge in 2019, the rapid adoption of these new technologies also brings different business challenges.

The article mentions the necessary (and huge) shift that is absolutely required for organizations to thrive. Going from buying “black boxes that will fix our problems and offer us solutions” – as the publication puts it, to the next stage, won’t be easy.

A passive attitude welcomes possible cases of “algorithm sprawl, project management issues, and vendor hype”.

But what modern, wise organizations do? How can we all avoid the so-called bad implementations of AI & ML?

 

 

Who will have to handle AI data?

Since data science is not a magic  trick – although sometimes it may seem so – in order for it to work, key people in your company come in. Apparently, “everyone from mid-level managers to C-level execs are going to use this AI”. They also need to understand how to use it, to be prepared and aware of this new age of technology.

Therefore, determining who will work with your AI data is absolutely necessary. You need the big picture before going into details. However, getting the right big picture requires experience.

Use experts – get consultancy as an ally in this big battle. You want to understand what will be going on, and someone who can put the process into perspective can make you go a long way. Having worked with systems, apps, connected data, Artificial Intelligence and data science, professional consultants can provide a reliable blueprint. How will it work for my business? The answer to this is much more accurate when you obtain it with the right guidance and assistance.

 

What does your AI data need to provide answers for?

As the article we’ve mentioned lists, operating Big Data generates effects that go beyond the lucrative insights.

You will also need to have a strategy and to deliver reports to your board.

As the process evolves at a global level, you will need to choose the most suited AI services pack – from the big tech cloud providers.

Data scientists are still scarce, and the models you will be dealing with lack transparency.

The AI-trained professionals are also scarce, and this specialization just made its way into the academic curriculum. For now, hands-on experience prevails.

Your AI data needs to provide answers and guidelines for all of the above, and more. You will be working with a tool with huge potential that you barely understand. Nevertheless, you need to move relatively fast while making the best choices. The AI tools unleash their potential on the go. Add an extra layer of software solutions – and you have a new functionality. Get on board with the best cloud provider, and you will be able to deploy your tools next-level style.

 

Prepare for the next step, by getting a partner that understands the new technology

It’s not only AI. As we’ve seen, it’s also Machine Learning, Big Data, algorithms, analytics, IoT, embedded sensor software, various layers that have to integrate with each other.

Working all these out into the strategy of your company, while resetting certain functionalities and expanding others – this won’t be easy.

As all things good and new, as overwhelming as it may seem, it needs to be done. The sooner, the better. Make the first step and choose a reliable software partner, one experienced in business digital transformation. Call, talk, schedule the meetings you need, soon you will have a whole new perspective on the matter.

 

We are here for you – our know-how and experience are both rich, and our eagerness and innovative spirit are the right match for this future of technology.

Contact us and let’s find out more about how a potential partnership may look like, and what it can do for both of us!

0

Leadership

We like to innovate. LASTING Software is the consultancy & software development company with a “no excuses” mindset. We have a clear focus on delivering the right product from an end-user’s perspective. Our specialists always put themselves in the clients’ shoes and deliver solutions that fit actual needs.

We…
develop the graphics engines & tools which allow you to control your car and view your world.

create medical systems that monitor and protect your families.

enable 100’s of smart factories around the world to manage their Materials Planning.

realize the algorithms and analytics processing Big Data, which underpin 1000’s of FDA/FMA clinical trials.

build news apps which allow you to report ‘Real news’ in ‘Real time’ with data driven journalism.

transform statistics and analytics into insights on your KPI’s in cloud based AI decision systems.

 

Development for the future – what is different?

Big Data starts with quantity, but it is not all about it. Quality also matters – as the professionals around the globe have already determined. Quality data leads to quality results. But the companies still need the best algorithms to sift through it, process it and deliver the most valuable insights.

Still, being able to access a larger quantity of data makes the big players in any field keep up their advanced pace. Trends can be computed into mega-trends. It takes a quite powerful business stance to be able to see things at this kind of level. That is why we constantly follow topics that concern our activity. Keeping updated with what other top level professionals do or think is a good way of taking advantage of Big Data insights, by proxy. Combined with our own experience and insights, this allows for trend anticipation.

On this line of thought, this week we noticed an article about the way organizations innovate. It’s about the manufacturing space, about the way the products’ UI needs to change. The delivered solutions have to meet the challenges of tomorrow.

Now, one may argue that software engineering is in a different league than manufacturing – and they would be right, of course.

However, when trying to innovate, understanding how people work on a scientific level is important in any line of work. For all successful innovators, the mindset is common. It acts like a unifying field that brings together all those who know or learn how to design and implement for the future.

 

To innovate, one has to start by being accurate


Whenever aiming to create completely different/improved elements, one needs to know the premises extremely well. Only by being aware of what has already been done (and how), you can come with that great extra element. That is why we fully assess our customers’ operational needs before providing possible solutions.

 

Remember that here, at LASTING Software:

  • The types of collaboration available include extension of the team, feature teams, or entirely independent product teams;
  • Communication is essential to establish the issues to fix, the elements to improve and the best software-related choices;
  • We design a plan that would best serve the requirements, and agree upon the software modules or solutions to implement and design;
  • The options are to adapt the existing software, or develop the new software to best suit the customer’s needs;
  • We deliver our product on time. Next, we provide support in the implementation, user training, and post-implementation stages;
  • Same room collaboration is greatly valued – nothing surpasses the power of personal collaboration.

 

Besides the expertise of the workforce, innovation requires a curiosity for the new, courage, determination, structure and a will to succeed. Focusing on what customers need now and in the future, along with what will make them more effective and efficient, proved to be the best way to go about becoming more innovative.

People need to be tenacious in their questioning of the status quo and accepted wisdom. They need to be able to anticipate mega-trends and incorporate them into products so that solutions are futureproofed for themselves and their customers.

Quote source

 

0

Leadership

We enjoyed reading this article published by an infrastructure engineer from Quora, Angela Zhang. It presents project phases, focusing on the right way to do project scoping, in a realistic and efficient manner.

As we enable teams to deliver products to market faster, efficiency is key. We facilitate delivery in multiple markets without having to incur the costs and time delays in ramping up permanent organizations. Subsequently, have learned hands-on how to speed up the R&D process and reduce time to revenue, as well as reduce burn rate. Indeed, developing a realistic and revised version of the project plan is important.


The article we recommend talks about a few best practices in the field. It is concise and it provides a good insight view. To quote just a couple of paragraphs:

De-risk the project as soon as possible. Two common ways of de-risking a project include (1) working on the riskiest parts upfront, and (2) prototyping the riskiest parts using dummy data and/or scaffolding. Whenever a new open-source system or external service is used, that usually represents a big risk.

&

Define measurable milestones to get to the project goal. Schedule each with a specific calendar date representing when you expect this milestone to be reached. Then, establish some sort of external accountability on these milestones by, for example, committing them to your manager and setting up milestone checkins.

*Visit the freeCodeCamp page on Medium for similar articles.

*Our way of working ranges from fixed-cost projects to time & material projects. Also, the types of collaboration available include extension of the team, feature teams or entirely independent product teams.

0

Leadership, News

As we spend most part of each weekday at work, it is only obvious why company culture is so important.

We immerse ourselves in an environment that should make us grow and develop. On the other hand, imprinting company values on different persons is a continuous process. It is also a very satisfying part of being a leader. Fascinating and sometimes complicated, the process leading to a successful outcome has a backstage phase.

Defining the company culture is proactive. You realize that you want to do it. You analyze, discuss and establish an identity. Authenticity is a permanent companion in this – or it should definitely be one.

But how did the professional perception of company culture evolved in the last decade?

 

A common denominator for company culture

In a quest to be unbiased, we chose HBR as a common denominator. Yes, we could have used insights from our own company. But, as we established ourselves as a standalone entity 18 years ago, in this big picture we are adolescents. Maturity is at the horizon. Yet, we are proud of our culture, and we learned and progressed with hands-on experiences.

Yet, the focus of this exercise involves a higher degree of societal relevance. How did the company culture concept evolve globally? What can we learn from comparing older and more recent recommendations from the same influencer?

 

Early 2000s – understanding the importance of values

This 2002 HBR article tackles “the confusion underlying many values initiatives”. Companies were willing to change something about their culture. But they were unsure about how to do this.

Besides listing the types of values, the article insists on three essential recommendations. One of these is to be aggressively authentic. Another one was to own the entire process. We’ll leave you to find out by yourselves the third one.

 

A decade and a half later, standardization makes its way

Most of us know by now why the “five ways to…” and “seven recipes to…” articles flood the online. They are SEO-compliant. They perform well with the search engines and at the same time attract the reader into clicking on them. Curiosity takes the better of all of us, sometimes.

However, these types of article also serve clarity and summarization. When experienced authors list rules and recommendations, you can be sure they used a thorough research process. Narrowing down a long list to just a few items surely takes time and pondering on the scope-matter. 

There we have it – in 2015 HBR mentioned 6 rules for building and scaling company culture.

In short, the rules were:

  • start with purpose
  • define everything clearly and use a common language
  • lead by example
  • work with your cultural ambassadors – aka, the people who naturally love and embrace the company culture
  • be truthful in your actions
  • wisely manage the human capital (“hire for attitude, train for skill”)

The article goes into insightful details, of course. What we extracted from here, however, is that earlier theories (see the 2002 article) have been confronted with reality. All the validated ones now became rules. Although the time span between the two features is large, we can notice how some of the recommendations are the same. Authenticity (truthful actions) is still present, proving that it doesn’t get obsolete. Ever.

 

2017 – Routine and bigger teams generate new issues

Two years later, and the same publication approaches another side of the problem.  Some strive for creativity and out-of-the-box solutions. But the company culture also includes those who perform routine tasks. Bigger team dimensions, plus routine may equal mediocrity. Mediocrity affects the entire group – and is ultimately counterproductive.

Demanding a step up to higher performance is not easy – and it should be rightly done. HBR provides 4 answers to the mediocrity issue:

  • show the consequences (establish and state the cause and effect connection clearly)
  • react with meaningful measures (and proportionate ones)
  • establish peer accountability (a fuzzy accountability distribution is highly unproductive)
  • defend the high performance standards vocally, “regularly and vigilantly”

 

2018 – Chronic company culture issues are toxic

In 2018 our influencer of choice went back to the big picture analysis. Their article on toxic company cultures speaks of the necessity of cultural capital. Investing in this type of capital is important. The cultural capital is a core element, “a type of asset that impacts what a firm produces and how it operates”.

Companies with a low cultural capital do not reflect the formal policies and procedures in the daily operations and habits. There is a disconnection. Somewhere in-between rules the traditional economy still applies, and the mere financial savings are the most important.

By keeping up appearances (and nothing more), these companies may feel like they get ahead of their peers in a sneaky way. Admittedly or not, they are trying to get by in the new economy, by re-using the old rules. In the long run, they end up just fighting against themselves.

The article analyzes why companies won’t invest in cultural capital, even after being aware this is bad for them. It also brings in a few public sector considerations. Turns out that the public sector influences the private one. It may encourage resiliency and support vital policies that ultimately shape people. Or it may not.

 

Pointing the finger at the most pressing problems, one by one

The 2018 HBR directory of articles as configured by the “organizational culture” topic selector looks like this – click here.

You may notice how the biggest issues are pointed out. From widely politicized problems to leadership questions, each one has its own article.

Workplace diversity, gender equality, pervasive peer attitudes, and a performance-obsessed culture – they are all in this list. The articles are interesting and they may well get you thinking. What does your company culture look like? Which are the most pressing unresolved matters?

0

PREVIOUS POSTSPage 1 of 2NO NEW POSTS