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    Scaling Business with Software Automation and Dedicated Team Component

    Scaling Business with Software Automation and Dedicated Team Component

    Sergey Bondarenko, CEO Skywell Software LLC


    9 min read

    Data Protection for User Privacy & Effective Competition

    The new law transcending the EU’s borders appeared to deliver a perfect storm for business to rethink current image of data protection under the GDPR rules enforced globally. This time, coping potential cyber breaches won’t necessarily need enterprises to face complex challenges that usually call for similarly sophisticated actions and solutions of the highest complexity. In a nutshell, there is nothing to do with these “hard footsteps of doom” we can almost hear coming with related measures to personal data protection for all — the EU citizens themselves, residents outside the alliance, and de-facto elsewhere on the globe. No doubts that potential financial penalties will definitely spur companies into actions, actually no matter how concerned they may be. It’s better to play safe with your dedicated team instead of incurring the risk of hefty fines, which are believed now to be easily arranged to up to 4% of average business annual turnover. And we think that the process of driving greater compliance should now be recognized by companies as a source of competitive advantage, rather than just messy or even directly cost-draining junction.

    With attention to those marketing messages under the EU’s GDPR compliance messages that have been actively kicked in lately — almost every online user on the glob must be already familiar with current undertaking. Apparently, there have been multiple emails from merchants and service providers received by all of us, without exception. Coming as polite reminders, these messages might as well easily provide another marketing advantage, at least against those market rivals who aren’t that proactive. So, it’s time to rush out and restore some trust demanded by today’s data-driven world.

    GDPR compliance

    Scaling Tech Startups with IT Innovation & Software Automation

    Although the world is materially spread with IT innovation and active, innovative people, bringing successful products or well-demanded services to market still has a considerably more uneven challenge than we might think. Lack of resources, insufficiently robust “supportive” community, the dominance of already established players, not to mention the inertia of marketplace itself — all these disruptive factors are often holding many technically sound concepts and even genuinely progressive ideas back from their deserved commercial success. 

    For the most of alternative thinking on commercializing technology innovation fueled with rapid scaling, there are two principal approaches — Agile & DevOps. And below are several practical observations backed with project-based remarks that could be useful for business executives and project managers:

    Product/Service: High Value Added at Short Chain

    Delivering real added value to the end user is the matter of core importance to every business. Companies involved in the modern IT sector should encourage feedback, emphasize tight customer interaction, welcome public proceedings, in line with taking strong adaptive and learning priorities beyond all. Unlike big monolithic enterprises, tech startups must be rapidly scaling to keep up with the ongoing developments in the industry. In fact, it’s arguably the only way to assure further progress and the whole project survival. It’s also crucial to have a reasonably short value chain would be the best fitting decision, at least initially. The whole project may be quickly bogged down with too diverse tech portfolio when innovations stemming from different agendas appear aligned with too many institutions. On balance, setting a tight and reasonably small supportive supply chain would fit best. That way, your team will be able to drive its everyday operations to the level of “over-collaboration.”

    choosing best way of scaling business using software automation

    IT Innovation Cycle: RAD-based Tactics

    For the most part, possessing an extensive arsenal of top-notch technologies doesn’t necessarily mean software product is destined to succeed. The global objective should never push dedicated team the way of “over-innovative” development when the process is finally found jam-packed with lots of needless tech innovation. Project management can eliminate this threat by setting maximum realistic targets. More importantly, governance must always stick their implementation effort. Based on the industry experience, brands are too often caught up in a dreadly competitive race, when the all falls into out-innovating each other. In reality, tech business should be maximum relevant to the actual needs and requirements of the user. To get innovative improvements aligned with the customer, it’s necessary to adhere to Rapid Application Development tactics, which turns development process into more adaptable one. Therefore, flexible software teams are recommended to rely mainly on intensified prototyping to keep tweaking their software products until fast-paced, and ever-changing market demands are met in full. In a nutshell, communication is everything.

    cutting development chain

    For Conclusion

    In closing, we should emphasize the lack of holistic and systemic approach to optimization being arguably the most essential condition of successful IT innovation. As a final point, I’d like to have a peek into future of software automation and machine learning. Based on the recent findings, the industry experts are now calling dedicated team leaders and IT decision-makers to consider these two proximate trends for monitoring throughout this year.

    Maturing machine learning appears now even more likely to drive the core growth areas in software automation via self-learning. Taking a measurable part of developer’s responsibilities, soon that can be proximately developed to enable automated systems successfully provision optimal resource allocation, for example, to meet deadlines. It might as well help the developer quickly identify the most appropriate system analytics to execute the process by software. Among the other opportunities, as an example, we’d like to point to automated testing already seen changing production environments throughout widespread adoption of test scripts.

    Machine Learning Typing Robot

    Developing AI opportunities won’t make us all out of a job, although the integration of artificial intelligence capabilities keeps gaining momentum. Perceived for the coming years as one of the most critical success factors for business, all new functionaries will still need lots of human oversight. IT professionals will surely benefit from growing software automation, which keeps cutting the amount of manual infrastructure operations and creating immediate value. But when it comes to determining whether a predictive thing might become prescriptive one or, for example, information security and pipeline maintenance — neither new machine-learning applications nor automated software solutions can replace human management, at least for now.

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