Combining the strengths of systems integration and product development

Luke Taylor
Author: Luke Taylor CCO & Deputy CEO
Date: 2nd June 2016
Categories: Financial

In today’s ever changing environment where technology changes outpace most currency fluctuations (predominantly driven by consumer demand for more innovative services within highly competitive marketplaces), software vendors like ourselves have to ensure that we are constantly keeping ahead of the curve.  In the financial and telecommunication industry, where Neural Technologies predominantly focus, it is imperative that we have software product offerings that can meet and align to the needs of the organizations in these respective industry domains and be able to deploy these in a timely and effective manner.

Product development – the process of designing, creating and marketing new products or services to benefit customers.

Deploying large complex data analysis products such as ours inherently goes hand in hand with large data integration activities.  The success of such projects requires agility from both the vendor and customer to be able to evolve and adapt the project based on the constant changes in the industry/business as they occur.  To ensure such success, it is imperative that projects are not out of date and defunct before they have finished deploying.  What would be the ROI and business case if the project did not align to the needs of the business?  It is essential that both vendor and customer have continuous collaboration and communication to ensure measurable outcomes are achieved.  Constraining both customer and vendor to an initial scope or compliance to a tender that was documented many months or even years before is not practical for either party.  Naturally both parties need to be open and practical to ensure that such an initiative is not abused and a common sense and fair approach is always considered.

Systems integration – the process of bringing together the component subsystems into one system and ensuring that the subsystems function together as a system.

An agile approach to meeting customer requirements involves a blended mix of services, product skills and a methodology to allow the vendor to react more efficiently and effectively to changes and nuances in any organization’s business model.  Collaboration, internally and externally and continuous communication ensures that both parties and the respective individual members are on board and driving the project forward with minimal delay, friction and misunderstanding.  Such a strategy does not mean an unstructured approach but does ensure that the vendor is working effectively to deliver a project on time and on budget, as well as assisting the customer to achieve his goals and ensure that measurable ROI is attained.  This sometimes means organizing projects to deliver tangible results more quickly by undertaking activities in parallel, phasing projects in multiple deliveries, initially focusing on key issues or grouping synergistic aspects, etc.

Likewise it is crucial that product development follows a similar ethos and mentality. Product development needs to be agile enough to adapt to industry changes, customer demand and circumstances such as threats, new technologies etc. If it cannot, then the product becomes extinct and confined to a dusty shelf in a dark server room.  Regular interaction with existing customers, potential customers, industry bodies and third party research bodies, etc., as well as continuous review of new technologies available, ensures that the product is always remaining one step ahead of progression.

As ‘big data’ evolves into ‘smart data’, ‘small data’, ‘real data’ or, as we define it, ‘Deep Data’, the need to integrate, understand and monetize these initiatives means complexity will only increase. The requirements and expectations from corporations and thus naturally from product and projects, will only escalate in size, length and complexity.  Combining a consultative and collaborative engagement model with agile product development allows vendors to compete and meet the ever growing, diversifying needs of data analysis that is demanded today and certainly will be in the future.  More importantly, the common goal of timely project success must be upheld, working in a mutually beneficial partnership approach.