Business Intelligence
Data analytics is the pursuit of extracting meaning from raw data using specialized computer systems. These systems transform, organize, and model the data to draw conclusions and identify patterns.
Simply put, data analytics lets us compile information from various software like Customer Relationship Management (CRM) or Enterprise Resource Planning (ERP) systems and analyze the data to make informed business decisions related to supply chain planning, inventory management, new product lifecycle management, asset management and more.
There are many benefits of establishing a data analytics mindset for an industrial or manufacturing company including the following:
- Improve supply chain and inventory management efficiencies
- Gain competitive advantage in the marketplace
- Increase revenues while lower costs
- Make informed organizational and operational decisions
- Benefits of outsourcing data analytics
Having an in-house analytics team seems like a no-brainer. In a perfect world, yes. If investing in an in-house data analytics team isn’t currently feasible, consider outsourcing those skills and services to reap the same rewards.
Critical insights with lower cost and risk associated
Outsourcing data analytics activities doesn’t mean you have to sacrifice value or quality as long as you choose to work with a trusted, experience partner. The reality is that this skillset is in high demand and the current talent pool can’t accommodate that demand. A 2011 report from McKinsey Global Institute says by 2018, the United States alone could face a shortage of 140,000 to 190,000 people with deep analytical skills as well as 1.5 million managers and analysts with the know-how to use the analysis of big data to make effective decisions.
If you can still have the critical insights associated with the analysis of data without taking on the associated risk and large investment of building out a complete in-house team, why wouldn’t you?
Not only can you minimize risk and decrease costs, you can be improving efficiency related to supply chain and inventory management. In the long run – and if done properly – this can lead to lower costs and increase revenue.
Show executive leadership benefits without full investment
Building a comprehensive, highly-skilled in-house analytics team is a hefty undertaking – in time and money. Getting executive leadership on board can require a strategic roadmap on its own.
Oftentimes gaining leadership buy-in can be a catch-22. They’ll want unwavering confidence in your plan to commit to it along with strong evidence of the return on investment (ROI). You can compile research and reports on success stories and connect your plan back to the business goals, but it might not be enough. Outsourcing is a great middle ground in which you aren’t asking for the full investment of time and resources, but you’re still expecting positive results for operational efficiencies, reduced costs and increase revenue. Something we can all feel confident about leadership being thrilled with.
Expand internal data analytics capabilities
There are several different ways you can structure a partnership when outsourcing data analytics. For example, if you have in-house analysts they can be focused on developing new, innovative capabilities to gain a competitive advantage in the marketplace while outsourced resources can tackle less strategic (yet still critical) activities like compiling reporting metrics to inform strategic initiatives.
This way, you essentially get the best of both worlds and you don’t necessarily have to give up one for the other. Both team can be working in tandem on parallel tracks to gain momentum and move the needle.
Outsourcing data analytics: A win-win
When you step back and look at each factor involved in having an in-house data analytics team versus outsourcing to a trusted partner, it’s clear that outsourcing these critical business activities can hugely benefit industrial and manufacturing companies. Outsourcing can provide companies with the insights necessary to make informed decisions that can improve efficiencies, freeing up time to be a strategic player in the increasingly competitive marketplace.
Development
Rapid application development (RAD) has been present for some time now in software development. This method was conceived to fix some of the shortfalls that were being experienced with the waterfall model. Rapid application development is specifically suited for developing software that conforms to user requirements. The development process is suited for adaptability to accommodate new information that might be gained during the project’s lifetime.
RAD is one of the popular methods used in agile software development. The agile method uses an iterative development model where the developers release a new improved version of the working software after a while. The method allows for the seamless evolution of software to accommodate user input and emerging trends. It is especially popular with web portal and mobile detection applications. Burcamp provides application development with Infor Mongoose for web portals and web content management with Adobe Business Catalyst. Burcamp can create customized web portals or enhancements to the CloudSuite. This allows for additional enrichments to the operations with rapid application development as the methodology. We can also create web based portals with a CRM using Adobe Business Catalyst.
Opportunities
Rapid Application Development (RAD)
Customized Web Portals
Customized Web Applications
Rapid application development has some advantages as that include:
Fast user feedback: Getting constructive user feedback is important in any development project. The RAD approach is designed to incorporate user feedback in the most crucial phases of the development process. The constant feedback is gotten through the many iterations and prototypes.
Measurable progress: The development process involves using iterations and prototypes which can be used to gauge the progress made on the project. This form of segmentation can, therefore, be used to plan schedules and manage budgets accurately.
Adaptability: The development process in RAD is designed for flexibility to incorporate new suggestions and user inputs. Therefore, significant changes in the requirements and system design can easily be integrated into the software during its development.
Early systems integration: the use of prototypes allows for system integrations to be done early in the development cycle. This is unlike in the waterfall model where the systems integration is done towards the end of the project. With RAD the early systems integration allows the developers to identify and fix critical errors in the system as early on.
Compartmentalization of system components: RAD uses independent and functional components that are later integrated to form the entire system. These components are useful in the iterative process since they enable easy modification. This practice is similar to the use of objects in object-oriented programming. The independent components are tested independently and hence reduce the time taken in the testing phase. They can also be reused in other projects.
