“If you do not know how to ask the right question, you get nothing.”
W. Edwards Deming – pioneer of Quality Control
“On average, people should be more skeptical when they see numbers. They should be more willing to play around with the data themselves.”
Nate Silver – statistician & editor-in-chief of FiveThirtyEight
Why Analytics is important
Analytics is a KEY component of business success today. Conversely, an inability to analyze data of all kinds – even worse, not having the necessary data available for analysis can have severe consequences for an organization. To leverage new sources and ever increasing volumes of data, analytics technology is also developing rapidly. Major software companies are investing enormously to boost their analytics capabilities. For example, Microsoft are currently releasing almost monthly updates to a key component of their analytics solution – Power BI. Developments in Machine Learning/ Artificial Intelligence will only hasten this trend.
Today more and more analytics applications are being developed outside the traditional IT unit. While often delivering quicker results this approach does have downsides in terms of ensuring “a single version of the truth” and frequently caused hidden IT costs. The task of acquiring data, building databases & Data Warehouses and ensuring data consistency are still tasks beyond the skillset of user departments. Failing to provision data correctly usually leads to errors, confusion and frustration.
How we can assist you
We bring a proven approach to assisting you, based on our many years of IT consulting experience in designing and implementing analytics systems. Our approach includes the following worksteps:
- Review your existing approaches to providing analytics including: database, analytics & reporting systems, interfaces to data sources etc.
- Conduct data analysis and reporting needs assessments. This typically involves interviewing people thoughtout all levels of the organization. Analytics can be operational (e.g. supporting real-time business processes such as identifying security breaches), analysis of historic data or predictive in nature.
- Determine required data analysis frequencies. This can range from real-time to periodic (hourly/ daily/ weekly/ monthly etc.) which in turn impacts the type of technology architecture required.
- Develop a Gap Analysis between current and desired analytics capabilities and a roadmap to close this gap.
- Select specific technology components to implement required analytics functionality.
- Install and test these components.
- Design and develop interfaces between systems, data structures/ Databases, Data Warehouses, reports, analytics applications/ dashboards etc. We focus on designing effective user interfaces (UI) for minimum clutter and maximum information content. In particular we follow best practice UI design principles based on guidelines developed by Prof. Hichert of the IBCS (International Business Communication Standards) Institute (see Example Guidelines) and Stephen Few.
- Train analytics users throughout the organization.
In addition, we also provide Project Management expertise and resources for data-related projects on an advisory or hands-on capacity. We work with both traditional “waterfall” PM methodologies as well as newer Agile approaches, especially SCRUM.