Flywheel Approach
Finding Inspiration in Every Turn
While some practices work well for traditional software development, they are wasteful for building analytics and reporting automation. In a mature data organisation employees can build new models and get necessary insights in minutes or hours, not weeks or months. The future is here, it's just not equally distributed.
Meet The Team
Dmitriy Yaroshenko
Dmitry is a hands-on solutions architect who specializes in and is passionate about data warehousing, cloud analytics, and strategy consulting. For 15+ years, he has successfully enabled businesses throughout financial services, telecom, gaming, insurance, and healthcare industries become data-driven, leveraging the best of technology and engineering practices. He's ready to solve challenges together and bring your business to the next level.
Slava Gagan
Slava is a programme and project manager with over a decade of industry experience and background in product management and data analysis. His core expertise is in leading technology delivery and organisational change for corporate clients, covering the end-to-end cycle for in-house development, vendor management, and integration of off-the-shelf software products.
Slava holds number of professional qualifications such as PMI-PMP, PBA and ACP; PRINCE2; ICP, ICP-BVA;
Karl Naughton
Karl is a business analyst and product owner with over 10 Years experience in the investment banking, risk and IT sectors. Drawing from his wide expertise he has successfully led major delivery programmes for a number of Tier 1 investment banks delivering first-class Business Intelligence solutions. He specializes in business analytics and process automation transformation for enterprise clients.
Let us start with what we do differently
-
We do not have development teams - we do not waste time on internal handover, our consultants work directly with business stakeholders and are individually capable for structuring objectives, requirements, building tools, testing and coordinating adoption.
​
-
We do not run scrum sprints or other delivery iterations - we strive to a lean single piece flow from initiation to production and use Kanban to manage work queues.
​
-
We do not do big design upfront - we will agree objectives and target operating model, but will keep the solution flexible to evolve as we work together. We do not want to waste those good ideas created in collaboration as understanding of possibilities evolve.
Initiation
We start with Why. We work with our clients to refine and quantify objectives they can achieve from reporting and analytics automation. We outline current state with relevant opportunities, barriers and constraints related to people, processes and technology. Afterwards we agree a target operating model, and build a roadmap to achieve it. Scale ranges from a single report to a company wide rollout of analytics with multiple use cases.
​​
Once we agreed what good looks like we progress with time and cost estimates. Once baselined we hold a periodic review to monitor scope, cost and timelines and make any necessary adjustments.
Delivery
We prefer to work alongside the business team, unless client wants to fully outsource the work. We ask clients to nominate several user champions who will help us with defining specific logic and will review results as we progress. This way we can get the most out of collaboration.
Based on the identified objectives and roadmap we split necessary work into a backlog of smallest valuable increments and will endeavour to ship them into production as soon as possible. We will set up weekly priority reviews, demo sessions and status reporting to monitor progress.
The delivery team assigned to the project covers everything from defining strategy through implementation to user training and final handover. Usually it is a two- or three- person team to optimise communication and time to market. One person might be enough sometimes but we need to account for a key man dependency.
Testing of the complete work is done in three stages - initially checked by the person who implemented the change against a quality checklist. Second, it is peer reviewed by other flywheel team members. Third, it is checked by a business user champion from a client's side to approve the change. Steps two and three also cover knowledge transfer and ensure business continuity. We will have a testing environment to review the changes with real data so that calculations make sense.
Once the core framework is ready clients can expect changes to be made available several times a day. We will archive each previous version to enable recovery just in case.
Handover and Training
Each change moved to production is reviewed by business users thus supporting initial knowledge transfer. Additionally these changes are covered in a weekly demo and status report to ensure everyone is on the same page. For knowledge retention we will document any logic change and major update so these materials can be integrated into the operating procedures.
We provide generic user training on the functionality early in the engagement cycle and hold more specific How-To and Q&A sessions after each major delivery. Training materials and session recordings are also made available on-demand.
Support
We also provide post engagement support to help our clients run their data and analytics capability.
We maintain a technology platform - update software, manage licences and security settings. We also support existing solutions and dashboards by either making follow up changes or coaching and supervising business team, so they can make updates on their own. Optionally we can provide someone to fully maintain the software and solutions and full daily execution as a managed service.