D E L I V E R Y P L A N

Transcription

1 D E L I V E R Y P L A N Building Data Science Solutions

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3 DATA SCIENCE. DELIVERED. The data science revolution is here. Businesses worldwide are creating competitive advantage by using machine learning and advanced analytics to optimise the operational efficiency of their organisation and deliver additional value to customers. It's often thought that you need to invest huge amounts of time and money into building a team with a very niche skillset before you can start doing data science. We can show you a better way. How we can help We make data science accessible to every business by delivering full solutions, tailored to your specific requirements. We don't just do analysis - we build and deploy data-driven services that generate measurable value. Our delivery plan is at the heart of this process, ensuring your project is delivered to the highest quality and is fully aligned to your business objectives. 1

4 DELIVERY PLAN Our established delivery plan takes your project from idea to deployment in six simple steps: IDEATION PIPELINING VALIDATION MODELLING PROPOSAL DEPLOYMENT Steps 1-3 are our discovery phase, during which we develop a deeper understanding of your business, competitive landscape and current data capabilities. Example projects We deliver data science solutions that solve a variety of business problems. Below are some of our most popular solutions - the full portfolio is available at BEHAVIOURAL SEGMENTATION IMAGE RECOGNITION RECOMMENDATION ENGINE CHURN PREDICTION PRICE OPTIMISATION DASHBOARDS 2

5 1. I D E A T I O N If you don't have a specific project in mind, we establish where data science can add the most value Our approach We know that data science can transform businesses and add serious value to your product or service. When it comes to data science, we encourage you to dream big. In a initial workshop or call, we engage with your key stakeholders to understand your business problems and suggest relevant data science projects that would a serve as a solution, along with broad pricing guidelines. Time required 1 session Outcomes Introduction to key stakeholders and business objectives Establish existing analytical capabilities Generation of ideas for future data science projects that would add value 2 3

6 2. V A L I D A T I O N We verify that the data you collect is sufficient to deliver the proposed data science project Our approach There's no data science without data. We'll meet with the team that manages your data internally to validate the idea against the following criteria: Accessibility Where is the data stored and how can it be accessed? Validity Is the necessary data being captured? Quantity Is there enough data to run the project? Quality How much data cleansing is required? With a deeper understanding of your data, we can tailor our proposal to your unique requirements. Time required 1 session Outcomes Validated data samples An approach to accessing your data (i.e. VPN, database logins, flat files, cloud storage bucket) An understanding of your existing data architecture 2 4

7 3. P R O P O S A L Our proposal is a document that explains the project requirements, process and deliverables in detail. Our approach We divide the delivery process into phases, each with a clear goal and timeline dependent on our previous validation of your data. We describe the dedicated resource that will be allocated to your project and provide a full specification for each deliverable, including details on tooling, data pipelining and deployment architecture. Our proposal will ensure you have all the necessary information that you need to make an informed decision, including pricing, review and update points and expected delivery date. Turnaround time 2 days Outcomes Specification for the project scope and deliverables A detailed timeline of the project process and delivery plan A fixed-price or day-rate quote for the project 2 5

8 4. P I P E L I N I N G We work with you to set up secure access to your data and begin preparing your data for modelling. Our approach We build your data science solution on solid foundations. This means ensuring that the necessary data cleansing and transformation scripts are in place for the modelling to be accurate and deployable. As you would expect, we take the security of your data very seriously. Any data we take off-site is stored in our secure, IPrestricted UK based cloud. To further mitigate risk, we work with anonymised data where possible. We write ETL scripts in SQL and Python to get your data to a state where it can be used to train machine learning or optimisation models Time required 1-2 weeks Outcomes Secure access to your data Scripts for data cleansing, transformation and pipelining 2 6

9 5. MODELLING This core part of the project focuses on iteratively building the solution to deliver measurable value Our approach We rapidly build an end-to-end MVP of your solution to establish an initial baseline from which future iterations of work can be built. Whether we're building a predictive model, a fine-tuned optimisation or an insightful visualisation, the following attributes always apply: Measurable Scalable Embedded Iterable We always ensure that the impact of our work is measurable - whether through predictive accuracy or a KPI Our solutions are built to scale with your business - they are designed with future growth in mind We're already thinking about the deployment of the solution, ensuring a smooth transition into BAU We build solutions in sprints, reporting back on progress regularly Time required 2-6 weeks Outcomes The solution, ready to be deployed (e.g. a predictive model, customer segmentation or price optimisation) The code base, usually in Python or R that builds the solution A fully documented analysis of the solution (e.g. accuracy, runtimes, key insight) 27

10 6. D E P L O Y M E N T This final stage deploys the solution into your business and sets up a process to monitor the system Our approach We take the time to ensure your data science solution is fully embedded into your business. We typically deploy solutions to a cloud-based architecture, dependent on your specific requirements. This also includes setting up reports and dashboards to monitor the solution. We run training sessions to fully handover the solution. We can also offer a managed service where we take care of the solution maintenance, for an agreed monthly fee. Time required 1-3 weeks Outcomes Deployment to your on-premises servers, or a cloud based architecture Reports and dashboards set up to monitor the solution for key metrics (e.g. accuracy, runtimes) Training sessions for key stakeholders 2 8

11 N E X T S T E P S We are looking forward to further discussing the process set out in this document with you and establishing how we can deliver a data science solution that generates real value for your business. If you would like to learn more about any aspect of our delivery plan, or have a particular data science project that you would like to discuss with us, just get in touch through the points of contact below. Points of contact ROSS WITESZCZAK Partner ross@applied-data.science DAVID FOSTER Partner david@applied-data.science

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