Big data consulting

When considering big data consulting services, you might be thinking:

I understand that big data systems can handle massive volumes of information and uncover complex hidden patterns in real time, but how can we measure their actual impact on our bottom line?

This is a valid concern, as a big data project can be complex and resource-intensive. But when done right with a big data consulting firm, a big data project can transform your business. ROI in big data isn’t just about cost savings. It can:

• lead to new revenue streams by identifying untapped market opportunities
• increase customer satisfaction through personalized experiences powered by data insights
• speed up your time to market by optimizing your supply chain and production processes
• sharpen your decision-making capabilities by providing real-time, actionable business intelligence

Let’s consider an example: a retail chain looking to optimize its inventory management and reduce operational costs. The retail chain approached Yalantis for expert guidance on leveraging big data to achieve these goals. Here’s how Yalantis big data consultants apply our ROI-focused methodology:

Step #1. Strategic assessment and goal setting

We conduct in-depth interviews with stakeholders to understand their pain points and objectives. For our retail client, we defined the goal of reducing overstock by 20% while maintaining a 98% in-stock rate for high-demand items.

Step #2. Data landscape analysis

Our big data consultants audit existing data sources, data types (structured, semi-structured, and unstructured data), and systems, identifying gaps and opportunities. We mapped out the retail client’s current inventory data flow, point-of-sale systems, and supply chain data.

Step #3. Solution architecture design

We create a blueprint for the big data solution, considering scalability and future needs. For the retailer, we designed a cloud-based data lake architecture with real-time data ingestion capabilities.

Step #4. Proof of concept (PoC) design

We design a small-scale implementation plan to demonstrate potential value. For the retailer, we outlined a pilot program for one region, detailing how predictive analytics for demand forecasting could be implemented using tools like Apache Spark and Python.

Step #5. Technology stack recommendations and implementation roadmap

Based on the PoC design and the client’s specific needs, we suggest the most suitable technologies and provide a detailed implementation roadmap. For our client, we recommended Tableau for visualization and Apache Kafka for real-time data streaming, along with a phased implementation plan that prioritizes high-impact, low-risk projects. This included a timeline for rolling out the solution across all regions and product categories.

Step #6. KPI framework development

We help establish key performance indicators and set up tracking mechanisms. For our retail client, we implemented Grafana dashboards to monitor inventory levels, turnover rates, and prediction accuracy in real time.

Step #7. ROI projection and tracking

We provide detailed ROI projections and ongoing tracking. For the retailer, we set up automated monthly reports showing reduced carrying costs, improved cash flow, and increased sales from better stock availability.

Step #8. Knowledge transfer and training

We ensure your team can maintain and leverage the new systems. This includes conducting workshops on data interpretation, providing hands-on training with the new inventory management system, and creating a comprehensive wiki for ongoing reference.

How long does it take to see results from big data consulting?

You can typically start seeing results within 4–8 weeks, but the overall timeline for reaping value from big data consulting services depends on several factors:

Quick wins and long-term value

Quick wins (1–4 weeks). Early in the big data consulting process, we focus on delivering rapid insights and improvements. Results at this stage often include:

• A comprehensive big data and analytics strategy roadmap tailored to your business objectives, which lets you prioritize initiatives and effectively allocate resources
• Identification of high-impact, low-effort data initiatives for immediate implementation: for example, optimizing customer segmentation, which could increase marketing ROI
• Preliminary data governance recommendations to improve data quality and accessibility, reducing data-related errors and saving hours of manual data cleaning each week
• Proof of concept implementations demonstrating the potential of selected big data technologies, such as a predictive maintenance model that could reduce equipment downtime
• Initial ROI projections based on pilot projects and industry benchmarks (for example, projecting a 15% reduction in inventory costs through improved demand forecasting, or a 10% increase in customer retention through personalized marketing)
• Skills gap analysis and tailored training plans for your team, such as identifying the need for data visualization expertise (data visualization consulting services) and creating a 6-week intensive course for your analysts

Long-term value (4–12+ months). The full potential of big data consulting services unfolds over time. It can include:

• Implementing a company-wide data literacy program, resulting in employees confidently using data in their daily decision-making
• Developing advanced predictive models that improve forecast accuracy, leading to better resource allocation and increased profitability
• Creating new data products or services, potentially opening up additional revenue streams worth 5–10% of your current annual revenue
• Establishing a data-driven product development process that reduces the time to market for new offerings

Factors affecting the timeline for seeing big data consulting results

The timeline for seeing results from big data consulting firms varies. You’ll likely see some quick wins in the first few weeks, but the full impact of these initiatives grows over time. As you collect and analyze more data, and as your team gets comfortable with new tools and processes, you’ll see increasingly valuable insights and improvements.

To keep things on track, we use tools like Tableau dashboards to monitor progress and get quick feedback. This helps maintain momentum and stakeholder buy-in while working towards larger long-term goals like achieving full data integration across all business units and implementing data science with advanced artificial intelligence (AI) and machine learning capabilities for predictive analytics and machine learning solutions.

Here are the main factors that influence how quickly you’ll see results:

Factor #1. Project scope and complexity

• Smaller projects: For focused tasks like setting up a new sales dashboard, you might see improvements in decision-making speed within the first month.
• Larger transformations: Big changes, like revamping your entire data system, can take several months before you see major impacts. Then, for example, you might see an increase in operational efficiency from automated reporting.

Factor #2. Your current data setup

If you already have solid data systems: We can build on what you have, potentially delivering quick insights within weeks using advanced analytics services on your existing data assets.
If we need to clean up your data first: Our data engineering process usually takes 2–3 weeks. Then, we can start generating initial insights and building more complex analytics models, typically seeing the first results within 1–2 months.

Factor #3. Organizational alignment and adoption

• Strong executive support: Committed leadership speeds up adoption of new data tools and practices by prioritizing resources, removing obstacles, and encouraging data use. This can lead to organization-wide results within 4–6 months, such as an increase in data-driven decisions across departments.
• Cultural shift: Building a truly data-driven culture across your entire organization can take 6–12 months, but it’s worth it. You’ll see smarter choices at all levels of your business.

Our approach is straightforward: we make sure you quickly see benefits of big data consulting services, but we also think about how to keep those benefits coming year after year. It’s about making your investment in big data pay off now and in the future.