Eight Ways Data Science Improves Your Business.
Predict, forecast, automate, and personalize …
This is just some of the potential that lies within your business data. Here we highlight eight key areas where applying data science to your business provides both short-term ROI and long-term competitive advantage.
1) Fortify your supply chain.
Advancements in graph data science have made it easier to create a digital twin of your supply chain. This virtual model allows you to stress test your system under a wide variety of real-world conditions so that you’re prepared for any potential disruption. Unanticipated cost changes? No problem. Change in regulatory or compliance standards? You’re prepared. Supplier instability? You have it handled. With your “graph connected” supply chain data, you can also quickly and automatically identify alternate paths when a breakdown occurs, so that your business does not miss a beat.
2) Improve engagment with customers and prospects.
With data-driven “prescriptive marketing”, you can automatically deliver a personalized message or offer to your highest-value prospects, at the exact time they’re most likely to engage. The result is a ‘next-level’ improvement in lead capture, conversion, and retention. Machine learning algorithms and A.I. can recognize the deep and complex patterns within your customer data to inform the “next best action” with the highest probability of success, allowing you to significantly improve your marketing ROI.
3) Reduce inventory while improving service levels.
It’s a daunting challenge, but with a detailed and accurate sales forecast, you can more closely align your inventory with future demand. A data scientist has powerful tools at her disposal to model time-series data, such as your sales transactions. By predicting when and where sales will occur, your business can not only better align resources with demand, but also more accurately forecast cash flows, optimize staffing levels, maximize production capacity, and place your incentives in markets where they will have the greatest impact.
4) Motivate and excite your employees.
Your employees are your company’s greatest asset. Forward-thinking firms are using data to better understand the key drivers of morale and productivity. Machine learning can predict the right tools and information that your team needs to stay motivated, productive, and feeling appreciated. Additionally, data can reveal critical insights into specific skill gaps and training needs. Finally, data scientists can build models that predict employee attrition, enabling your business to reduce the loss of talented employees.
5) Maximize margins without losing sales.
Congratulations! You made the sale. But could you have charged more? Did you provide a discount to a customer that would have purchased anyway? This is one of the most immediate impacts a data scientist can have on your bottom line. By modeling the maximum “willingness to pay” for a specific customer and product segment, you will know exactly when and where a discount is needed, and the maximum price level you can charge without negatively impacting profitability. And, are you taking full advantage of upselling and cross-selling opportunities to earn a higher share of your customer’s wallet? Customized “product recommendation engines” automatically suggest additional products that will be most interesting to a specific customer.
6) Retain your loyal, high-value customers.
If your customer data is siloed and disconnected, it’s impossible to get a complete view of your customer’s experience. Innovative businesses have taken a “Customer 360” approach, which integrates customer data streams into a consolidated view for sales, marketing, customer service, and operations. Deep and complex patterns within your customer engagement are then analyzed to predict whether a customer will defect so that your team can take appropriate action ahead of time.
7) Detect production issues before they arise.
The plant floor is your company’s profit-generating machine. In addition to products, it’s also producing massive amounts of data that can be leveraged to drive further improvements in productivity. In manufacturing, detecting even the smallest anomaly in your streaming data can provide the earliest possible indication of a larger problem, such as equipment failures, quality issues, and supplier concerns that could cause significant business disruption.
8) Automate repetitive business processes.
When you have people doing “machine work,” it’s not only inefficient, it can frustrate your valuable employees and cause deep-seated morale issues. Robotic Process Automation (RPA) frees your employees, enabling them to apply their innate skills to creativity to solve problems, innovate new business ideas, and build meaningful relationships with others. If they’re stuck doing “automatable tasks,” then you aren’t maximizing the positive impact they can have on your bottom line. Skilled data scientists can unpack your business processes to find key areas where generating accurate predictions can enable automation. Examples of processes with high automation potential include paying invoices, replenishing inventory, updating CRM data, generating reports, onboarding new employees, and conducting audits (to name just a few).