Data optimization is about generating value from your data and using it to drive revenue growth. In terms of return on investment (ROI), the most lucrative targets are sales, service provision, and marketing.
This is more than using data to find money under the sofa cushions with operational efficiencies. By generating insights about your customers’ habits and patterns, data optimization helps your business attain agility and market knowledge, both of which allow you to outmaneuver the competition and gain a top-line advantage.
The biggest problem with data is the amount of unstructured and redundant information you store. While this data may be necessary for the operation of underlying systems, you need to filter through this noise to extract insights that benefit your business.
This is where data analytics comes in. New cloud-native technologies allow for real-time access to the data that matters. These capabilities can be personalized at the department-level, presenting relevant data to your sales, service, and marketing teams to help them filter out the noise. The result is more relevant insights, with the bonus of better data compliance and security.
Using sales and marketing as an example, these insights can work synergistically to drive revenue by strategically targeting your customer base. Real-time marketing insights will allow you to discover the most lucrative and willing customers for your products, making it possible to capture your real customer base while avoiding financial waste on mass marketing initiatives that seldom generate results.
Next, real-time sales analytics can be incorporated into your website. You can track customer browsing habits and generate customer profiles so that you are aware of their buying intentions.
When monitoring customer engagement, you can retain interest during live chat sessions by redirecting customers from chatbots to sales representatives. This adds a human touch that increases the likelihood of customers finalizing their purchases.
Finally, a discounted sale is arguably better than a lost sale. The strategic use of one-off discounts could land you a successful transaction, either via flash sales on your website or follow-up email marketing pushes after a webpage visit.
This is all fueled by data and real-time analytics, following sales and marketing psychology to retain interest and increase the value proposition to customers who are “on the fence.”
While key stakeholders certainly have knowledge and expertise in their field, many enterprises are now prioritizing decision-making based on data rather than intuition or educated opinions. This involves moving away from guesswork and towards data-driven, objective decision making at the business level.
Culturally, this is called the “highest-paid persons opinion” or HiPPO. By moving away from HiPPO to data-driven decisions, you remove both emotion and opinion from the decision-making process, allowing you to remain hyper-focused on your customers and market trends. This is what drives revenues: catering to customer needs and outmaneuvering your industry competitors.
In short, faster decision-making and cycle times are only beneficial when the decisions themselves are good, making data optimization incredibly important.
Internal operations that should be targeted with data optimization include human resources, enterprise resource planning (ERP) and supply chain management (SCM), and employee engagement.
With HR, data metrics like revenue per employee, performance versus potential, and workforce engagement are critical in driving revenue growth. At the department-level, this allows you to determine the efficiency of your workforce and use this data to target employee productivity and maximize your HR return on investment. Here, data optimization involves leveraging pre-existing information for these purposes while also discovering ways of expanding the breadth of HR data collection and analysis.
Under ERP and SCM, you have inventory management, internal purchasing, and production planning. Enterprise resource planning is only of benefit when the master data source is of high-quality. In this case, data optimization comes in the form of data clean-up and governance, along with the enabling of real-time analytics. Using inventory management as an example, real-time analytics would enable just-in-time (JIT) purchase orders, getting enough stock to cover forecasted sales while minimizing overstocking to smoothen cash flow.
Finally, employee engagement can be significantly improved with data optimization. This HBS.edu story illustrates how higher engagement can reduce absences by 37% and improve productivity by 30%. One estimate shows that a 1% increase in engagement leads to a 0.6% revenue improvement and a 58% reduction in churn costs. By generating contextualized engagement insights relevant to your industry, this means you can drive positive employee impacts that will increase productivity and revenue.
Trianz enables digital transformations through effective strategies and excellence in execution. Collaborating with business and technology leaders, we help formulate and execute operational strategies to achieve intended business outcomes by bringing the best of consulting, technology experiences and execution models.
Powered by knowledge, research, and perspectives, we enable clients to transform their business ecosystems and achieve superior performance by leveraging infrastructure, cloud, analytics, digital, and security paradigms.
Finding Hidden Patterns and Correlations Innovative technologies such as artificial intelligence (AI), machine learning (ML) and natural language processing (NLP) are transforming the way we approach data analytics. AI, ML and NLP are categorized under the umbrella term of “cognitive analytics,” which is an approach that leverages human-like computer intelligence to identify hidden patterns and correlations in data.Explore
What Is an SQL Query Engine? SQL query engine architecture was designed to allow users to query a variety of data sources within a single query. While early SQL-based query engines such as Apache Hive allowed analysts to cut through the clutter of analytical data, they found running SQL analytics on multi-petabyte data warehouses to be a time-intensive process that was difficult to visualize and hard to scale.Explore
The Cloud is the Key to Transformation Success… Transitioning your applications to the cloud is undeniably a critical factor to a successful digital transformation endeavor. It’s more than just a lift-and-shift, however. Let’s explore several things that you need to consider before migrating your applications to the cloud, including: Readiness of your application portfolio Where to begin – the right business case and migration strategy Technology requirements and considerationsExplore
Application Modernization at Speed and Scale Enterprises are pursuing greater application scalability, cost efficiency, and standardization with containerization and virtualization platforms. So, what’s the difference? Containers are a type of virtualization technology that allows users to run multiple operating systems inside a single instance of an OS. They are lightweight and portable, making them ideal for running applications across different platforms.Explore