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Analytics Value Chain

Analytics is a vast discipline covering data structure, computer science, statistics and business subject acumen.


The typical journey for an team to adopt data and analytics-driven insights looks like the following. There are two ways to view analytics services, one way to is to look at the technicality of the quantitative analysis. The other is to look at the dimensions and specific use cases that are challenge focused. See the two dimensions below.



Use Cases

Analytics Services: Technically Driven



Whether it’s employee retention, product unit sales, or customer churn analysis, get reports delivered to you on time, so you can get your hands dirty and start making insightful decisions.


Metrics Aggregation and Manipulation:

Performing automation internally and calculating complex metrics by pulling multiple data sources into a single summary table.



Exploring business opportunities by transforming data and statistical outputs into business insights. Not sure how to act on churn rates, or customer lifetime value data? Let us help!



Taking data to the next level by applying machine learning and statistical forecasting models. Gain insights into the future, so you can be prepared.



Taking objective and constraint functions to optimize for marketing spend, scheduling, load balancing and machine efficiency. AAARL uses advanced techniques to dramatically boost ROI.


Business Consultation :

Business driven analysts can provide actionable recommendations based on your business use cases in combination with our own internal data.

Analytics Services: Challenge Driven


Management Analytics:

Real time data visualization with cost, revenue, profit and employee data to help managers allocate resources and asses the health of the organization.


People and Human Resource Analytics:

Utilizing metrics related to workforce demographic, recruiting, retention, performance, and health and safety, be more proactive in problem solving, and spend less time dealing with transactional activities.


Inventory Analytics:

Manage inventory levels with analytical accuracy. Forecast future stock requirements to avoid stockouts or overstocking, and see which single/combination of items are performing best..


Financial Analytics:

With automation, get to the complete picture, quicker. Utilizing software, your data can be pulled from multiple sources and consolidated into a format that works best for you. Additionally, use predictive analytics with historical data to forecast for future gaps.


Operations Analytics:

Track important metrics like service time, machine efficiency, and energy consumption to understand the health of key assets, and optimize for higher utilization rates.


IT Analytics:

Optimize IT resources by understanding and predicting where IT requests may come from. Using descriptive and predictive analytics, better prepare staff to balance loads and allocate resources optimally.


Customer Analytics:

Understand your customers. Familiarize yourself with their interactions with your products or services, reduce purchasing friction by optimizing your value chain based on detailed customer profiling, and explore valuable new business opportunities only possible through the use of analysis reporting such as churn alerts and customer segment analysis.


Transaction Analytics:

Combining customer data with recency, frequency and monetary values of transactions, understand purchasing behaviour and which sales or marketing channel has the highest impact on specific customers.


Social Media Analytics:

Decrease the distance between organization and customer with social media and web presence analysis. Discover insights such as which clients are key influencers on social media and what the tone of their posts are. Additionally, receive monthly reporting on your own social media performance.


Marketing Analytics:

With monthly reporting using advanced analytics to understand customers, transactions, and marketing channel performance, make decisions to increase ROI on marketing spend with more information than ever before.


Pricing Analytics:

Pricing elasticity on products is a key question for a variety of industries. Optimize profits by testing various price points using statistical methodologies.


Sales Analytics:

Which sales channel is performing the best? Perform analysis on internal sales and external competition to get a 360 degree picture, providing decision makers the knowledge of which lever to pull on to improve results.


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