Embracing a Growth Mindset: Your Key to Analytics Success
03 Mar
In a world where data is paramount, don’t you agree that insights are invaluable? And with the right mindset you bring to the table will truly set you apart!
Enter the growth mindset – a powerful approach that can propel you and your business forward in your analytics journey like never before.
So, what exactly is a growth mindset? Simply put, it’s the belief that your abilities and intelligence can be developed over time through dedication and hard work. It’s about embracing challenges, being persistent when faced with setbacks, and putting continuous efforts to master the art of problem-solving.
In analytics, a growth mindset is your secret asset. Instead of being intimidated by complex data sets or unfamiliar techniques, you see them as opportunities to learn and grow. You welcome feedback, both positive and constructive, knowing that it will only help you and your business to improve.
We must understand that failures aren’t roadblocks – they’re stepping stones on the path to success. When you encounter obstacles in your analytics projects, you don’t give up or see them as indicators of your limitations. Instead, you view them as valuable learning experiences that will ultimately make you stronger and more capable.
Moreover, a growth mindset fosters a spirit of collaboration and innovation. You’re not afraid to seek out new ideas or perspectives, knowing that they can lead to breakthrough insights. You’re open to experimenting with different approaches and methodologies, knowing that innovation often arises from trial and error.
So, the next time you sit down to tackle a challenging data or analytical problem, remember the power of a growth mindset. Embrace the journey, learn from your experiences, and watch your business reach new heights!
We are NRoot Labs, specialize in comprehensive BI solutions. As a technology-neutral company, our team of BI consultants excels in delivering business solutions that leverage actionable insights supported by business data. Our commitment to understanding the complexities of business processes enables us to provide enhanced BI solutions for our clients.
Enhancing Business Efficiency : The Synergy Between ERP and BI
23 Jan
In today’s business landscape, the significance of making quick and well-informed decisions cannot be emphasized enough. Be it manufacturing, retail, finance institutes or any other industry, two pivotal technologies that play a crucial role in facilitating data-driven decision-making and operational efficiency are Enterprise Resource Planning (ERP) and Business Intelligence (BI).
The partnership between Enterprise Resource Planning (ERP) and Business Intelligence (BI) is like a well-coordinated orchestra —a subtle yet powerful collaboration that significantly influences overall performance.
While ERP systems are invaluable for managing various aspects of business operations, they have their limitations when it comes to in-depth data analysis. This is where BI software steps in. BI tools are specifically created to go through large sets of data, spot trends, create reports, and offer decision-makers important information in real-time. This ensures a more thorough understanding of the data collected by the ERP system, helping businesses make informed decisions promptly.
Picture ERP as the engine driving your business vehicle, ensuring all components work in tandem. BI, in this scenario, acts as the GPS navigation system, guiding you through the complex terrain of data. It’s not just about having a powerful engine; it’s about knowing where to steer. A comprehensive study by Gartner, spanning industries worldwide, revealed that businesses leveraging both ERP and BI reported a remarkable 35% enhancement in decision-making processes.
The beauty of this collaboration lies in the ability of BI to extract meaningful insights from the ERP’s data repository. It’s the difference between having a library full of books and having a librarian who can guide you to the right ones.
In essence, ERP and BI are the unsung heroes of organizational efficiency. While ERP sets the stage, BI provides the spotlight by turning raw data into valuable insights. It’s a partnership that goes beyond technology, creating a synergy that empowers businesses to navigate the challenges of the modern landscape with precision and foresight.
After all, in the world of business, it’s not just about having the tools; it’s about having the right tools working together harmoniously.
We are NRoot Labs, specialize in comprehensive BI solutions. As a technology-neutral company, our team of BI consultants excels in delivering business solutions that leverage actionable insights supported by business data. Our commitment to understanding the complexities of business processes enables us to provide enhanced BI solutions for our clients.
The Changing Face of the Auto Retail Industry: Adapting to Stay Relevant
03 Nov
The auto retail industry, like many other sectors, is undergoing a rapid transformation driven by technological advancements, changing consumer preferences, and environmental concerns. In this article, we will explore how the auto retail industry is evolving and why building trust with existing customers through analytics is more essential than ever.
The Shift in Industry Landscape
The traditional model of auto retail, where customers visit showrooms and dealerships to purchase vehicles, is slowly losing ground to alternative models. Online marketplaces, direct-to-consumer sales, and ownership of vehicles like subscription-based services/ leasing/ fleet etc are becoming increasingly popular. Customers now have more choices and flexibility than ever before, challenging the traditional dealership-centric. Here is why the shift is happening –
- Digitalization: The internet and mobile technology have made it easier for customers to research, compare, and even purchase vehicles online. This reduces the dependency on physical showrooms.
- Changing Consumer Preferences: Many consumers are seeking more convenience and personalized experiences, which online platforms and direct sales models can offer.
- Clean energy vehicles: The growing awareness of environmental issues and the push for sustainable transportation are driving the demand for electric vehicles and alternative mobility solutions. The government’s active support for these models and technologies is likely to bring about significant changes.
Impact on Customer Retention
With this changing landscape, auto retailers must adapt to retain existing customers. Building trust with these customers is paramount, as it can be more cost-effective than acquiring new ones. Let’s explore additional methods in which insights can deliver value-adds –
- Personalized Customer Experiences: Using data analytics, auto retailers can gather insights into customer preferences, behaviours, and purchase history. This enables them to offer personalized recommendations and experiences, enhancing customer loyalty.
- Preventive Maintenance: Analytics can be used to lock in maintenance revenue ahead in time by customized schemes based on driving patterns, vehicle health check ups thereby retaining customers with attractive lock-in schemes, leading to trust and reliability in the eyes of the customers.
- Feedback Analysis: Customer feedback and reviews can be analyzed to identify areas for improvement. Responding to customer concerns and suggestions can help build trust and demonstrate that the retailer values their input.
NRoot Labs insightful dashboards on UIO (Units in Operation) and NIO (Units Not in Operation) or even a basic customer feedback have assisted auto retailers in refining their after-sales operations & thereby retaining their customers & strategize ways to reacquire former customers.
A prominent automotive dealership that chose our UIO & After Sales Overview dashboard remarked that : “With visibility at our UIO and NIO dashboards & after-sales surveys using Customer Satisfaction Index (CSI) offered us valuable insights into our retention and customer experiences. The informative dashboards built by NRoot Labs enabled us to identify areas for improvement, enhance service quality, and strengthen customer loyalty. By analyzing this data, we were able to customize our offerings, boost customer retention, and maintain a positive reputation in a competitive market.”
The Need for Data Analytics
In the digital age, data is abundant, but it’s only as valuable as the insights extracted from it. Data analytics provides auto retailers with the tools to:
- Understand market trends: It enables retailers to anticipate shifts in consumer preferences and demand. With auto retail analytics, businesses can stay agile and make data-driven decisions to thrive in a rapidly evolving market. This knowledge can be used to tailor marketing and sales strategies as well.
- Optimize Inventory: By analyzing sales trends, retailers can better manage their inventory, reduce obsolete stock and costs.
- Improve Operational Efficiency: Analytics can enhance the efficiency of various operations, from supply chain management to after-sales service, making the business more agile and cost-effective.
In Conclusion The auto retail industry is in the midst of a significant transformation. Dealerships and showrooms may evolve into experience centers, focusing on brand engagement and customer education rather than just sales. The physical presence may continue to serve a purpose, but it will be complemented by online platforms and alternative sales channels. Adapting to change and building trust with existing customers through data analytics is essential for staying ahead of the curve. The key to success lies in understanding and meeting the evolving needs and expectations of the modern consumer.
Data, when harnessed effectively, is the key to navigating this new era in the auto retail industry.
Harness the power of analytics in manufacturing industry!
23 May
By coupling Information & Analytics, every manufacturing unit can adeptly oversee and streamline its diverse functions, including the shop floor, supply chain, sales, and post-sales service. This can be achieved by utilizing the available data to drive productivity and profit through data-driven decision-making programs.
Accelerate Data-driven Smart Operations with NRoot Labs Manufacturing Analytics
Our comprehensive self-service data analytics platform empowers organizations to harness operational data at every stage of the data lifecycle, from the shop floor to the top floor. This enables them to maximize value, minimize risk, and leverage the full potential of their data resources.
Improved Efficiency: Operational analytics helps identify inefficiencies and bottlenecks in manufacturing processes, enabling organizations to optimize resource allocation, reduce waste, and improve overall operational efficiency.
Enhanced Quality and Yield: By analyzing operational data, organizations can identify patterns and trends that impact product quality and yield. This allows for proactive measures to be taken, such as identifying and resolving quality issues in real-time, resulting in improved product quality and higher yield rates.
Faster Problem Resolution: Operational analytics enables timely identification and resolution of production issues by providing real-time insights into the manufacturing processes. This helps minimize downtime, improve equipment maintenance, and reduce the time required to resolve problems, thus enhancing overall productivity.
Optimal Inventory Management: Analytics helps organizations gain better visibility into inventory levels, demand patterns, and supply chain performance. This enables improved inventory management, reducing excess inventory and stockouts, optimizing storage space, and minimizing carrying costs.
Data-Driven Decision Making: Operational analytics provides organizations with actionable insights based on data analysis. This empowers decision-makers to make informed decisions regarding production planning, resource allocation, process improvements, and other critical areas, leading to better operational outcomes.
Predictive Maintenance: By analyzing operational data and equipment performance, organizations can implement predictive maintenance strategies. This helps detect equipment failures or maintenance needs in advance, minimizing unplanned downtime, optimizing maintenance schedules, and improving overall equipment reliability.
Just like how manufacturing industries convert raw materials into valuable finished products, discover how our solution on some of the key Manufacturing analytics drive our customers to achieving efficiency and value-added insights from their raw data! The below infographic helps explain the various analysis:
NRoot Labs is an end-to-end BI solutions provider transforming Data into Valuable Insights for Manufacturing Industry.
How can fill rate analysis help automotive businesses?
15 May
In any retail business a customer demand satisfaction is one of the most important factors to track. Was the needed item available in stock when your customer asked for it? To gain the trust of your retailers, you need to have an accurate fill rate.
Why fill rate?
The most important goal is to fulfil your consumers’ needs and provide them with an unforgettable experience! Good news is you will be able to achieve this with the help of fill rate. Determining this KPI is critical because if it remains low, it could lead to loss of sales, loss of customers, and a poor reputation. And with the accurate statistics at hand, a dealership will become aware of missed opportunities and take steps to manage them immediately.
In an auto dealership, fill rate is the percentage of customer orders that a dealer can ship over a given point of time from the stock without placing backorders or missing a sale. In simple words, it’s an indication of how well you’re able to meet customer demand at any given time.
In order to improvise, auto retailers must ask themselves – “Why are fill rates so low, what is being done about it and what can we do to help ourselves through the challenges posed by low fill rates?”
Let’s break it down!
To understand fill rate better, we must know the difference between service level and fill rate.
Fill rate simply answers one question – Was the client’s desired item in stock today? Whereas service level addresses issues such as how the situation was handled by the retailer. If the desired item was sold out and you were able to convince your customer to ship an alternative item or place a backorder instead. In this condition, your fill rate may take a hit, but your service level may improve as you are able to convince the customer to come back to you. There are chances that you may fulfil your customer’s request, yet their experience with the retailer may be unpleasant as they had to go for an alternative item.
In the broad sense, service level conveys customer satisfaction that can be a positive or a negative one. Whereas one can measure your dealership’s fill rate at any time throughout the year to determine how efficiently supply chain management meets order demands.
So, what is the ultimate fill rate and how do auto dealers improve it? The answer is – the higher the order fill rate, the better!
NRoot Labs is an end-to-end BI solutions provider transforming Data into Valuable Insights for Automotive Dealerships. To know more contact – sales@nrootlabs.com
Automotive Series: Top 6 Metrics To Track For Your Inventory Management
16 Apr
Why is inventory management crucial for an auto retailer?
Inventory can play a substantial role in the health of a business—having too much can cause problems, as can having too little. With an inventory management analytics, automotive retailers can get visibility into items across all channels, ensuring the right items are available, at the right time, in the right place.
Let’s discuss the key factors that you should be tracking –
Cost to market:
Effective dealers minimize costs to make inventory procurement efficient. Your dealership can make the most of its inventory by narrowing (not eliminating) costs and bringing in high-value inventory.
Inventory Turn Rate:
This is the overall in-stock inventory of your dealership versus your team’s monthly sales. The effectiveness of the dealership departments is key to increasing your dealership’s turn rate. Faster turn rates on fresh inventory will improve your GMROI across dealership.
Gross Margin Return On Investment (GMROI):
The GMROI is a useful measure as it tells the average amount that the inventory returns after its costs. A ratio higher than one means the dealership is selling the stock for more than it costs to acquire it and shows that the business has a good balance between its sales, margin, and cost of inventory.
Average Days to Sell Inventory (DSI):
This measures how long it takes for your dealership to turn its inventory into sales. When the measure is high, it may indicate that your inventory movement is inefficient.
Vehicle Demand versus Inventory:
Every vehicle has a window for maximizing its return on investment. Your dealership can determine the best-selling window by tracking a vehicle’s market value and demand. This information should also help you with your appraisal and inventory sourcing.
Mechanical And Cosmetic Reconditioning Time:
Auto dealers need to keep the inventory fresh and moving in an economical timeline. The longer a car spends in the shop, the lesser time it’s out for sale. Efficient dealers solve reconditioning delays.
NRoot Labs is an end-to-end BI solutions provider transforming Data into Valuable Insights for Automotive Dealerships. To know more contact – sales@nrootlabs.com
Automotive Series: Top 5 Metrics To Evaluate your Vehicle Lead Management
09 Apr
If you can’t measure it, you can’t improve it.
As an auto dealer, you must create a digital sales funnel to evaluate and assess the success of your sales and marketing teams. Measuring the vehicle leads serves as a guide to new revenue opportunities to grow your business. It’s vital to know your performance indicators that explain which scheme attracted more inquiries or which campaign converted test drives to sales.
Below, you’ll find five important vehicle lead management KPIs that will help you measure your business performance and boost your growth rate.
Let’s get started…
Number of Inquiries by source and contribution %:
helps understand which strategy worked best and by what percentage. This will in turn help direct the right resources towards the right scheme
Conversion % at every stage of funnel:
helps understand a prospect lifecycle and how many move to different stages down the funnel
Cost per Qualified Lead:
enables sales and marketing teams to set their sales goals, calculate potential ROI, and determine advertising budgets
Lost Sale Ratio:
explains missed sales opportunities that resulted by not fulfilling the demand of a customer request be it a specific product, feature, a discount amount, or even inconsistent customer experience.
Trade in Ratio:
assesses the various strategies applied by used-car evaluators to attract customers to opt for trade-in schemes, especially when used car business is driven by supply
Over the long term, this will help the top sales and marketing team to analyze the data and deploy resources in a smart way to maximize lead management and better conversions!
NRoot Labs is an end-to-end BI solutions provider transforming Data into Valuable Insights for Automotive Dealerships. To know more contact – sales@nrootlabs.com
Automotive Series: Top 6 Metrics To Evaluate Your Vehicle Sales
21 Mar
Financial KPIs That Drive Successful Vehicle Sales Strategy
Tracking and measuring the performance indicators of your business is key to measure the successes and failures of your business and to make critical adjustments in your execution so you can achieve your strategic goals.
In this post, we’ll outline 6 most fundamental Financial KPIs that will help you keep close tabs on your vehicle sales performance and boost your long term success.
Facing an uncertain and disruptive future, how can automotive executives prepare? Which KPIs can chart the roadmap for the future?
Vehicle Average Selling Price(ASP)
The term average selling price refers to the price at which a certain group of goods or services are typically sold. Auto dealers can tweak this KPI to position themselves by finding a balance in pricing based on the market and their break-even point. This can also serve as a benchmark for entities who want to set a price for their product or service. It can be an effective way for sales executives to compare how various accessories, service contracts etc. are sold and their discounting strategy. Finally, it translates what the business thinks is the best and the most profitable route.
Gross Profit Margin Ratio:
Gross profit margin is a profitability ratio that compares the gross margin of a company to its revenue. In an auto dealership it means how much profit a dealer makes after paying off their Cost of Sales (COS). Auto dealers need to competitively increase their GP ratio by marking up goods to sell at a higher rate. Another way is through Supplier Support to aid push inventory with suitable discount percentage to attract customers. This is a win-win model for both the OEMs and the dealerships as they make a sale and not have an aging inventory.
Net Profit Margin Ratio:
A high net profit margin in an auto dealership means how effectively can they control their overhead costs and/or provide products or services at a price significantly higher than the cost. This can be achieved by efficient management by support teams, low operating costs and robust pricing strategies.
Average Gross Profit Ratio:
Average Gross Profit is a profitability ratio used to calculate the percentage of profit company makes from its total revenue for a unit of vehicle sold. For an auto dealer it means how much gross profit they made per vehicle.
Fixed Overhead Absorption:
Fixed absorption is the measure derived from operational costs that are covered for every unit of product sold.
Used-to-New Ratio:
If an auto dealer achieves 1:1 used:new vehicle sale then they have done a “good” job, and if they have 1.25:1 (or more) ratio indicates a “great” job. This helps release pressure on the new-vehicle department for overall dealership profitability.
NRoot Labs is an end-to-end BI solutions provider transforming Data into Valuable Insights for Automotive Dealerships. To know more contact – sales@nrootlabs.com
Transforming Data into Value for a leading Automotive Dealer
27 Dec
Client
An authorized dealer of leading automobile brands such as Nissan, Infiniti, Renault, Great Wall and Dongfeng Motors, Ford and Lincoln. Being synonymous with quality automobiles in the GCC, the client has consistently set the standards for excellence, not only in sales, service and spare parts but also in customer service and satisfaction.
Background
The client was looking to support their growing business by transforming the IT operations and streamlining data management while improving accuracy. They were seeking a holistic view of their business to support their decision making.
Challenges
- The IT landscape was not aligned to business value and outcomes.
- The business users face the challenge of reporting out of Autoline Rev8 DMS which is not capable of supporting self-service and better visualization/dashboards to enhance decision making capability.
- The users were dependent on tech support/DMS reports for extracting the data from the source systems to analyze & monitor KPIs outside the DMS system using excel & other means.
- Decentralized data across multiple locations and multiple fragmented reports across functions made it hard to get the full value out of the data.
Solution
NRoot Labs was chosen as a trusted partner to implement and enhance information management by building a custom analytics solution for the dealership. NRoot Labs kicked off the project by putting together a digital transformation roadmap aligned to system readiness and business objectives.
The first step was redesigning existing reporting architecture for automobile business covering areas of Sales, Inventory, Service and Parts. NRoot Labs leveraged its unique data-extraction methodology from CDK. The data was then manipulated and shored up in the Enterprise Data Store in a usable format.
The team made data and analytics easier to access and use by deploying Microsoft Power BI to create interactive dashboards for several business areas. The deployment team also implemented data governance and change management guidelines for effective and secure use of data and analytics.
The client worked with NRoot Labs to ensure the data being reported was completely accurate.
Business Impact
- The solution helped IT/business solve data management issues in ERP at faster time with greater standardization, transparency and 0% manual effort.
- The report turnaround time is now reduced to 30 mins from 8 hours.
- Department managers now plan strategies for low performing products at 10x faster than earlier as Power BI provides the information on the fly for various periods and departments at all product levels.
- In turn, Stock availability based on the historic sales and inventory, each store P&L is increased by 30-40%.
- The solution is being leveraged to improve After Sales efficiency and productivity.
- Better planning of Menu Bundles/service packages.
- Increase in upsell Revenue.
- Customer retention in service is increased to 32%.
- Decrease in customer churn and revenue leakage.
- Better control of Obsolete category parts and better parts ordering process.
Create new value from data for your business now!
Self service BI vs. Traditional BI: A solution that IT loves and business trusts
23 Oct
As organizations shift their approach to analytics, IT leaders should seize the opportunity to redefine their role.
Adopting a collaborative approach to truly support self-service is the key to changing the perception of IT – from a producer to a strategic partner and enabler for the organization. Collaboration between the business and IT is critical to the success of the implementation. IT knows how to manage data and the business knows how to use the insights to drive business decisions. Early collaboration will not only lead to the deployment of a platform that meets the needs of the business but also drives adoption and impact of the platform overall. Indeed, in the 2015 Magic Quadrant for Business Intelligence and Analytics platforms, Gartner placed self-service data discovery tools designed for end users firmly in the forefront of the leaders’ quadrant.
Data Experts vs. Data Users
Owing to their complexity, traditional business intelligence (BI) tools have always been handled by data experts, meaning decision-making was limited to a privileged few. But not anymore. Today, In the world of BI, it’s all about the business user. Forget about those old tools that only data scientists or the IT department could use. In today’s fast-paced business environment, no one can afford to take weeks or months to prepare a report. It is all about being agile. Business users, at different levels, are able to access the real-time data they need & quickly generate results without the need for working on spreadsheets & any technical expertise. Often, no coding skills are required & even the reports can be sliced & diced as required without the use of Excel Pivots or any other methods of aggregation in SQL. The future is self-service, data discovery and quick insight—bringing power to the business users!
IT Governance vs. Empowering Users
As a self-service business intelligence solution, Self Service BI empowers the end user to seamlessly carry Self Service Data Analytics processes or Self-Service Reporting, without being heavily dependent on IT. When compared to Traditional BI, Self Service BI have a shorter development cycle that uses less IT resources and is quicker to deliver as well as easy to deploy on multiple platforms & devices. For example, reports can be accessed through smartphones & tablets. Because of the rich user interactive feature, user adoption is typically greater with Self Service BI than with Traditional BI as it is easier for any non-technical business user to understand & leverage. In Self Service BI Analytics, Data discovery is quick & easy, as it helps business to overcome the hurdles of Data Extraction & Data processing tools & pull data from different sources within their organisation (including the core data pipeline) to answer ad-hoc one-off questions. Once the Data-model is architected properly it helps information savvy users to get their answers fast without spending additional time on data-processing.
Self-Service Business Intelligence Governance provides ways for enforcing quick & affordable data governance. Business users are often unaware of the complexities of data preparation and the risks involved in getting it wrong. Without an authority guaranteeing strong data governance, they may miss mistakes in their own data, and draw the wrong conclusions—or different business users may draw upon poorly curated data sets, and reach different decisions. To prevent this, IT will most likely need to get involved.
Standardization vs. Customization
Each end user may be asking different questions, and looking for different answers. With flexible in-memory acceleration, users are able to create reports and answer questions for themselves, rather than having an IT department create reports for each question/user. Especially as data volumes grow, this becomes increasingly critical. With this in mind, self-service reports can provide a huge boost to productivity, as they can be personalised based on the individual requirements of staff. Self service reporting, enables an interactive reporting experience, as end users can make modifications and additions to their reports on the fly calling information to them instantly. Since report elements are chose individually, end users are able to ask their own questions of the data fully customizing their reports to match their data analysis needs. Additionally, end users should be able to interact with their finished reports by applying controls such as on-screen filters, sliders, conditional formatting, and by creating drill down and linked reports.
$$$ vs. $
One of the great benefits of Self-Service BI is the price, as well as further money that can be saved. With Self-Service BI being available over the Cloud, it can greatly reduce cost as no hardware need be installed. In addition to this saving, specific reporting staff are not needed as end users can report themselves, thereby saving money on personnel.
Standard Reports Vs. On Demand Reporting
Implementing ad hoc reporting functionality can be of major benefit to the entire enterprise. Self-service reporting puts the tools necessary to build a fully functional report and modify existing reports directly into the hands of end users so that data analysis can be achieved quickly, intuitively, and interactively with little to no training. Ad hoc reporting speeds the report creation process by empowering end users to work with their reports independent of developers. This helps to eliminate the lengthy back and forth cycle between end users and IT to achieve a final report, saving valuable time for both the end user and developer and allowing them to focus resources towards more mission critical activities. The platform gathers and stores all your cloud and on-premise info in a centralized location that you can access anytime, anywhere. You can also make use of pre-packaged content packs and built-in connectors to streamline import of your data from other sources (internet).
Dashboards and Reporting vs. Data Visualization as a service
An extensive library of visualizations and an intuitive drag-and-drop interface makes it easy for users to build data discovery dashboards. It will enable users to quickly visualize data with out-of-the-box grids, graphs, charts, and maps. If that’s not enough, it’s also easy to extend the visualization library to incorporate new third-party visualizations, like D3, or build your own from scratch with our Visualization Builder and SDK. Self-service tools allow them to visually slice and dice data, drill down to the bottom, and even change appearances with different chart types and a wide range of predefined templates for everyone. Visualization can change how business managers and other workers “see” data. The way data is presented to users will be as important as the information itself. But for achieving that, a flawless IT and BI architecture must be built that can deliver the right data to the right users and empower them to take advantage of it.
As an organization, you won’t get very far on self-service BI and data visualization if you don’t have high-quality data, a well-designed systems infrastructure, and consistent processes. A lot of work has to take place behind the scenes to build an IT and BI architecture that can deliver the right data to the right users and empower them to take advantage of it.
Making the transition to self-service analytics can be tricky and filled with challenges. Implementing few rules such as Embracing good data quality practices, Documenting Data definitions and lineage standards in data dictionary, embedding data science in reporting solutions, Developing security practices can will create a strong foundation for your team to build on. So, what’s next? Finding a trusted implementation partner can help. At NRoot Labs, our team of experts know BI and cloud computing. We helped many companies bridge that gap between IT and business users. Call us for a quick chat to discuss how you can bring the balance between IT and business at your organization.
Data is only as good as the questions you ask
28 Aug
DATA IS ONLY AS GOOD AS THE QUESTIONS YOU ASK
Data Data everywhere, not a drop to act! Data volumes and types are growing at such a rapid rate. The immense resource makes it possible to be many things that previously could not be done and to do them significantly faster.
In many industries, the businesses are drowning in the wide expanse of data and are unable to use it effectively and to drive business value or insights.
BE SPECIFIC
No matter how many millions of dollars you spend on tools and technology – to capture, process and share information, the question remains – are you making better decisions? Unless you ask the right questions and specific questions, your data will not provide the right insights.
| Asking Vague questions | vs. | Asking specific questions |
|---|---|---|
| How to raise my ROI? | What are the channels we should focus on to raise revenue while not raising the cost? | |
| What channels lead to bigger profit margin? | ||
| Which marketing campaign worked best? |
WHAT SHOULD I MEASURE?
Getting down to basics: Key Performing Indicators (KPI)
It is key to ask the data analysis questions from the start. They lay the foundation to your BI framework.
| How was sales last year? | vs. | What is the average Revenue Per Unit (ARPU)? |
| What is your Customer acquisition Cost (CAC)? | ||
| What is your Customer Lifetime Value (CLV)? |
WHAT ARE MY DATA SOURCES?
Ask your data team if the right data is available to address the specific questions. Identify the data sources you need now and for future and gather them in one place.
It is very important to make sure that your data is not skewed towards a subset, because it may not give you the bigger or the whole picture.
HOW TO ENSURE DATA QUALITY?
Your data analysis questions are designed to give a clear view of reality. If the data is incorrect, you may get distorted view of the reality.
Read more about our Data Integration process
WHO IS THE END USER?
Knowing the end user will help you decide, what data and report you should focus on. Each type of end users, whether it is members of staff or someone from the management/governing body, has different needs and expectations. Some of the questions that you could focus on are as below:
- Who are your end users?
- How will they act on the results?
- What do they expect from the reports?
- What are their needs?
- What are their technical skills?
- How much time can they spend on the analysis?
HOW SHOULD I PRESENT THE DATA?
Most valuable insights, if presented poorly can leave your target audience, without the impact you are hoping for. It is important to convince the end user that your data is accurate, reliable, important and urgent to act on.
| Data in a spreadsheet | vs. | Drawing a picture with data |
| Data in a table | Telling a specific coherent story |
HPW TO ENSURE A DATA DRIVEN CULTURE?
With this information, you can outline questions that will help make key business decisions and set up a data driven infrastructure, teams and culture in a consistent basis.
Companies that have successfully cultivated a data-driven culture reap a multitude of benefits, from better employee understanding of the value of data and how to apply it to decision-making to a widespread commitment to backing up ideas with data and measuring outcomes across the board.
Without information, you’re simply another person with an opinion.
Embracing a Growth Mindset: Your Key to Analytics Success
03 Mar
In a world where data is paramount, don’t you agree that insights are invaluable? And with the right mindset you bring to the table will truly set you apart!
Enter the growth mindset – a powerful approach that can propel you and your business forward in your analytics journey like never before.So, what exactly is a growth mindset? Simply put, it’s the belief that your abilities and intelligence can be developed over time through dedication and hard work. It’s about embracing challenges, being persistent when faced with setbacks, and putting continuous efforts to master the art of problem-solving. In analytics, a growth mindset is your secret asset. Instead of being intimidated by complex data sets or unfamiliar techniques, you see them as opportunities to learn and grow. You welcome feedback, both positive and constructive, knowing that it will only help you and your business to improve. We must understand that failures aren’t roadblocks – they’re stepping stones on the path to success. When you encounter obstacles in your analytics projects, you don’t give up or see them as indicators of your limitations. Instead, you view them as valuable learning experiences that will ultimately make you stronger and more capable. Moreover, a growth mindset fosters a spirit of collaboration and innovation. You’re not afraid to seek out new ideas or perspectives, knowing that they can lead to breakthrough insights. You’re open to experimenting with different approaches and methodologies, knowing that innovation often arises from trial and error. So, the next time you sit down to tackle a challenging data or analytical problem, remember the power of a growth mindset. Embrace the journey, learn from your experiences, and watch your business reach new heights! We are NRoot Labs, specialize in comprehensive BI solutions. As a technology-neutral company, our team of BI consultants excels in delivering business solutions that leverage actionable insights supported by business data. Our commitment to understanding the complexities of business processes enables us to provide enhanced BI solutions for our clients.