Ditch the Data Bottlenecks: Why Sigma Wins Over Looker

Ditch the Data Bottlenecks: Why Sigma Wins Over Looker

Written by

Mike Galvin, Managing Director

Published

April 22, 2025

Data Analytics
Sigma

Data modeling is essential for turning raw data into actionable insight—but not all modeling approaches are built to last. Looker, with its powerful semantic layer and LookML modeling language, once set the standard for centralized data governance and self-service analytics. But as many organizations have learned the hard way, what starts as a promising framework can become a long-term liability.

Despite its early appeal, Looker’s modeling approach often creates friction, complexity, and bottlenecks that hinder agility and scalability over time. Fortunately, newer tools like Sigma offer a fresh approach—one that eliminates the overhead of rigid data models while empowering business users to explore and analyze with freedom and confidence.

The Promise of Looker’s Data Modeling Layer

Looker introduced a compelling vision for modern business intelligence (BI): a centralized, code-based semantic layer that abstracts SQL logic and standardizes metrics across the organization. Using LookML, data teams can define dimensions, measures, joins, and business logic in reusable files. The benefits are clear—centralized governance, version control, and consistency.

This model appealed to many organizations looking to bring order to fragmented reporting environments and reduce the burden on analysts manually writing SQL. For a time, it worked well. But as teams scaled, so did the problems.

Why Looker Models Struggle Over Time

1. Complexity Grows Rapidly

As data needs evolve, LookML models tend to grow in size and complexity. What starts as a manageable set of views and explores can balloon into a tangled web of dependencies, nested joins, and abstracted logic that’s hard to debug, let alone maintain. Small changes can have unintended ripple effects, making even simple updates risky.

2. Bottlenecks for Business Users

The centralized modeling layer puts the power squarely in the hands of the data team. While this ensures consistency, it also creates a bottleneck: business users must request updates or new metrics through developers. This slows down decision-making and discourages innovation. Over time, users stop exploring and start waiting.

3. Skills Gap and Maintenance Burden

LookML is a proprietary language, and maintaining models requires not just SQL knowledge, but fluency in YAML, Git workflows, and Looker’s specific abstractions. Training new team members or scaling your analytics function becomes a challenge—especially when compared to more intuitive tools.

4. Limited Real-Time Collaboration

Looker is largely dashboard-driven, with limited capabilities for spontaneous collaboration or iterative exploration. Business users can slice data only within the bounds defined by the model, which limits their ability to answer new questions on the fly or experiment with different views of the data.

5. Governance vs. Agility Tradeoff

Looker’s emphasis on governance often comes at the cost of agility. The more tightly you lock down models to ensure data quality, the more you constrain users’ ability to explore. In many organizations, this leads to shadow BI, where teams export data to Excel or create parallel solutions outside the sanctioned platform—defeating the very purpose of central governance.

Why Sigma Is Better

1. Spreadsheet-Native Interface

Sigma brings the power of a modern data warehouse to a familiar spreadsheet interface. Business users don’t need to learn LookML or write SQL to get insights. They can build pivot tables, apply formulas, and create visualizations just like they would in Excel—only at cloud scale.

“Users interact with data using a spreadsheet-like UI that requires no coding—lowering the barrier to entry for insights.”

2. Real-Time Access Without Predefined Models

Unlike Looker, Sigma allows direct querying of cloud data platforms without the need for a semantic layer. Users explore data in real time, dramatically reducing time-to-insight and avoiding long request queues for model updates.

3. True Business User Empowerment

Sigma breaks down the wall between technical and non-technical users. Analysts and business users can create calculations, join datasets, and build dashboards without writing code—reducing the load on data engineers and accelerating time to insight. By enabling users to filter, join, calculate, and visualize data independently, Sigma reduces dependency on technical teams.

“Everyone from analysts to execs can make data-driven decisions without waiting for developers.”

4. Governed Flexibility

Governance isn’t an afterthought in Sigma—it’s built into the platform. Admins can define access controls, certified datasets, and permissions to ensure data integrity while still giving users room to explore. It’s the best of both worlds: flexibility with oversight.

5. Seamless Embedded Analytics

Sigma makes it easy to embed business intelligence (live dashboards, tables, and interactive analytics) directly into your customer-facing applications, portals, or internal tools. With secure, customizable embeds that respect user permissions, teams can deliver real-time insights to customers, partners, or business units—without duplicating infrastructure or exposing raw data.

6. Built for the Modern Data Stack

Sigma’s cloud-native architecture works seamlessly with Snowflake, Databricks, BigQuery, and dbt. By shifting compute to the data warehouse and integrating with upstream transformation tools, Sigma eliminates the need for a rigid, proprietary modeling layer.

From Rigid Models to Real-Time Insights

Looker helped pioneer the idea of a governed semantic layer, but its rigid modeling approach often becomes a barrier rather than a bridge. The overhead, complexity, and user friction it introduces make it difficult to sustain in the long run—especially for organizations that need speed, flexibility, and scale.

Sigma offers a smarter path forward: one that empowers business users, accelerates insight, and aligns with the architecture of the modern data stack. If your Looker models are holding you back, it might be time to explore a better way.

Accelerate Analytics
with Sigma and OneSix

You don’t have to settle for outdated models and clunky workflows. With Sigma’s spreadsheet-native interface and direct access to cloud data, your team can move faster and smarter. As a Sigma consulting partner, OneSix can help you make a seamless transition to modern BI.

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Using AI to Extract Insights from Data: A Conversation with Snowflake

Using AI to Extract Insights from Data: A Conversation with Snowflake

Published

February 6, 2025

During Snowflake’s World Tour stop in Chicago, Data Cloud Now anchor Ryan Green sat down with leaders from OneSix. During the conversation, Co-founder and Managing Director Mike Galvin and Senior Manager Ryan Lewis note how Snowflake’s technology has changed the game, allowing them and its customers to focus less on how to build data infrastructure and more on how to extract insights from data, be it via the use of AI or reporting or dashboarding.

Get More from Your Data with Snowflake

As a Premier Snowflake Services Partner, we drive practical business outcomes by harnessing the power of Snowflake AI Data Cloud. Whether you’re starting with Snowflake, migrating from a legacy platform, or looking to leverage AI and ML capabilities, we’re ready to support your journey.

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Embedded Analytics: A Non-Negotiable for User-Centric Software Companies

Embedded Analytics: A Non-Negotiable for User-Centric Software Companies

Written by

Ajit Monteiro, CTO & Co-Founder

Published

October 30, 2023

Data Analytics
Technology
Pyramid Analytics
Tableau
Power BI

In an era where data drives decisions, and subsequently, the trajectory of businesses, the adage “knowledge is power” has never been more pertinent. For software companies in particular, there’s a significant emphasis on not just gathering data but also on presenting it in a way that’s efficient, insightful, and user-friendly.

Embedded analytics plays a pivotal role in this data revolution. By integrating analytics capabilities and data visualizations directly into user workflows, applications, or portals, embedded analytics streamlines access to insights and provides users with a highly interactive and user-friendly data engagement experience. So, why is it an absolute must for software companies to embrace embedded analytics right now? Let’s explore.

1. Meeting the Surge of Enhanced User Expectations

Today’s software users, with the tech advancements and the data-rich platforms they’re accustomed to, have gone from being passive consumers of information to actively digging for deeper insights. Static reports just don’t cut it anymore. Users want analytics that are dynamic, interactive, and allow them to explore. Embedded analytics offers users the freedom to dissect and play with their data without ever leaving their operational environment, elevating user satisfaction and engagement.

2. Achieving Competitive Differentiation

In a market saturated with software solutions vying for user attention and loyalty, delivering enhanced, value-driven user experiences is paramount. Embedded analytics offers a competitive edge, setting software solutions apart by enriching user experience through tailored insights, predictive analytics, and real-time data interaction within the software itself. It becomes a significant differentiator that not only attracts users but also retains them by continuously adding value to their interaction with the software.

3. Enabling Informed, Real-time Decision-making

The ability to make well-informed decisions in real time has become a key factor in successfully navigating today’s fast-paced business landscape. Embedded analytics embeds critical data and insights directly into the user’s workflow, thereby not only streamlining decision-making processes but also ensuring that every decision is backed by insightful data without the need for disruptive shifts between operational and analytical tools.

4. Mitigating the Strain on Development Resources

As user demands for custom reports and deeper analytical insights increase, development teams often find themselves bogged down with requests for custom reports, diverting crucial resources from product development and enhancement. Embedded analytics alleviates this strain, empowering users with the tools to create, modify, and interact with reports autonomously, thereby freeing development teams to focus on core product development and innovation.

5. Sustaining Growth Through Scalable Solutions

As software companies evolve, so do their data needs and the analytical expectations of their users. Embedded analytics offers a scalable solution, accommodating growing data and user bases while ensuring that the analytical depth, interactivity, and user-friendliness of the platform are not compromised. This ensures that the software remains in alignment with user expectations and needs, safeguarding its relevance and utility in the long term.

6. Enhancing Customer Loyalty with Superior Experiences

In delivering an enriched, interactive, and autonomous data interaction experience, embedded analytics significantly enhances user satisfaction and loyalty. When users can derive actionable insights, sculpt reports, and explore data on a platform that is simultaneously robust in its operational and analytical capabilities, it instills a sense of autonomy, satisfaction, and loyalty towards the software, fortifying its user base against the allure of competing solutions.

7. Steering Towards a Future-Ready Model

As technology evolves, so will the methodologies in which data is presented and interacted with. Embarking on the embedded analytics journey now ensures that software companies are not playing catch-up in the future but are well-entrenched in the advanced data interaction models of tomorrow, ensuring sustainability, relevance, and leadership in the future data landscape.

Unlock Growth with
Embedded Analytics

The integration of feature-rich analytics within a SaaS application can fundamentally reshape the competitive landscape for software providers. As user expectations, market dynamics, and technological capabilities evolve, embedded analytics stands out as the beacon guiding software companies towards enriched user experiences, competitive differentiation, and strategic future readiness, making its adoption not just beneficial, but imperative.

For a deeper dive into how software companies can enrich user experiences and drive sustainable business outcomes with embedded analytics, view our comprehensive guide.

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OneSix helps companies build the strategy, technology, and teams they need to unlock the power of their data.

Unleashing the Power of Embedded Analytics

Unleashing the Power of Embedded Analytics

Written by

Mike Galvin, CEO & Co-Founder

Published

October 26, 2023

Data Analytics
Technology
Pyramid Analytics

It’s no longer optional to be a data-driven organization; it’s a requirement for staying competitive and relevant in today’s market. Some of the biggest brands, like Amazon and Netflix, have set a high standard by being fully data-driven from top to bottom. They’re leveraging data to drive more customers, to retain those customers, and to make themselves more profitable.

So what does it take to become truly data-driven? A critical piece of the puzzle is integrating analytics seamlessly into your everyday operations, which is where embedded analytics comes into play.
Unlike traditional approaches that use iframes to display analytics on a website, Pyramid Analytics—a premier OneSix partner—offers a unique embedded analytics solution. They focus on delivering lightweight code that ensures fast performance and scalability. This guarantees that you get the insights you need without wasting valuable resources.

To put it simply, the solution embeds analytics in the page, not on the page with iframes. This approach is vital when you’re considering sharing data outside your organization’s firewall. Embedding analytics surfaces opportunities to not only leverage data for insights but to also effectively monetize it by pushing information out to your customers.

Let’s delve into some real-world examples and use cases that highlight the transformative potential of embedded analytics.

Putting Analytics into the Hands of Users

One of the primary challenges in the realm of embedded analytics is making data accessible to users within the applications they use daily. In this case, “users” can be customers who are accessing analytics within your software product or employees who are accessing analytics in an internal application.

For many organizations, reporting is an afterthought. But the truth is, if your reporting is falling short of user expectations, your business could be at risk of increased customer churn and frustrated employees.

Consider a scenario where an inventory manager uses a homegrown or third-party application for day-to-day tasks. Accessing a separate dashboard and drilling down into various metrics to reorder products can be time-consuming and tedious. Embedded analytics simplifies these tasks by presenting essential insights directly within the application they work with daily. This kind of data-driven user experience not only streamlines processes but also enhances decision-making by providing relevant data without requiring users to switch between multiple systems.

A Unified User Experience

Consistency is another significant advantage of embedded analytics. Instead of dealing with a multitude of reporting tools and interfaces, organizations can create a unified experience for their end-users. By integrating data from various sources into a single location, it becomes much easier for teams to access and interact with data consistently.

This approach not only improves efficiency but also enhances the overall user experience. Users won’t need to adapt to different reporting tools and interfaces, simplifying their work while making it more accessible and enjoyable.

Democratizing Data Access

Another challenge when dealing with multiple tools is managing access to data. Which tool should users leverage and what data can they see? This complexity often leads to confusion and inefficiencies. Embedded analytics solutions simplify data governance, giving organizations greater control over who can access what data, and when they can see it.

As a result, data governance becomes more manageable, and the user experience becomes more seamless. Instead of struggling with multiple systems and logins, users can focus on what matters most: extracting insights from data to drive better decisions.

Real-World Success with Embedded Analytics

To illustrate how embedded analytics can be a game-changer in the real world, consider the case of a certain healthcare software provider. This company had a 90-day window to transition away from its existing reporting tool. The challenge was to find a solution that could quickly integrate with their web application, promate rapid user adoption by providing easy learning curves, and drive meaningful reporting outcomes.

Pyramid Analytics’ platform proved to be the ideal choice. The platform’s ability to seamlessly connect to various data sources, ease of adoption, and efficient AI-augmented reporting allowed the company to meet its tight timeline and deliver a superior experience to users. OneSix supported the installation and configuration, encompassing the construction of data models and report outputs, as well as testing and deployment of Pyramid models and reports.

Take a Deeper Dive into Embedded Analytics

In a recent webinar, OneSix and Pyramid Analytics came together to share insights on the power of embedded analytics. Watch the recording below to learn more and see a live demo of Pyramid’s platform.

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Embedded analytics is a game-changer for data-driven organizations across industries. OneSix is here to help your organization build the strategy, technology, and teams you need to unlock the power of your data.

Introducing Community Bank 360° for Data-Driven Growth

Introducing Community Bank 360° for Data-Driven Growth

Written by

Mike Galvin, CEO & Co-Founder

Published

September 28, 2023

Data & App Engineering
Data Analytics
Financial Services
Power BI
Fivetran
Matillion
Snowflake

In today’s digital era, community banks face an ever-evolving landscape of challenges. Recognizing the pressing need for a dedicated solution tailored for this sector, OneSix introduces Community Bank 360°. This offering is not just a tool, but a comprehensive strategy and service offering based on our commitment to aid community banks in harnessing their data effectively.

Introducing Community Bank 360°

Community banks find themselves at a crossroads, needing to evolve and integrate new-age solutions while preserving the essence of their community-focused ethos. It’s within this backdrop that OneSix’s Community Bank 360° emerges as a beacon, offering these institutions a way forward in navigating the digital transformation journey.

Unified Data Platform

Centralized Data Management

By centralizing all pertinent data, we eradicate the gaps that prevent a consolidated customer view, enabling banks to swiftly access and analyze customer information from a single point.

Master Data Management

Ensure consistency, accuracy, and reliability across your data assets. By applying advanced Master Data Management techniques, we ensure that data from various sources is coherent, reducing discrepancies and offering a single version of the truth.

In-depth Customer Analytics

Data Visualization

Visualize the customer journey like never before. With tools like Power BI and Tableau, banks can grasp complex data patterns through intuitive visuals, enabling quicker and more informed decisions.

Actionable Insights

Beyond mere data visualization, the solution extracts actionable insights. By understanding customer behaviors and preferences, banks can design strategies that resonate and effectively respond to market demands.

Scalable & Flexible Infrastructure

Cloud-Driven Solutions

With the flexibility of the cloud, banks can scale their data operations up or down based on demand, ensuring efficiency without compromising on capabilities. This agility allows banks to adapt to changing data needs seamlessly.

Powered by Matillion

Recognizing that every community bank is unique, our solution harnesses the power of Matillion’s engine, offering the liberty to customize data processes. This means banks can mold the solution to fit their unique operational nuances and requirements.

Holistic Training & Support

Empowering Banks

The best tools are only as effective as those wielding them. We provide a comprehensive training program, ensuring your team can make the most of Community Bank 360°.

Continuous Support

Our commitment doesn’t end post-implementation. With a dedicated support team, we ensure you’re always equipped to tackle any challenges that come your way, maximizing the utility of the tool for enduring success.

Unlocking Business Outcomes

Drawing upon industry-leading insights and cutting-edge methodologies, our solution aims to elevate every facet of banking—from customer engagement and operational efficiency to growth planning and risk mitigation. By integrating this transformative approach, community banks can unlock unparalleled business outcomes:

Enhanced Customer View

Delve into enriched customer interactions and offer banking experiences that resonate. As Forrester points out, those who tap into customer insights see a staggering 85% rise in sales growth compared to their peers.

Deeper Customer Engagement

With our 360° customer view, create tailored banking experiences, fostering enhanced loyalty and retention. Again, Forrester’s findings reinforce the value of deep customer insights, linking them to an 85% surge in sales growth.

Maximized Cross-selling and Upselling

A nuanced understanding of each customer’s journey uncovers latent opportunities, allowing banks to present relevant offerings. Such strategies, as McKinsey highlights, can amplify sales by a remarkable 10%.

Operational Streamlining

By harmonizing various processes, banks can drive down redundancies, fine-tune their workflows, and enhance decision-making. Integrating data in such a manner can precipitate cost reductions of up to 23%, as noted by IDC.

Adaptive Digital Strategy

As digital banking undergoes constant metamorphosis, our solution ensures community banks always remain a step ahead, appealing to the modern, tech-savvy customer.

Risk Mitigation & Enhanced Compliance

With a robust data framework, banks can confidently navigate the intricate regulatory maze, benefiting from improved reporting, reduced errors, and diminished compliance-associated risks.

Strategic Growth Planning

Grasping the core segments of the customer base permits banks to align their strategies with the highest growth potential sectors, optimizing the return on investment.

Personalized Marketing Campaigns

Harnessing detailed customer insights allows for the crafting of targeted marketing endeavors, which in turn, enhances engagement rates and bolsters the ROI on marketing investments.

Revolutionize Your Community Bank

Community Bank 360° is more than a tech upgrade. It equips banks with the requisite tools and insights to not only remain competitive but also to chart an innovative path towards sustainable, data-driven growth. It’s a strategic guide for community banks in a digital world. By adopting this approach, banks can not only enhance customer relations but also ensure sustainable growth in a challenging market environment.

For a deeper dive into how community banks can overcome their data challenges with Community Bank 360°, view our comprehensive guide.

Get Started

OneSix is here to help your organization build the strategy, technology, and teams you need to unlock the power of your data.

Deciphering the Data Dilemma: Top Challenges Community Banks Face Today

Deciphering the Data Dilemma: Top Challenges Community Banks Face Today

Written by

Mike Galvin, CEO & Co-Founder

Published

September 13, 2023

Data Analytics
Data & App Engineering
Financial Services

The digital era brings with it immense opportunities, but also new challenges, especially for community banks. The heart of these challenges often revolves around data—how it’s collected, stored, analyzed, and utilized. Let’s delve into the specific data hurdles community banks are grappling with and explore potential solutions.

Fragmented Data Systems

Community banks often struggle with managing data spread across multiple systems. This fragmentation not only causes inconsistencies but also deprives banks of a unified 360-degree view of their customers. As a result, they miss out on leveraging holistic insights for effective cross-selling, up-selling, and tailored service offerings.

Inadequate Customer Insights

A disjointed data system makes it difficult to extract meaningful insights about customers. Without a comprehensive understanding of customer behaviors, preferences, and needs, community banks face challenges in designing products and services that resonate with their clientele.

Operational Inefficiencies Due to Data Disparities

A disjointed data system makes it difficult to extract meaningful insights about customers. Without a comprehensive understanding of customer behaviors, preferences, and needs, community banks face challenges in designing products and services that resonate with their clientele.

Navigating Regulatory & Compliance

With the ever-evolving landscape of financial regulations, community banks face the daunting task of ensuring their data practices comply with these standards. Disparate data systems make it harder to adhere to regulatory norms, increasing the risks of non-compliance and potential repercussions.

The Digital Competence Gap

As fintech solutions and larger banks tap into advanced data analytics, AI, and other digital innovations, community banks may feel left behind. Embracing digital transformation is no longer optional; it’s a necessity to meet modern customer expectations and stay competitive.

Navigating the Future with OneSix’s Community Bank 360°

To effectively address these data-related challenges, community banks need a comprehensive strategy. Enter OneSix’s Community Bank 360°, a dedicated solution tailored for community banks to harness their data. This solution offers:

A Unified Data Platform

to centralize data, eliminating gaps and providing a consolidated customer view.

In-depth Customer Analytics

through Power BI integration, enabling banks to visualize complex data patterns and extract actionable insights.

Scalable & Flexible Infrastructure

that adapts to changing data needs, ensuring efficiency. It’s powered by Matillion, allowing banks to tailor the solution to their unique operational requirements.

Holistic Training & Support

ensuring banks maximize the utility of Community Bank 360°.

Revolutionize Your Community Bank

Community Bank 360° is more than a tech upgrade. It equips banks with the requisite tools and insights to not only remain competitive but also to chart an innovative path towards sustainable, data-driven growth. It’s a strategic guide for community banks in a digital world. By adopting this approach, banks can not only enhance customer relations but also ensure sustainable growth in a challenging market environment.

For a deeper dive into how community banks can overcome their data challenges with Community Bank 360°, view our comprehensive guide.

Get Started

OneSix is here to help your organization build the strategy, technology, and teams you need to unlock the power of your data.

Achieving True Customer 360 from Scratch in Record Time

Achieving True Customer 360 from Scratch in Record Time

Written by

Faisal Mirza, VP of Strategy

Published

July 13, 2023

Data & App Engineering
Data Analytics
Financial Services

In today’s data-driven world, organizations across industries face the challenge of managing customer data scattered across multiple systems. The lack of a unified view of customer information often leads to inefficiencies, data inconsistencies, and missed opportunities. In a recent webinar, Faisal Mirza, Vice President of Strategy at OneSixshowcased the implementation of a customer 360 solution for a leading mid-sized bank in New England. He highlights the challenges faced by the bank, the solution implemented, and the remarkable outcomes achieved. 

Challenges Faced by the Bank

The banking client approached OneSix with several challenges. Their existing systems were fragmented, with separate platforms for commercial lending, residential lending, and core banking operations. This siloed approach resulted in a lack of interaction between systems, making it difficult to identify and link customer information accurately. Back-office processes were cumbersome, and customer support teams struggled to provide efficient service due to a lack of comprehensive customer data. Additionally, data quality issues, such as inconsistent naming conventions and formats, further complicated the situation. 

The Customer 360 Solution

To address these challenges, OneSix partnered with the bank to develop a robust customer 360 solution. The solution aimed to provide a holistic view of each customer by integrating data from the various systems into a unified platform. By establishing a common data platform, the bank could tie together customer interactions, track their history, and gain valuable insights for personalized marketing and improved customer service. 

The Implementation Process

The project faced several constraints, including a limited budget, a small team, and a tight timeline. Despite these challenges, OneSix adopted an agile approach and leveraged the team’s expertise to devise an efficient solution. They utilized cloud technology, including Snowflake and Fivetran, to bring together data from multiple systems.

By leveraging Fivetran for data ingestion and transformation, they streamlined the process and ensured accurate and timely data integration. The resulting customer 360 data warehouse provided a comprehensive view of each customer, including their demographics, interactions, accounts, and collateral. 

Benefits and Success

The implementation of the customer 360 solution yielded significant benefits for the bank. With a unified view of customer data, customer support teams could quickly identify callers and access their interaction history, leading to improved service and reduced call handling time. The marketing team gained valuable insights to drive targeted campaigns and personalized offers. The bank also witnessed enhanced data quality, streamlined processes, and increased customer satisfaction. 

Lessons Learned and Recommendations

Throughout the implementation process, OneSix emphasized their collaborative partnership with the bank. They highlighted the importance of selecting the right tools and technologies aligned with the organization’s goals and strategies. Their modular approach allowed for scalability, ensuring that future expansions and system integrations would be seamless. They emphasized the significance of a well-defined data strategy and roadmap for organizations looking to embark on similar customer 360 initiatives. 

The Power of Customer 360

The success of the customer 360 solution showcased in this webinar demonstrates the power of integrating customer data from disparate systems into a unified platform. By leveraging cloud data platforms, data integration tools, and a collaborative approach, organizations can overcome data fragmentation challenges and achieve a holistic view of their customers. 

Get Started

OneSix helps companies build the strategy, technology and teams they need to unlock the power of their data.

Analytics Projects: 6 Common Reasons They Fail

Analytics Projects: 6 Common Reasons They Fail

Published

March 24, 2023

Data Analytics

Why do so many analytics projects fail?

Data continues to be created and consumed at an increasingly stunning pace year over year. Predictions from global data experts show that humans will produce and consume about 118 zettabytes of data by the end of 2023.1

Soon, data itself will become a primary product for nearly every business, and data analytics will form the core of every company’s business model. Nearly every product on the market will be forced down one of two paths, becoming either “smart” (i.e., analytics- and data-driven) or obsolete.2

So, how do companies compete in a world where data becomes the primary product?

Most companies don’t know where, or how, to start.  And so, they start to do ‘things’ and they fall into a spiral of complexity, and instead of removing complexity with data, the data adds more complexity.

Analytics project complexity often leads to costly failure.

85%

of big data projects fail*

87%

 

of data science projects never make it to production**

20%

of analytics insights will deliver business outcomes*

So, what are the top factors causing this complexity and causing analytics projects to fail?

Lack of Clear Data Strategy

One of the most common reasons for analytics project failure is the lack of clear objectives. Without a well-defined goal, it becomes challenging to measure success or even know where to start. A well-defined data strategy helps to align stakeholders and create a clear roadmap for the project.

Poor Data Quality

Poor data quality is another major reason why analytics projects fail. The accuracy, completeness, and consistency of data used in analytics projects are critical. If the data is inaccurate or incomplete, the insights drawn from it will be unreliable, leading to flawed conclusions.

Inadequate Data Infrastructure

Analytics projects require a robust data infrastructure to support data processing, storage, and analysis. Inadequate infrastructure can lead to slow processing times, system crashes, and data loss, all of which can jeopardize the project’s success.

Lack of Skilled Talent

Analytics projects require skilled professionals with data science, statistics, and programming expertise. Organizations that lack the right talent will find it challenging to implement analytics projects successfully.

Siloed Systems

Their data is trapped in individual siloed systems limiting insights across multiple applications and domains

Resistance to Change

Analytics projects often require significant changes in organizational processes and workflows. Resistance to change can occur at any level of the organization and can impact the success of the project. It is essential to identify potential roadblocks early on and work to mitigate resistance to change.

To help companies solve data complexity problems, we’ve purpose-built One Six as their partner in building a Modern Data Organization.

Modern Data Organizations are committed to the idea that all business decisions must be data-driven. They have defined and executed a clear and deliberate strategy to centralize their data, extract meaningful and reliable insights, and develop a culture where high-quality insights are available and actionable at all levels of the company.

Developing an Enterprise Data Strategy that provides a clear and deliberate roadmap from your organization’s current state to where you want to be, is the critical first step for a successful analytics project, and to becoming a modern data organization.

The One Six team created our Data Strategy Roadmap process to help companies map their path from their current state to their desired future state. This process prioritizes projects with high ROI and low risk. Our strategists will collaborate with your team to determine the most impactful projects in the short and long term. They will create a list of prioritized projects using an opportunity matrix, which will show which projects deserve investment and the best order to tackle them.

Current State

The One Six team will analyze the existing data assets, strategy, platforms, people, and processes and create a scorecard of your organization’s data maturity.​

Future State

The team will create a strategic vision for your data-driven organization’s future state, including technology, people, processes, and data use cases.​

Roadmap

The team will develop a roadmap to move you from this current state to the future state prioritized by the projects that provide the most value.​

Equipped with your detailed Enterprise Data Strategy, One Six has the experience, expertise, and personnel to help implement your data strategy roadmap and ensure success for your analytics projects.

Making Business Intelligence Insights Actionable at Logistics Companies

Making Business Intelligence Insights Actionable at Logistics Companies

Published

January 31, 2023

Data Analytics

At One Six we believe the most successful companies make data-driven decisions to enable business growth and establish their competitive advantage. But consolidating data in a data warehouse and building high-level dashboards that represent the state of the business is only the first step.

The valuable insights gained from the data need to be disseminated to employees so that they can act on them to make informed decisions and create value for their customers.

As we’ve worked with logistics companies over the years, we’ve found the following technologies have helped these companies drastically improve their business.

Embedded analytics

Embedded analytics places insights at the point of need, inside portals, and workflow applications, which makes it possible for users to take immediate action without needing to leave their day-to-day work. It drives efficiencies within workflows and significantly increases user adoption of your analytics investments. Metrics are still centrally governed and pushed out to systems, which increases trust and reliability.

Example: Logistics companies have large amounts of data on suppliers, including prior issue tracking, complaints, delivery time delays, etc. Embedding insights from this data into an ordering platform allows better data-driven decisions when an order is placed.

Event-based notifications and automated workflows

Notification platforms allow email, text, and app-based notifications as changes happen in the business. In a modern data organization, users don’t need to check dashboards to find actionable insights based on changing data. They can instead receive real-time notifications to alert them of these changes, enabling them to react quickly and focus on business outcomes.

When the solution to a problem doesn’t require human intervention, these notifications can also initiate automated workflows to resolve the issue.

Example: Logistics companies work with large amounts of transactional data, and service quality is defined by on-time delivery and clear communication with clients. Being able to promptly notify the right people when there are issues with an order allows them to solve the issue or communicate necessary changes. If the problem is common and a solution can be automated, the system can update the order and notify the customer, removing the need for human intervention.

Data-Native Applications

Modern data warehouses enable rapidly building custom applications on top of large, centrally managed data sets. These applications use the centrally stored data from line of business applications, don’t require moving large amounts of data between systems, and can be built to an organization’s specific needs.

Example: A logistics company can build an equipment management application to represent the real-time status of trucks and their load, allowing users to know which trucks are partially or fully empty, which in turn reduces costs and improves efficiency.

At One Six we help logistics companies build modern data organizations. As part of our Logistics Data Strategy Sprint, we define their advanced analytics strategy in 4-6 weeks.

How Do Logistics Organizations Leverage Data More Effectively?

How Do Logistics Organizations Leverage Data More Effectively?

Published

January 20, 2023

Data Analytics

Logistics companies can take several steps to better leverage their data:

Collect and store large amounts of data from a variety of sources:

Logistics companies should collect and store as much data as possible from a variety of sources, including internal systems, customer interactions, and external sources such as market research and industry trends.

This will provide a rich and comprehensive dataset that can be used to gain insights and make informed decisions.

Use advanced analytics and machine learning techniques:

Logistics companies should use advanced analytics and machine learning techniques to gain insights from their data.

This can include identifying trends, predicting outcomes, and detecting anomalies in the data. By using these techniques, logistics companies can uncover valuable insights that can help them improve their operations and deliver better services to their customers.

Integrate data and insights into business processes and decision-making:

Logistics companies should integrate the data and insights they generate into their business processes and decision-making.

This can include using data to inform product development, marketing, and sales strategies, as well as to optimize operations and improve the customer experience.

Provide data-driven products and services to customers:

Logistics companies should also consider using the data and insights they generate to develop data-driven products and services for their customers.

This can include offering data analytics and visualization tools, or providing custom reports and insights that help customers make better decisions and improve their operations.

Overall, logistics companies can better leverage their data by collecting and storing large amounts of data from a variety of sources, using advanced analytics and machine learning techniques, integrating data and insights into their business processes and decision-making, and providing data-driven products and services to their customers. By taking these steps, logistics companies can improve their operations, deliver better services to their customers, and drive growth and success.

Logistics companies that best leverage their data to operate as truly data-driven organizations have made the transition to a Modern Data Organization. To learn more about what a Modern Data Organization looks like for logisitcs companies, check out the resources below.

If you would like to see how One Six can help transition your business to a modern data organization, contact us today for a Free Consultation.