The decision to better utilize your data can help you emerge successfully from COVID-19 and lead to huge gains for your company. According to Gartner, 78% of executives believe analytics is the key to growth after the chaos of 2020. But, data analytics leaders are faced with questions on where to start, how to scale, and how to effectively align data and analytics to business outcomes.

In this guide, you’ll learn about the benefits of working with data analytics consultants, the biggest challenges you’ll face when adopting a data analytics approach, the 7 most critical factors you should consider during the evaluation process, and more.

We will be answering the following key questions:

• What is data analytics and how can it help a business?
• What do data analytics consultants do?
• What are the biggest challenges companies face when adopting a data analytics approach?
• What are the benefits to hiring data analytics consultants?
• What should you consider when hiring data analytics consultants?
• Are you ready to hire data analytics consultants?

What is data analytics and how can it help a business?

Performing data analysis can be quite complicated, but the process essentially boils down to drawing insightful conclusions of substantial business relevance from datasets.

Over time, data analytics has evolved from conducting a simple analysis of what has already happened using Excel to advanced analytics that utilizes algorithms and machine learning to uncover trends and make predictions. Prescriptive analytics aims to provide recommendations based on patterns found, opening new doors for companies to take that data one step further.

Many companies are also finding immense value in combining and analyzing their first-party data (i.e., data already owned) with third-party data (i.e., external sources of data) to more accurately monitor and predict future consumer behavior trends using data science and artificial intelligence (AI). For example, ThoughtSpot recently predicted that organizations that capitalize on internal and external data for timely signals and comprehensive insights will outperform their competitors by double digits.

When companies choose to invest in data analytics, they aren’t just investing in the latest “shiny object.” They are effectively transforming their business by arming themselves with the right tools, the optimal datasets, and the necessary expertise to identify actionable insights that can drive growth and lead to a competitive advantage.

What are the biggest challenges companies face when adopting a data analytics approach?

1. Taking the first few steps
     All companies already have access to some level of sales, supply, or customer information. But how do you leverage that data to accomplish your business goals, and which third-party datasets might help to improve the results? That’s where many companies get stuck. How do you identify the right sources of data, what is the best way to collect and share it across the organization, how can you ensure the quality and security of the data, which data and analytics priorities should you tackle first, and who is responsible for keeping them on track? Many critical decisions must be made during the first phase to lay the groundwork for a successful digital transformation.
2. Aligning data and analytics strategies with business outcomes
   While some companies are making strides, many today still view data analytics as a tech-driven project. Yes, technology is crucial to any successful data analytics implementation, but it is not the starting point. Instead, you must identify the business outcomes you hope to achieve first and then identify how you will collect, extract, and analyze the data necessary to achieve your goals. According to a Gartner survey, when Data and Analytics teams are involved in developing the overall business strategy of their organization, see a consistent increase in business value by a factor of 2.6x.
3. Too much data, too few insights
   In 2018, Forbes stated that “Over the last two years alone 90% of the data in the world was generated.” While more data can be useful, in many cases, it just leads to major data quality challenges. According to the State of Data Science 2020 report published by Anaconda, data scientists spend 45 percent of their time preparing and integrating data for analysis. Instead of analyzing data, most in-house data analysts wind up spending the majority of their time wrangling it.
   
   Why is data quality such an issue? Many companies collect data from a myriad of sources, including ERP systems, CRM systems, sales systems, HR systems, social listening commentary, customer surveys, and third-party data—you get the picture. When employees pull data from multiple disconnected sources, they generally find discrepancies. And without clean data, the rest of your digital transformation becomes more challenging because it has been built upon a foundation of poor-quality data.
   
   “It was like driving a car at night with the windshield blacked out. At some point, we were going down the road, but we had no real indicators of what we were about to face and what actions we should take.”

   Chief Information Officer
   Global Medical Device Manufacturer
4. Lack of data governance strategy
   That poor-quality data we mentioned in the previous paragraph stems from a lack of data governance. A carefully considered data governance strategy will empower companies to effectively store, cleanse, and manage their data assets. Unfortunately, for many companies, this is where their strategy stops. In reality, not only do the datasets change over time, but so do the customers you’re targeting, the tools you use, the regulatory data privacy laws you must comply with, the resources you have access to, and even the business objectives you’re trying to achieve—all of which require nearly constant monitoring. A viable data governance strategy should help you to direct and manage change in the people, processes, and technology across your organization.
5. Inadequate resources
   Collecting the right data is a necessary first step, but how do you act on it to drive the results your company needs? That requires data scientists that understand your business objectives, know how to identify the right models, and utilize AI effectively to help you build optimal predictive and prescriptive models. “Every data scientist must place enormous importance on learning business knowledge related to the problem they are solving,” said Ashish Singru, Senior Director & Head, Global Business Analytics Center, eBay in a conversation with Analytics India Magazine. Unfortunately, the combination of business knowledge and advanced skills in analytic tools is in high demand and can be difficult to find, which often leads to the development of AI or ML models that do not deliver the results you need to solve your business problem.
6. Getting useful data into the hands of those who need it
   Once you have the right data and tools, how can you enable your employees to use that data to make better decisions? Often referred to as “data democratization,” proponents of this initiative believe that it’s essential to distribute information across all functions of an organization to empower decision-making. However, many companies struggle with the cultural changes needed to integrate and connect the people, processes, tools, and information necessary to propel and maintain this type of digital transformation.

What do data analytics consultants do?

Tackling all of the challenges that arise when adopting a comprehensive data analytics approach can feel like navigating uncharted territory. How do you prepare for the journey? You could aimlessly set sail in a small sailboat and hope to get to your destination OR you could hire an experienced companion to guide you on your journey.

So, which do you choose? The one-man sailboat or the trusty guide and his arsenal of wisdom and tools? Unless you intend to make your own episode of Survivor, we both know which decision is the better one.

The truth is most companies DO need a companion guide for this digital journey. The best data analytics consulting firms will help your company soar by creating and implementing business-relevant end-to-end solutions for you. Your data analytics consultants will guide you through this process by understanding your data landscape, developing a results-driven strategy, recommending the right data architecture and tools to achieve your goals, and providing ongoing support as needed.

Most data analytic consulting firms can help you develop and implement advanced analytics models utilizing big data, IoT, AI, and machine learning with your business outcomes and success metrics in mind. Your consultant will also help you put in process change management plans to drive the adoption of new tools and analytics across your organization.

What are the benefits of hiring data analytics consultants?

At this point, you should have a better understanding of the challenges in adopting a data analytics approach across your organization. Many companies never get a chance to start the process because the resources they lack are in high demand and hard to secure. Our partner, ThoughtSpot, says, “Despite incredible education in data and statistical methods, undertraining in business applications and domain expertise is keeping data science from delivering the value.”

The good news is, the services provided by data analytics consultants can directly help you overcome the challenges that your company faces and bring with them the necessary industry knowledge and business acumen to deliver that value. The best analytic consulting firms will also work closely with you to develop effective data solutions that stay within budget and meet your projected timeline.

Once hired, your data analytics consultants will integrate your chosen data sources into a data platform, whether a cloud-based data lake or on-prem data warehouse, or hybrid structure. Your data analytics consultant will ensure your data is clean and develop the predictive and prescriptive analytics models recommended to make timely and better-informed business decisions. They will also help you determine the best method to collect and share the data across your organization utilizing self-service BI tools and confirm the data remains reliable, compliant, and secure in the process.

For example, Wavicle’s client, a medical device manufacturer, had 12 ERP systems, which led to slow reporting, inconsistent information, integration issues, and, consequently, a lack of trust in the data. The manufacturer also had no single complete view of the customer or their transactional data.

“It was clearly evident, even without any people or any technology in that area, what was going on just by experience,” said the CIO of a Global Medical Device Manufacturer, during a webinar hosted by Wavicle. “It was like driving a car at night with the windshield blacked out. At some point, we were going down the road, but we had no real indicators of what we were about to face and what actions we should take.”

Global Medical Device Manufacturer’s newly integrated data foundation drives value across their organization.

Increases efficiency

Minimizes risk

Lowers cost

Empowers data-driven decision making

Enables business evolution
and growth

Wavicle’s insight platform became the one source of truth for the medical device manufacturer

1. Improved productivity and performance
   Went from 30 ventilators per week to 600 per day.
2. Increased First Pass Yield
   Went from 37% to 85-90%.
3. Lowered time spent waiting for shipment data
   Went from 2-3 times per week to 1 hour.

To solve this problem, Wavicle helped them devise a scalable strategy and integrated all the sources of data into a single cloud data warehouse to build a trusted insights platform for their executive leadership team. This enabled the medical device manufacturer to vastly exceed their 2020 business goals, driving the following results:

• Improved productivity and performance—from 30 ventilators per week to 600 per day
• Increased yield—First Pass Yield increased from 37% to between 85-90%
• Data speed—shipment data was now available within 1 hour instead of 2-3 times per week

Without the necessary business acumen and the strategic implementation of a cohesive and compliant data analytics platform, our client would not have been prepared for the unexpectedly high demand for their ventilators brought on by the pandemic.

Whether you want to analyze qualitative survey data using advanced natural language processing algorithms, improve demand forecasting after unprecedented changes in consumption, develop automated recommendation engines that surpass increasing customer expectations, or optimize your pricing strategy in real-time—there is a relevant use case to achieve your business goals.

In short, when you decide to hire a data analytics consultant, you are future-proofing your business.

What should you consider when hiring a data analytics consultant?

If you’ve made it this far, it’s likely that you’re planning to move forward with hiring a data analytics consultant. We know how overwhelming the process can be. The market is overcrowded and it’s often difficult to distinguish any noticeable differences between them.

For that reason, we’ve put together a list of the 7 most critical factors to consider when you begin your search to hire data analytics consultants.

1. Client-first approach
   Whichever data analytics consulting firm you choose, make sure they spend time assessing the quality and accessibility of your existing data. Your data analytics consultants should be working as a close collaborator with you to develop recommendations around the business problems you seek to solve. They should also be willing to offer flexible solutions that meet the budgetary needs of businesses within the promised timeline.
2. Support structure
   Who will be on your team? Will senior executives be involved? How accessible will the data analytics consulting team be? Will there be time zone conflicts? The ideal data analytics consulting firms have teams employed across the globe so they can offer round-the-clock support. That kind of availability will help to mitigate potential risks and ensure your digital transformation stays on schedule.
3. Technology agnostic
   To successfully implement the right data and analytics strategy, your data analytics consultants will help you identify the right tools to collect, integrate, store, cleanse, and analyze your data. Whether out-of-the-box solutions or custom architectures designed with your needs in mind, they will ensure you have the right information architecture to house and analyze multiple data sources. Your data analytics consultants should be well-versed in the best-in-class available technologies and work with you to develop a flexible solution that favors scalability and business growth rather than simply following the latest technology trends.
4. Business acumen
   This is an especially important consideration. We believe that the best analytics consulting firms come with business acumen and industry knowledge, and our partners agree. Data analytics consultants need to have a firm understanding of the business problems you’re trying to solve so that their recommendations are developed with your specific needs in mind.
   
   Data analytics consultants need to have a firm understanding of the business problems you’re trying to solve so that their recommendations are developed with your specific needs in mind.
5. Advanced analytics focus
   The data analytics consulting firm you choose should be a leader in developing cost-effective solutions that are scalable while reducing risk and enabling you to make more informed, data-driven business decisions. The best data analytics consulting firms will also help you transform your data analytics by developing custom advanced analytics models that leverage machine learning, AI, and cloud strategy to deliver more robust data analytics solutions aligned to business outcomes.
6. Nimble and ready to scale
   The best data analytics consulting firms are nimble enough to tailor services to meet specific requirements. They should be prepared to address changing business and market conditions and be proactive in anticipating client needs and associated risks. Speed is a critical component of successful digital transformations. Your data analytics consultants should offer suggestions to increase speed-to-market to reduce timelines and costs.
7. Success metrics
   Finally, the best data analytics consultants prioritize business outcomes to measure the effectiveness of their solutions. They should have documented examples of successful initiatives they have developed. They should also have customer references who will attest to the success of the programs they’ve supported. Questions you should ask include: How successful was the data analytics solution for the client? How did they measure the results? Once implemented, will different metrics need to be used to measure the success of the data analytics solution?

Are you ready to hire data analytics consultants?

Hiring data analytics consultants can be an overwhelming process. You may find the evaluation checklist we made to be especially helpful in your search to find the best consulting partner for your data and analytics journey.