The Real Value in Data Science Consulting

Data analysts will always have advanced training or experience in subjects like statistical data, numeracy, or computer programming. Their skills and expertise are extremely beneficial for any kind of organization. However, businesses might lose a lot of money on unsuccessful data science investments, especially if a wrong business choice is made based on the outcomes of a predictive algorithm. 

More and more, businesses are offloading, shifting, and outsourcing their data science expertise to data science consulting companies. This is why RTS Labs approaches corporate data consulting as a group effort. Once we help you put together the right team, we provide businesses with everything they need to handle almost any crisis.

To help mid-sized businesses boost productivity, efficiency, and decision-making in real time, RTS Labs develops customized, end-to-end machine learning infrastructure as part of its data management and data analytics solutions. 

However, it begs the question: how do you get something effective out of data?

Data analytics consulting firms like RTS Labs provide turnkey AI and machine learning solutions that lead data science projects for companies. These consulting firms can help companies create innovative strategies by applying advanced data analytics and smartly deploying these solutions. 

As the digital world continues to disrupt industries, it’s essential that consultants keep abreast of new technologies and techniques to ensure they stay ahead of the curve.

Many organizations think that to turn binary numbers into dollar signs, you need a lot of data and a team of expert data scientists. In reality, neither of these things is necessary for businesses to achieve success with data. They can, however, be quite useful if you utilize them well.

Hiring a data science consulting firm allows you to use the entire company’s data science expertise as you need them. In addition to providing actionable insights, data science consultants can also help you brainstorm and identify other problems that may exist within your company. In this article, we will discuss the challenges that have emerged in the field of data science in the past few years, and how it can help in different ways with consulting.

The Pitfalls

The data sometimes just isn’t there!

There is an important distinction that we need to understand here first. If data analysis and data science are really about how to use data, then data engineering is the study of how to make data usable.

Engineers are really the champions who make sure that machine logs and huge data stores can be used with big data toolkits. They do this by supporting the facilities behind the scenes. Engineers do not devote as much time trying to look at information as data analysts do. Instead, they take a gander at the hardware that stores the data and work with it. Data scientists work with the data, and data engineers work with the data pipelines.

When interest in data science shot through the roof, businesses started to recruit a large number of data scientists. However most of them did not yet have a data-pipeline setup, but they assumed data scientists would arrive and slowly add value. This did not happen, which is not a big surprise. 

Most data scientists do not know how to put together data pipelines. They work with information that has already been prepared and can be easily picked from a dataset that has previously been processed. Both sides were now distraught.

The data analyst was prepared to begin creating machine learning models when he got there, but he couldn’t. The company had put a lot of money into its team of data scientists but they were not making any money from them. These businesses, unfortunately, lost a significant amount of money and time by jumping on the machine learning bandwagon prematurely, just because it was attractive. 

Machine learning doesn’t necessarily apply to every problem

Machine learning is not a one-size-fits-all remedy to every issue. Decision-makers and managers who lack a technical perspective need to understand this first. Machine learning alone could not solve every issue and it should not try to either. People in senior leadership positions, on stakeholder teams, and on business teams often do not have a technical background. When they hear words like “data science” and “machine learning,” they automatically tend to get higher hopes.

The data scientist’s job is to bring individuals back into the present and explain clearly what is plausible and what isn’t. This is especially true when it is impossible to get enough data. Do not start developing or investing in a learning algorithm unless you are certain that computer vision modeling is the best way to go.

Building neural network models, especially ones that use a lot of data, takes a lot of computing power and can be expensive for an organization. After all, why spend time constructing a machine learning algorithm if the issue can be resolved with hard-coded rationale or simple estimations?

The Actual Use-Cases

Data science consulting makes it possible for businesses to talk to their customers.

Data science gives you a chance to connect with your customers in a meaningful way. Everyone lives and breathes tech. When businesses use data science, their customers are happier, more likely to respond to new offers, and less likely to opt out. In data science, this idea is often called “mass personalization.” Teams in charge of sales and marketing can use this data to learn a lot about their customers and market dynamics. With all of these new insights and information, a business can give its customers the best experience possible.

When we have the right data, data analysis helps us to get a better understanding of our customers and market segments. The real value of data science consulting comes from being able to take that information and incorporate it with other data sets. 

This lets you get more accurate and useful insights, which can be used to build a better picture of the target market and learn more about how it behaves. When customers are happy, businesses are happy and make money. Recently, there has been a strong organizational push toward measuring executives’ performance on statistics like:

  1. Cycle Time
  2. Opt-Out Rate
  3. Dispute Resolution
  4. Net Promoter Score (NPS)
  5. SLA (Service Level Agreement) Compliance

Once we know that data science empowers companies to open a dialogue with their clients and provides trustworthy, impartial, and forward-looking professional guidance, we can see that it is the essential ingredient in accomplishing the above user experience measurements.

Consulting helps businesses build that infrastructure. Many marketers and business leaders do not recognize data scientists as figureheads yet, which is a shame. Usually, it is just about reporting or running digital campaigns. Most of the time, people still go with their gut feelings or instinct when making decisions.

Organizations need to make a real effort to attract, recruit, and continuously develop leaders in data science, a position that consulting and advisory roles make easier. The exercise could otherwise be very overwhelming and time-consuming. 

There are many business leaders today who are actively seeking such a big change in their organizations. They were brave enough to hire and pick leaders who knew how to run a business, use math, and use technology.

Data science gives business advice that can be trusted, is not biased, and looks to the future.

There is a common misconception in the business world that you cannot mix business and math. Actual data scientists are entrepreneurs who know how to use math and technology to their advantage.

Companies that can see how valuable data science is treat their data analysts as business associates. Even so, there is an uphill battle raging at the moment because there is a strong idea that enterprise and data science do not go together. I think that the next big change in data science will be led by people with an advisory background or way of thinking.

You can make better decisions with the help of data science consulting.

Since data scientists can collect and analyze data from many different sources, this makes it possible for them to make big decisions with more confidence. Using the data they already have, data scientists can develop and implement models that suggest a variety of possible actions. This lets them figure out which path will prove to be best for the business. It does not help to make decisions and try out different methods if there is not a clear way to measure the results.

By hiring data scientists, you can determine and utilize the key metrics related to the significant changes and choices you have made, so you can measure how well they worked. This is true not only for one-off decisions but also for continuous or repeat business processes as a whole. With consistent access to the firm’s existing monitoring application, data scientists can debate the organization’s current approaches and procedures to find ways to enhance and develop them to incorporate more computational approaches.

Their job is to consistently enhance the value achieved from the users’ data, which enables the company to be more effective and successful. In the long run, as data scientists look at and study the business data, they are able to recommend precise techniques and approaches that will improve the organization’s performance, better engage customers, and increase the company’s bottom line by optimizing its data.

They can use quantifiable, networked, connected data-related methods to build predictive models. They can then employ these models to generate automatic notifications that help ensure a quicker response when unexpected patterns are identified or unforeseen circumstances unfold. This may save time, money, and resources in the long run.

The Real Value in Data Science Consulting

The bottom line

At the end of the day, it boils down to whether your organization has the data engineering capability it needs to fully utilize the benefits of data science consulting. Many programming partners now go out of their way to help companies build this infrastructure before providing additional services to best achieve corporate results. The advisory role of consulting lets partners leverage the power of data to help connect with customers, make better decisions, and do so much more.

Looking for the right software development partner? RTS Labs has helped hundreds of businesses of all sizes successfully develop the right outsourced custom software for many business needs. 

Get in touch with RTS Labs today to learn more about how we can help!