Almost across the board, businesses are asking themselves. “How are we going to grow our business to the next stage?” No matter what industry you are in, using your company’s data is imperative to understanding how to scale, and at what pace. We’ll look at ways that data can be leveraged to turbocharge your business scaling strategy.
So now you have "big data"
“Big data” was traditionally the term for data sets that were too complex for traditional data-processing applications to deal with. Today, we have access to tons of data, and the means to process and analyze it. That begs the question, what's next? Here are 5 tips on how to tap your data to scale your business successfully.
#1: Improve Productivity
The correct use of data can be one of the key drivers to increase productivity. This can be in in terms of boosting output, or being more efficient - including ensuring that the right people are focused on the right tasks. As McKinsey notes:
“...better data integration across a range of internal and external sources can cut down on search times and help analysts, auditors, and others spend less time tracking down information and more time applying the results. Professionals can run the numbers on much bigger sets of data, do better vetting, and do it all faster, allowing specialists to apply their skills in other ways. While AI and machine-learning tools do require a more significant investment of time and resources, many other capabilities can be created using tools and systems that most organizations have in place today, and then refined from there.”
Data can uncover areas where productivity can be improved: whether it’s production levels at a manufacturing plant, or the numbers of a nationwide sales team, failing to leverage business data in order to scale is a huge missed opportunity.
As McKinsey conclude, “virtually every organization has valuable customer data assets that could be put to better and more active use”.
#2: Increase Opportunities
Research suggests that companies effectively leveraging customer behavioral insights will outperform peers by 25% in terms of gross margin, and an incredible 85% in sales growth. Such insights are driven by data.
For some businesses, it can be as simple as as stocking certain products together. For others, it may be insights into the buyer’s journey, effective retargeting, or appealing to the customer at exactly the right time and place.
Many of these trends, patterns, and opportunities would not be available if it wasn’t for the ability to query large amounts of data. Now, big data analytics tools can uncover these opportunities. While some of these could be uncovered anecdotally - for example a sales person noticing that people buying a certain shirt would often buy a specific belt - this is certainly not scalable.
For uncovering scalability opportunities, and using them to scale your business, data is key.
#3: Reduce Bottlenecks
Most organizations experience bottlenecks of some kind; a process - or part thereof - which holds things back and, if this bottleneck is eliminated, will result in increased efficiency for the organization.
The “traditional” bottleneck is found in a manufacturing environment. For example, an auto part might have to be galvanized. The process may take time, as only a certain amount of parts can be galvanized per hour. This leads to a build-up of parts at this point in the process, and a bottleneck ensues.
Bottlenecks can be found in any part of the business however; from transport and logistics, to approvals and technology. Data is critical in identifying, and solving these bottlenecks and restoring efficiency to the organization.
Today in a manufacturing environment for example, data can be analyzed to predict bottlenecks, prevent overstock, and manage situations where certain orders spike. The same applies to any area of business, where the power of data used correctly can streamline process, remove bottlenecks even before they occur, and ensure scalable success for organizations.
#4: Streamline
When Matthew Beatty, a veteran data analyst, joined Payformance Solutions as director of analytics in 2017, he wasn’t exactly sure what to expect. He certainly couldn’t have predicted that through a deep analysis of data, his team would uncover $3.6bn in healthcare savings in a year.
With billions of claims and massive amounts of data, much of this would have gone unnoticed if it weren’t for Beatty and his team.
This holds true for almost every company and industry. Using data science in business, particularly when dealing with data that you already have access to, means you can streamline operations, cut expenses, and focus on scaling up.
#5: Achieve Personalization at Scale
Personalization at scale was somewhat of a “holy grail”, especially to marketing departments. The implementation of thorough data analysis, together with improved computing power and leaps forward in artificial intelligence and machine learning have finally made this a reality.
This has already resulted in websites displaying differently based on your past behavior and user profile, as well as personalized messaging and deep conversations.
The fact is, an email addressed “Dear Customer”, that goes on to detail winter specials, is going to have significantly less success than one that starts “Dear Zoe” and recommends outfits based on your purchase history (assuming your name is Zoe - if not, that would be a case of personalization gone wrong).
Using data to drive personalization at scale is an incredible way to connect and engage with customers, deepen existing connections, and scale faster.
Getting Data Right
Having the data is one thing. Accessing it, storing it, and querying it is quite another. For this, you need Panoply. Panoply is an autonomous data warehouse built for analytics professionals by analytics professionals. You can ingest data from all your disparate sources to one place, and use this data effectively to scale your business.
