Is data the great equalizer for helping medium-sized companies compete with larger, more established organizations?
Large corporations, many of which are listed in Fortune rankings, can have several advantages that mid-sized companies don't often have. They might have the backing of investors or shareholders, and they might benefit from greater access to global markets. Their internal teams can be bigger, and their brand can be stronger.
Despite these strengths that larger corporations typically enjoy, mid-sized organizations can still win business against them if they find a competitive advantage. One advantage for a mid-sized business might be with the insights and knowledge resting within their organizational data.
Data comes in many forms, such as information about customers, social media, website activity, corporate finances or internal documents. To help get the most from data, here are five data management strategies for mid-sized companies that can help them better compete against larger-sized organizations.
- Data Management:
From my experience, I've found that many mid-sized companies have an inadequate data management strategy. This might be due to a lack of resources or not fully understanding the power of data. Sometimes, the amount of data companies possess simply overwhelms them. When the mindset of "our data is a problem" creeps into the corporate circle, the company is at a disadvantage.
A company can transform its data into an advantage with a modern data estate. A data estate can consolidate and integrate all current and future data sources into a central repository to ensure "one version of the truth." This holistic view approach can improve the accuracy of updates, analysis and reporting throughout the company.
- Data Automation:
Managing corporate data properly requires multiple steps such as extracting, integrating, cleaning, transforming, loading, modeling and more. Historically, all of this work has been done by manual coding and repetitive tasks, both of which are time-consuming and expensive.
Today, many progressive companies are automating their data infrastructures to eliminate manual coding, decrease time to data, consolidate toolsets and, ultimately, improve data quality and reduce costs. Data automation can also provide automatic traceability and lineage to help support governance, compliance and regulatory requirements.
- Data Speed:
Traditionally, business users looking for access to data would have to submit a request to IT for review and approval before being granted permission to look at the data. No more, as we're seeing a growing number of companies providing preapproval for designated business users to have instant access to corporate data. This accelerates obtaining crucial information to answer their questions so they can make decisions on the spot — or what's commonly known as "data democratization." Doing so can also free up IT to work on more strategic initiatives.
Despite this growing trend, too many mid-sized companies are still stuck in the older model where IT permission is required, therefore decreasing optimal decision-making. This delay can reduce productivity and efficiency throughout an organization.
- Data In The Cloud:
The cloud alone can become an equalizer for helping a mid-sized company compete against a larger company. With the cloud, an organization can substantially improve speed, agility and scalability. Data in the cloud can provide a 24/7 analytics environment for relevant corporate users, accessible at any time from any location.
In addition, with some cloud programs, a company can have access to a suite of applications and a range of services that it otherwise could not afford, as cloud vendors could offer subscription models and "pay-as-you-go" pricing. Having access via the cloud to some of the latest technology and innovations could put mid-sized companies on par with what larger competitors with bigger IT budgets had traditionally used.
- Data Transformation:
Mid-sized companies should also keep an eye out for the latest technology innovations that might require on-premises integration to strengthen modernization and workflow efficiency. For instance, a well-suited data visualization platform for viewing data can pay dividends by helping to better understand data. Artificial intelligence (AI), machine learning, predictive analytics, IoT and blockchain are other technologies that many larger organizations have used at great levels and that more mid-sized businesses are now using. With a modern data estate, AI can work in concert with corporate data to perform deep analysis and provide recommendations to business users about suggestive actions.
The point is if you're a member of the late-majority crowd or tend to be a laggard when it comes to purchasing new technology, you might want to reconsider your conservative approach if you'd like to increase your competitiveness.
Data Wrap
With these five strategies applied, businesses can get the most from their data to improve collaboration and communication regarding daily work, product status and project management. Further, data insights can move a business to introduce products sooner based on market-demand data, react faster to an emerging industry trend revealed by data or adjust pricing based on consumer elasticity data.
In addition, data users within functional areas are empowered to make faster, better-quality decisions. For organizational departments, having a central platform speeds up measurement and adjustments for profit and loss, supply chain issues, inventory usage and other factors germane to their respective business unit. These strategies can make a company more agile and more competitive.
There are, of course, many other elements that could potentially make a mid-sized organization an attractive option versus a larger organization such as quality, pricing and service. What's essential to understand is that when business strategies are somewhat equal, data can make a substantial difference in aiding an organization to find an angle to better compete against an industry giant. Conversely, not having a data strategy and a supportive data estate in place to help leverage data insights properly can really set back a mid-sized company and hurt its chances of contending for new business.
This story originally ran in Forbes on July 23, 2020.