August 29, 2021
Ensuring Success by Partnering with a Mature Data Analytics Company
A New Vantage Partners 2020 Big Data & AI Executive Survey revealed that just 38% of respondents consider their organizations “data-driven,” and only 26.8% say they’ve successfully implemented a data-centric culture in their companies. According to Mention’s 2019 Data-Driven Mindset Report, only about 15% of businesses actually support data-driven decision-making.
As Big Data analytics enter the mainstream, those low numbers could lead to big problems. Businesses must learn to make sense of their rapidly expanding datasets to remain competitive—or even just stay in business.
While many companies are well aware of the importance of becoming data-driven, it’s not exactly easy to pull off. It requires a lot more than a handful of SaaS investments and some automated workflows.
Data analytics companies can help brands make sure they use Big Data right on all fronts: use-cases, tools, and data sources—plus the infrastructure and culture to support a scalable strategy.
Why Partner with a Mature Data Analytics Company?
From manufacturing and marketing to retail, healthcare, and financial services, Big Data has quickly moved from trend on the horizon to urgent priority across all sectors. While most organizations are aware of the benefits Big Data brings to the table and the risk of getting left behind, many lack the skills, tech, and culture to turn raw, unstructured insights into real business value.
Part of the challenge lies in the fact that Big Data analytics is often talked about as a single strategy or solution. The reality is, it’s a broad concept that covers a wide range of industries, use-cases, and technologies. Without the right skills or experience, it can be hard for companies to figure out where to begin. Working with a company that understands the data analytics landscape can help you put together a strategy built to fit your business goals, select the right platforms, and implement an organization-wide data culture.
Audit Existing Data Ecosystem to Determine Needs
The first step in implementing a Big Data analytics strategy is assessing the current state of your data landscape. You need to audit existing data sources, applications, platforms, and anywhere you’re collecting and storing data.
A few things this process should cover:
- Are there gaps or information silos preventing you from accessing insights? Data silos prevent companies from capturing the full potential of their Big Data initiatives. Your company might have multiple data sources that don’t connect. Or different departments might have different processes and naming conventions for capturing and categorizing data. Tackling silos can be tricky—it’s often a manual process that requires interacting with various departments and mapping out all available data and how it’s currently being used.
- Is there dark data containing hidden insights you weren’t yet aware of? Dark data is a term that describes the unused, often unstructured data that businesses collect during their business activities, but don’t leverage for other purposes: think old documents, transaction records, call logs, or web traffic. Many companies have no idea what kinds of insights they’re sitting on, which means missed opportunities and potential security risks.
- What kind of shape is your data architecture in? If you don’t have a Big Data strategy, your data architecture probably needs an update. Working with a data analytics consulting company means you have an expert to guide you through the process. They can make recommendations for incremental upgrades and help you prioritize the areas that stand to make the most significant impact.
The right data analytics partner can also help you identify your data sources and determine whether your existing data strategy is working. From there, they will work closely with your team to develop and implement a road map for building or modernizing a data strategy that aligns perfectly with your target objectives.
Identifying and Implementing Use-Cases that Align with Business Goals
As companies begin thinking about how to take on Big Data, they need to frame every decision around their business goals. According to Deloitte, most organizations use data to increase customer retention, attract investment, unlock new opportunities, and stay competitive in an increasingly complex business environment.
For each use-case, organizations must develop a data provisioning and management process specifically tailored to the problems they’re trying to solve. Otherwise, they risk investing in a weak data strategy with little impact on the bottom line.
Unfortunately, many companies kick off their data analytics strategy with only a vague idea of what they hope to accomplish. Either they’re pursuing digital transformation without doing research, or they’re (understandably) not quite sure where to begin.
The benefit of working with data analytics companies is that they help you identify hyper-specific use-cases and the appropriate KPIs to measure the impact of your efforts. Additionally, they can help you come up with a plan for phasing out legacy systems and develop an operating model.
Your partner should help you set targets, establish processes, and maintain alignment with core objectives as you implement your strategy. As you evaluate potential partners, make sure you ask about their experience working with companies in your niche market. For example, manufacturers may want to partner with a company that specializes in leveraging IoT insights to optimize their process.
If you work in an industry with specific regulatory requirements, like finance or healthcare, look for a company that has experience managing large volumes of sensitive information. Alternatively, if you’re a retailer looking for better marketing insights, look toward companies that have a record of helping clients improve lead generation and conversion rates.
Platform and Tool Selection
Working with a mature data analytics partner can help you ensure you select the analytics tools, hardware, and models to support your goals as well as the right datasets that need to be connected. As this recent article by TDWI points out that each advanced analytics solution comes with a unique set of data requirements. For instance, a self-service BI platform tends to work best with data that has already been somewhat standardized and has access to business metadata.
By contrast, data mining platforms rely on huge volumes of raw, unstructured data, and no metadata. That said, ensuring the highest ROI hinges on making sure you choose those raw datasets wisely. Irrelevant, inaccurate data creates a whole lot of noise, not to mention the unnecessary strain on your infrastructure.
Speaking of infrastructure, ensure your tech stack covers everything from security and processing to storing data and analyzing insights. Depending on your organization’s existing data capabilities, you want to look at data analytics companies that can help you set up dashboards and reports that present insights in a way that your employees can easily understand. Additionally, if this is your organization’s first major data initiative, consider looking for a data analytics consultant that can provide hands-on training once solutions are in place.
Implement a Data-Driven Culture
While change management isn’t officially part of a Big Data strategy, it may be the biggest factor in determining whether your initiative succeeds or fails. For companies without a data strategy, working with a data analytics consultant can help leadership define team roles and responsibilities and provide guidance as they take on the difficult task of eliminating silos and driving cross-departmental collaboration.
If you’re building a strategy from scratch, consider the following as you evaluate solution providers:
- Will you need help getting buy-in from the team?
- Do you need assistance in establishing a training program?
- Will you require finding workers with the right data science skills?
- If you need to hire, are you looking to outsource or hire in-house?
For companies with a data strategy already in place, look toward data analytics companies with experience helping you understand how to make data-driven decisions. Ask potential partners if they have experience in assisting companies in developing a single source of information or in breaking the habit of searching for data to justify pre-existing biases.
Becoming a truly data-driven company involves more than investing in a few new tools and using data to inform decision-making. For many organizations, it starts with the right data analytics partner.
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