Overcoming the challenges of implementing a successful business analytics program: strategies for organizations
As the world continues to evolve, new technologies are opening up fresh opportunities for businesses and organizations to grow and solve problems. One area in particular relates to business analytics and big data. With so much insight and statistical formulas to draw from big data, businesses are now better positioned to solve existing problems and predict different ways to tackle potential ones within the organization.
Business analytics strategies consist of several methods and practices that can bring new revenue streams to light, uncover customer lifecycle, improve the quality of products and services, increase sales and nurture closer engagement with valuable customers. The potential of business analytics programs for organizations is immense. The best way to make the most of them is to ensure a precise balance between organizational, technical and cultural requirements.
In reality, these may prove to be a complex process, particularly for organizations that are new to the business analytics game. As a result, there may be a number of challenges that organizations will go through when implementing these programs. In fact, they may encumber the potentials that organizations look to gain from these processes.
It’s interesting to see that while an organization may bring in business analytics with the intention of solving problems, the challenges experienced may bring up other problems. Fortunately, the experiences of the foremost analytics leaders show that these challenges can be tackled, particularly if they are envisaged beforehand. Here, we dissect the different levels of challenges that business analytics may present and also find worthy solutions that can help organizations address them.
What is business analytics?
Simply put, business analytics is the collection and analysis of data to determine the success and growth possibility of a business. When business analytics is included in an organization’s plan, it typically includes the use of technologies, skills and methodologies to determine the performance rate of existing strategies. It is also beneficial to the organization’s leaders when assessing the strengths and weaknesses and working towards creating a more effective strategy for the business. The essential components of a business analytics program include the following:
Descriptive analytics uses statistical analysis to identify trends in existing data. All descriptive analytics seeks to do is draw attention to existing patterns in data. A good example of descriptive analytics is KPIs (Key Performance Indicators), as they collect the different levels of data that provide the required metrics.
On the other hand, this type of analytics is more advanced. It creates predictive variables that determine identified patterns that will be used to develop future behavior. This analytics category comes through when determining the strategies that could apply and work best in given scenarios.
This third type of analytics goes all the way to apply research methodologies and management styles to determine the precise action that will help in achieving a set goal. Prescriptive analytics ensures that collected data can be compiled into models that help improve business decisions. These identified patterns will provide more information and proof that will improve business growth if done properly.
Major challenges associated with the implementation of business analytics
It is envisaged that by 2025, about 463 exabytes of data will be generated globally. For organizations, the particular business analytics challenges that will be faced will depend on the specifics of the organization. However, some major challenges are associated with business analytics programs, and they include the following:
Poor collaboration between the key stakeholders
One general challenge that big analytics has within organizations today is that the major stakeholders handling the essential parts of it, from evaluation down to implementation, are not typically in sync. For business analytics plans to work across boards of departments within an organization, it’s important that teamwork and collaboration are championed.
This is essential to the business and IT departments, as they are the major drivers of development in the area of business analytics. When these stakeholder units work together, it’s easier for objectives to be laid out and achieved for overall business development.
Getting carried away by the glamor of the latest technology
Undeniably, it’s easy to get carried away by the buzz of IT and the latest technologies of today that an organization forgets to invest in the right ones that align with business goals or ones that will bring about the required results. From artificial intelligence to predictive analytics and machine learning, so many investments can be made in the area of technologies that it’s easy to go over budget or even out of line.
Surely, global organizations are and will continue to gain immense value from investing in the latest technologies. In reality, however, not all variations of intelligent software can generate clear value for all businesses.
Overdependence on either C-level or traditional organizational flow
In every organization, having a C-suite committed to creating a data-driven business is vital. However, a top-down mandate is insufficient to ensure analytics become widely accepted throughout the organization. In addition to these senior-level initiatives, the organizational flow needs to get as far down as the grassroots project level to ensure that business analytics is woven into the organization’s essence. Neither should it be left solely to this group to decide how the organizational flow goes. Instead, it should be a balanced effort.
Failing to build a data culture among employees
Beyond just adopting new technologies, the business also needs to ensure that a culture of data and analysis is built into the employees of the organization. Business executives often skip the part where employees are taught and supported to utilize the new technologies and systems and expect the same output level as the organizations that have technology ingrained in them.
The employees will be the ones to engage with these new technologies directly, so the desire to use and understand them needs to be passed across to employees as well. One reason business analytics may not work is constant pressure on employees (lower-level ones in particular) to utilize and maximize the systems when they have no strong know-how or support.
Overlooking data security and protection
The truth is, with more use of data, there’s a higher chance of security breaches. Since business analytics is essentially the use of data, when the data is disorganized, the business is opened up to more security threats.
Organizations that are quick to overlook the need for security and protection of their data may experience a number of challenges as they begin to go through the business analytics process. The more tools and software added to your business strategy, the higher the chances of security risks if potential threats aren’t adequately provided for. Some potential threats that may oppose the growth of business analytics include unsecured data sources, non-compliance to privacy laws and unprotected stored data.
The rigor of consolidating data from multiple sources
Irrespective of size, there will never be just one source of data within organizations. From websites, emails and social media platforms to financial reports and CRM portals, there are a number of places where data comes from and in varying formats. Data and metrics come from various disjointed sources, and if care isn’t taken, it could pose a serious threat to business growth.
While trying to consolidate the data from multiple sources into one place, business analytics may encounter one of its biggest challenges. First, trying to compile data manually may be a much longer and more complicated process. Then, there’s a higher chance of encountering errors, and a simple consolidation error will, without a doubt, render the entire data set unreliable.
Failing to build on success
Finally, one mistake that many organizations make that poses a risk to the development of business analytics is failing to build on existing success. Within a number of previous strategies, there’s a chance that there have been instances of success here and there from different departments within the organization. A lot of times, these successes have helped the organization as a whole to gather insights from the collected data and make decisions for considerable success.
A number of times, just a few departments have championed these efforts, but rather than allow the efforts to go to waste, it’s important for the business as a whole to adopt the resources and style that has been introduced. An organization that fails to build on existing success has a lower chance of advancing and handling bigger business analytics needs.
What are the solutions to these business analytics challenges that organizations face?
While we have highlighted the challenges that businesses face with business analytics today, it’s also important to point out the possible solutions that we can work with. Here are some solutions:
Creating a cross-functional analytics team
In an attempt to solve the existing problem of poor collaboration between key stakeholders, business leaders should endeavor to create cross-functional analytics teams. They should consist of employees within the business, technology, legal, operations and HR spaces to encourage the use of analytics in their individual departments and across the organization.
Evaluating the analytics software being introduced into your organization
Don’t invest in new technologies only because it’s the rave of the moment. Rather, carefully assess the needs of your business and consider the major drivers that need specific applications to push for desired outcomes. Ask the necessary questions and determine whether the techniques or technologies being introduced will indeed help your organization achieve its specific goals. These specific goals may mean increased productivity, development of improved products and saving costs, among others.
Don’t be swayed into investing in buzzy technologies that may not only have no effect on your business goals but also affect the efficiency of existing methodologies.
Including data adoption as an essential part of company cultures on all levels
The first step for any organization looking to inculcate data into its company culture is assessing the existing expertise level of employees in regards to analytics. Take surveys, ask questions and compile reports in order to identify the analytics-savvy level of your organization stakeholders, right from the C-level down to the grassroots workers.
Another reason why it’s important to take honest assessments is that it becomes easier to detect the talent gaps that need to be filled. These surveys often highlight the need to hire new staff members or divert existing staff members to take up new roles. These existing staff members who take on new analytics-based roles will typically do so because of their expertise. They can also influence their teammates to adopt new styles of working until the point where a concrete data culture is spread across the entire organization.
Working towards changing the line of thought of employees is an important way of solving the problem of over-dependence on a specific level of workers to apply analytics. When business leaders create a culture around understanding and using data and find ways of educating or supporting employees, it becomes much easier to navigate the hurdles of business analytics.
Implementing an effective data management strategy
Aside from using data for an organization’s business analytics, it’s also important to ensure that your data plan is fit for the business, both now and in the future. This involves outlining a data management strategy that works best for you.
A good data management strategy also makes plans for data security and protection. It not only cleans up databases to ensure that all existing data is up to date without any form of invalid, duplicate or outdated data, but it also plans for backup and integration platforms that ensure a nice play between the different databases.
Also, focusing on creating a centralized data center for an organization makes it much easier for employees to get accessible information whenever it is required. It also frees up time spent on data consolidation and helps all stakeholders measure data from across different channels.
Making plans for concrete data security
From the moment an organization decides to adopt analytics into the business, it’s important to make plans for possible security concerns. This can be largely guaranteed by hiring the right cybersecurity professionals to safeguard the organization’s data, conducting different corporate training programs on data use and management for all stakeholders across the organization, using the right data analytics tools, encrypting data with protected login credentials and controlling access rights.
Identifying business initiatives that deliver positive results
To ensure continuity and the ability to build on previous success, an organization’s analytics team needs to ensure that leads who promote data-driven decisions are highlighted and properly documented. Ensure that previous positive results are used to promote the wider adoption of analytics across the organization. This makes the entire analytics process easier and justifies the investments made in these advanced tools. Undoubtedly, cross-departmental successes are the social proof that departments across the organization need to motivate them to adopt analytics.
Without a doubt, there are a number of prospective challenges that abound for organizations striving to expand the use of business analytics for competitive advantage. Some of them are foundational issues that arise from the onset, while others result from procedural decisions that are made on the way. As we have seen, leaving these challenges unattended will cause a number of difficulties for the business. One major key to avoiding this is ensuring that as a business owner or stakeholder, you are well equipped to handle whatever problem that high-demand roles in data may bring your way as you journey through your career.
If you enroll in an online business analytics master degree program at an accredited university like St. Bonaventure University, you will learn about the intricacies of big data, including data collection, data cleaning, data modeling, data visualization and data analysis techniques that are used to extract insights and drive business decisions. The key is ensuring that you’re well-equipped to handle challenges and remain a problem-solver, and all of this can be gained from practical and advanced knowledge of big data for business.
The first key to solving problems is becoming aware of them. When we know what the problem is, it becomes much easier for us to put strategies in place to handle them. A good understanding of the challenges of business analytics and their potential solutions will also help you as a business stakeholder to implement them, both on a small and larger scale.
The possibilities of big data for businesses today are boundless. The existing challenges are not enough reasons to prevent you from utilizing these gold mines for your business. Rather, be solution-minded and find ways to use them to your advantage today!