One thing is certain – data analytics will only gain momentum for the foreseeable future and will be at the core of countless new technology solutions. Reliance on Business Intelligence (BI) and Analytics now outweigh strategy as the key requirement in business planning. But what will business analysis look like in the coming years? How will today’s version of BI and data analytics evolve over time, and how can you ensure that your business stays competitive by using new resources that emerge?
There’s no doubt data analytics and BI tools are evolving at a rapid pace. According to one McKinsey report focused on the healthcare industry, “data analytics and information services will have the fastest growth rate at 16% to 18% over the next five years, while core administrative services are unlikely to see much growth due to automation.” Here’s what you need to know as you plan your company’s future initiatives.
1. Data Specialists Shortages Will Create Challenges
There is a noticeable shortage of qualified data analysts and data scientists in the market today, and this issue is expected to worsen in the short-term. Start planning now for a way to address it whether that be unique incentives to increase your company’s competitiveness in the market, or by creating a program to identify internal candidates and fund their training. Start today.
2. Wider Adoption By Business Users
BI and analytics tools will continue to focus on usability and increasing natural language that enables business users to extract data and create reports without needing to understand the underlying algorithms. Not only will this increase efficiencies and create further adoption throughout companies, but it will also help alleviate some of the problems created by the data scientist shortage.
4. Increased Reliance on Large Data Networks
Vast data stores sometimes referred to as advanced data networks will become increasingly valuable for companies to access. The plethora of consumer data contained therein can supplement a company’s existing customer data to complete gaps in the view of their customers and will enable them to provide more personalized services and potentially create new services to address unmet needs and desires.
5. Growth In Machine Learning Will Accelerate
The options created by machine learning and artificial intelligence (AI) are endless, and it will be a race for companies to harness its power and create new services that provide value in unique ways. Many industry experts predict that machine learning will take over the majority of customer service roles in the near future.
6. Managing Company Data Becomes Even More Challenging
As we’ve seen since the beginning of the data analytics and BI onslaught, managing source data and ensuring its accuracy and consistent format is paramount. The validity of the data ‘going in’ determines the usefulness of the data ‘coming out.’ As companies rely more heavily on this information to run their businesses, finding a way to solve this problem becomes non-negotiable.
Add to the challenge the continued increase in new data sources from omnichannel interactions, the ever-growing threat of security issues, and a public that is more aware and more cautious than ever about their privacy, and you can easily recognize the need for a significant investment in time and resources to address this challenge.
7. Interconnectivity Becomes Critical To Success
With increased reliance on new internal tools for data analysis and BI, coupled with an accelerated need to access external data stores, networks, and IoT devices, interconnectivity will be the key to building a cohesive data analytics machine for your business.
To stay competitive in the coming years, it will be critical to create a plan for securing talent and to plan well in advance for strategic investments. Also of high importance will be the need to create process strategies for maintaining clean data across all systems.
If you’re interested in learning more about any of the topics above or want to discuss specifics about your organization’s challenges, contact an experienced data analytics and BI professional to schedule a discovery session.