The good news for tech companies—you are in demand! However, being in demand also brings a unique set of challenges. As businesses across multiple industries become increasingly dependent on technology, tech companies owe it to themselves to study different business processes to help improve operations and better address client needs.
Since tech companies leverage data that help inform client strategies, it is only appropriate that the Technology, Media, and Telecommunications (TMT) sectors tap into data analytics to help predict business trends and influence strategies.
Think of data analytics as a Swiss Army knife with different “tools” that help organizations understand Key Performance Indicators (KPIs) that refine business strategy. This article will discuss two data analytics tools often used in business forecasting: Predictive Analytics and Prescriptive Analysis.
Predictive Analytics
Simply put, predictive analytics generates insights that leverage data assets. It can manifest itself in a simple forecast or a more complex outcome involving multiple macro and micro sensitive outcomes, each varying by scenario with intricate interdependencies. Armed with this information, the tech company can plot key trends such as revenue, cost, product utilization and adoption, process cost and optimization, and more. These and other KPIs can then be studied within time frames ranging from days and weeks, to months and years. Some tech companies even track daily users by the hour. These predictive analytics insights can help companies better anticipate market and consumer trends and use information to help manage cash flow, allocate resources and craft financial strategy. For example, by the end of a fiscal year, many businesses have exhausted their budgets and do not have resources to invest in technology services. With predictive analytics, technology companies can better plan for the cash flow impact during slower months — information that will help determine a company’s capital versus operational spending.
Natural Language Processing – Customers Speak Their Minds Predictive Analytics provides keen insights on trends using short qualitative surveys from a customer point of view. Natural language processing (NLP) dissects this wealth of qualitative information at scale, and the additional layer of data provides a deeper understanding of client sentiments and opinions driving technology purchases – great information for TMT organizations. This capability can be further leveraged to measure a company’s change agility and burnout, concepts that impact productivity and solution delivery. The Healthcare Consulting practice at FORVIS successfully combines two decades of research and cutting edge natural language processing to deploy a burnout analytics and organizational change management tool called Clarity. |
Prescriptive Analysis
Think of predictive analytics (WHAT) as what the data is pointing to in the future, and prescriptive analysis (HOW) as explaining the optimal future choices. This kind of insight provides organizations the necessary information to help develop strategies by analyzing multiple scenarios before investing time and resources to implement them. When organizations understand the prescriptive analysis approach, which considers economic objectives and optimizes them against key operational constraints, they will be armed with the necessary tools to develop a successful business strategy.
In the technology sector, change happens quickly, and TMT organizations must adapt their products and services to evolving client needs and innovative market forces. Predictive and prescriptive analytics can help tech companies identify and focus on target markets best suited to reach their business goals. In addition, predictive and prescriptive analytics help tech companies better understand business initiatives such as:
- Why tech solutions are successful or unsuccessful
- How well new tech onboarding services work
- Where automation can help organizations
- How to better align products/services with client needs
- Product development
How FORVIS Can Help
“To reach data-driven decisions, it is crucial to use efficient and effective data analytics,” says Amit Arya, chief data & analytics officer at FORVIS. The Data Analytics practice at FORVIS provides more than an enterprise overview; it combines technology, industry intelligence, and tailors data perspectives and applied insights that help grow and manage your business successfully.