The manufacturing industry and field service industry are facing a growing problem – how to capture tribal knowledge from an aging population of workers. At the 2019 Field Service Conference in Amelia Island, FL, this topic was widely discussed amongst industry representatives.
By: Dmitriy
When most people think of ML, they imagine a team of data scientists, high overhead costs for computer hardware and timelines that stretch into quarters or a year before seeing results. But today the market is filled with automation tools and cloud-based computing power. ML, AI, and Big Data are available more than ever. It is now easier for medium to large-size businesses to start using and applying these advancements in business intelligence technology to grow and improve their business.
One of the things I enjoy about our work in analytics is the variety of business problems we solve. While the specifics of the problem vary, our overall objective is always to derive value from the data. Putting the client’s needs first means that we adjust our approach to best fit the situation rather than fixate on a specific tool or pre-selected solution. This variety makes the work exciting, but it also creates challenges in staffing the appropriate skills. Over the years, I have come to refer to our solution to this challenge with the phrase “Analytics is a team sport.”
The term predictive analytics refers to the analysis of existing data to create forecasts that when properly applied, help avoid future problems. While kaizen helps spot problems live on the manufacturing floor, using predictive understanding methods provides an opportunity to:
There’s a reason why businesses are trending towards big data. Data analytics can be used to isolate areas of a business that need to be improved, in addition to paring down to the areas of the business that are performing most successfully. Through an internal audit, a business can fine-tune and streamline its business processes, ultimately using performance metrics to improve its productivity and revenue.
It’s often easier to reduce an organization’s costs than it is to increase its income, but the bottom line is the same — an increase in revenue. If you’re looking for ways to streamline your expenditures and improve your cost savings, it’s time to look at your analytic data.
Your expense sheet holds all of the information you need to identify potential opportunities. Identify your largest suppliers and vendors and begin there. Look for opportunities to:
Visualized, aggregated data gives you valuable insights that you might not be able to see on a spreadsheet. This is the premise behind big data visualization: large-scale patterns may only be visible once data is consolidated, analyzed, and visualized. Using the right software solutions, you can better understand where your organization is spending the bulk of its money. From there, you can look at ways to fine-tune your operations.
A supplier may not just be costing you money in terms of raw materials. Assessing supplier performance is also necessary to determine the full impact of their costs. Are delays making it necessary for your organization to delay products? Have mistakes in the supplier chain required returns or additional administrative processing? Supplier performance impacts efficiency, which can impact the system as a whole.
At the same time, contract compliance must also be enforced. If suppliers are required to deliver product under certain guidelines — and they are not doing so — then they are not performing up to their contract. Issues of compliance must be enforced if negotiations are to be useful.
In addition to making decisions based on current spending, you must also consider future spending. If certain areas of your business are about to grow and expand, then your organization needs to focus on developing out these sectors and reducing costs within them. If areas of your organization are starting to become obsolete, then their cost savings benefits are going to be minimal.
Data analysis is not effective if it isn’t used to affect change. Once your cost savings data has been analyzed, it’s time to make simple, clear, and functional changes to the spending of the departments that it impacts.
If you want to reduce spending in your organization, comprehensive data analysis is the most effective way. Through better data analysis, you can drill down to your organization’s spending habits, discovering inefficiencies and identifying trends. Of course, this also requires the right software and the right business processes. You can find out more through the experts at Starr & Associates.
For many decades, the healthcare industry as a whole was able to maintain status quo. In the last decade alone, however, it’s experienced a great deal of disruption. From self-service healthcare and patient self-advocacy to predictive analytics and big data, the industry is changing. From small clinics to large healthcare organizations, businesses within this industry must change with it.
In predictive analytics, historical datasets are compiled and analyzed for patterns. Once patterns are found, this analytic data is used to make predictions on future outcomes. Predictive analytics can be used for a wide variety of scenarios, ranging from determining whether a customer might leave the organization to identifying the products and services a customer may be most interested in.
Predictive analytics has existed for as long as data has existed, but it isn’t up until recently that the raw, computational power necessary for making accurate guesses was available. Organizations now collect more data than ever before and can use this data to make surprisingly accurate predictions.
Patient-generated data can now be analyzed to diagnose a multitude of issues. As patients are continually becoming stronger advocates for their health, organizations are going to see an increase in self-service healthcare. Patients are going to be pursuing their own diagnosis and are going to be identifying their symptoms. Patients are also going to be studying their billing and their medical costs more intently.
In the past, it wasn’t always necessary for healthcare organizations to be proactive about transparency. Though patients have always had the right to their own healthcare data (and the agency to make their own decisions), it wasn’t always a priority that patients understand every step of the process. In the new medical landscape, patients are going to begin to demand to be equal partners in their health decisions.
To compete with these new, disruptive technologies, healthcare clinics are going to need to take steps towards creating a more patient-friendly system. Collecting data is only one small part of this; clinics will also need to be able to reliably analyze and protect this data, both regarding confidentiality and security.
As patients become more knowledgeable and forceful about their rights as a consumer, healthcare professionals are going to need to be more customer-centric and patient-focused. This may create a radical shift in many business processes and business operations, especially in terms of customer acquisition and retention.
Healthcare organizations are in for some significant and immediate change as the industry is in the process of being disrupted by new, advanced data technologies. At Starr & Associates, we can help. Contact us today to find out more about the disruption that could be headed for your business.
The modern business world is an infinite jungle of data. Navigating this tangled landscape requires focus on meaningful information and skills to transform it into actionable insight.
Nearly every company goes through some organizational growing pains. One common development, departmental silos, occurs at some point. Successful companies break down a silo, a department that protects its information, keeping it from other departments. Silos cause growth breakdowns, so continued growth requires their eradication.
