Today’s interview with CEO Matt Lescault of Lescault and Walderman will take a deep dive into understanding the realm of predictive analytics and how the focus shifts from the rearview mirror of historical data to the forward-looking road of future possibilities.
The subject delves into the significance of predictive analytics and we will unpack its role in steering businesses towards new horizons rather than dwelling on past achievements
What Is Predictive Analytics?
Well, let’s start by exploring some terminology that is commonly utilized and widely known. We are familiar with the concepts of trailing and leading analytics which pertain to the insights we gain from past data versus future predictions. When delving into predictive analytics, the focus shifts towards datasets and information that offer insights into our future direction rather than dwelling on the past. If we solely concentrate on our historical data, how can we foster change, growth, and differentiation? Continuously gazing into the rearview mirror will only lead to repetition. So for me, the key to getting predictive analytics right revolves around harnessing leading datasets that guide and aid us in determining our future trajectory.
What Software And Or Technology Can Be Used For Predictive Analytics?
I find this question to be a little bit funny because if I could go back and say what taught what software or technology cannot be used for predictive analytics. The software that an organization uses in general, typically is operational in nature. which holds a ton of data, both your historical data but also data that tells you about where you’re going or what’s been successful in your organization. The question is what software technology can aggregate that data, take all that information into one place, and present a set of information that is viably useful? What happens within organizations is that you have a multitude of technology that holds this data and those technologies are disparate or separate from one another and can’t really overlay or adapt to what the full picture is.
A lot of organizations will use their ERP software like Sage intact to do that because that ERP software can provide for both financial accounts and what we call statistical accounts or non-financial data. There’s also software out there like Domo and others that are data aggregators. And what that means is that they’re pulling from multiple sources and creating a dashboard visualization of your data across your subset. In the simplest of terms, if we look at marketing, and I do have a passion for marketing, even though some people want me to stay out of it 😀, with something like Domo, you can aggregate data from Google Analytics, Google AdWords, your SEO to get a total spend or figure out your actual costs. This even goes a step further and calculates the cost of other third-party products that you’re using, so you can start to overlay that data and that’s only in a small microcosm of the business. Think about the challenge of doing that in every part of operations that you have as an organization.
To learn more about Lescault and Waldermans Sage Intacct ERP modules click here.
What Are The Key Insights Lescault And Waldman Look For First When Analyzing The Data Insights?
This question is a hard one as I’ve been known to say it depends. And it really does. Every industry has different insights. When we are employed as an outsourced accounting consultancy it’s our job to find and compartmentalize the data. So that’s why we track what we call KPIs or key performance indicators by industry. A professional service firm is going to have separate criteria for data sets that are more important to how they operate than a manufacturing firm or an e-commerce firm. You will always have some high-level insights that you’re looking for, but they are dependent on an industry basis. That’s why it’s so important to align yourself with organizations and people who understand the field where you play and what matters to your business. There are different opportunities to grow what we call enterprise value or the value of your organization. If I take it to professional services I will look at insights into our gross profitability by department utilization because a lot of what we do is based on an hourly rate however that doesn’t mean that you have to track hourly. It is important to understand the utilization of your staff and how efficient they are at getting the job done. Also understanding what drives overall success with your client base. So in professional services, we look at time to completion, turnaround times, average client retention, and average client value. Those are key insights and the main indicators of whether we’re being successful as a firm.
How Does The Utilization Of Predictive Analytics In Financial Forecasting Provide Businesses With More Accurate Insights Compared To Traditional Methods?
Traditionally, there was a lot of emphasis on historic financials and evaluating those historic financials to guide decision-making for the future. I think a shift has occurred over the last decade, where there was an understanding that technology, as a tool for businesses, rapidly develops, scales itself, and provides additional capabilities. If you were solely looking at your historical data, you weren’t capturing what was possible for the future. So, predictive analytics, which involves benchmarking against others’ data, is not just about your data. I had an acquaintance, the head of a local regional bank in the DC area. He said, “We’re not one of the big five banks. We believe in following fast.” What he meant is, don’t try to be the trendsetter because you’ll never be one at that size. Instead, understand what trendsetters are doing, analyze their actions, and follow fast to establish credibility. Predictive analytics, to me, is not only about understanding your data for future forecasting but also about gaining access to other organizations’ data to shape decision-making.
To learn more about Lescault and Walderman’s outsourced financial planning and analysis services click here.
How Does Having The Ability To Predict Financial Trends Using These Data Insights Contribute To Strategic Planning And Expansion Opportunities For Businesses?
So I think naturally, if you can successfully predict financial trends and utilize the insights from your data, you’ll be in a position to make faster decisions. Your organization becomes more nimble. This, in turn, allows you to seize opportunities that arise. Every entrepreneur and business encounters consistent opportunities, but not all follow through. Many organizations miss out on these chances. The key difference between highly successful organizations and those that plateau is their willingness to take risks and seize opportunities, even when it may disrupt the organization. Predictive data and trends enable you to determine which opportunities align with your organization’s mission-focused agenda. Having experience in this, you wouldn’t want an accounting firm, for instance, to venture into offering marketing services, right?
Can You Provide Examples Of Companies That Have Experienced Significant Business Growth As A Result Of Incorporating Predictive Analytics Into Their Financial Forecasting Processes?
I can provide some examples at a higher level without pinpointing specific clients. What I would say is that organizations comprehending their industry’s trends invest strategically in less obvious areas. For instance, when a software company heavily invests in a particular product, and it gains momentum in your industry, you can strategically decide to invest simultaneously and gain traction. I’ve witnessed this both within our organization and externally with others.
For example, businesses thrive on partnerships, whether they involve software, technology, or other collaborations. Aligning with organizations possessing similar yet distinct capabilities can set you apart in the marketplace, creating opportunities. Companies experiencing high growth often embrace disruption in their day-to-day operations.
To learn more about Lescault and Walderman’s success stories click here.
How Do The Quality And Relevance Of Input Data Influence The Accuracy And Reliability Of Predictive Analytics Models? And How Can Businesses Overcome Data-Related Challenges?
In simpler terms, do you encounter issues with bad data coming in and resulting in poor data going out? The essence of this question lies in addressing data-related challenges to ensure the data you utilize holds value. To me, the answer always revolves around reducing manual processes and minimizing human intervention, especially at the transactional level.
The quality of data fundamentally hinges on the transactional component, be it financial, marketing, sales, or operational data. If the initial data input is accurate, you can effectively analyze and manipulate it. However, organizations heavily reliant on manual processes, such as human data entry or manual data transfers between systems, expose themselves to increased chances of errors and misinformation.
Another facet of data challenges pertains to data structure. During ERP system optimization, we often notice that clients, whether external or internal, tend to overly complicate their data structures. They expand dimensions and fields within systems to an excessively granular level. This complexity can hinder efficient data evaluation.
Recently, I was involved in an internal process where we reviewed our business reporting across various segments. We streamlined our reporting set from about 20 different items down to just seven. We found this approach had a more significant impact on data analysis. Simplifying the data structure allowed us to discover more efficient methods of data manipulation and analysis within the system, preventing unnecessary over-engineering.
What Advancements Or Trends Are Anticipated In The Field Of Predictive Analytics For Financial Forecasting And How Might These Developments Impact The Way Businesses Operate?
The number one item anybody should be talking about here is (AI) Artificial intelligence. AI is rapidly evolving and can efficiently handle data transactions, a capability it already possesses. It will continue to enhance this aspect, significantly improving data accuracy. It has already started to reduce manual labor and time invested in various processes and time-consuming processes. This transformation will influence our business strategies, with investments directed toward both AI and human resources to further develop and expand upon the information provided.
In my previous discussions, I have emphasized the shift towards accountants adopting an advisory role. This transition is required because our value as transactional practitioners is diminishing. AI will emerge as the primary driver of predictive analytics, emphasizing the importance of value-added advisory services.
To learn more about Lesacault and Walderman’s custom accounting software and system implementation services click here.
How Can Businesses Stay Agile In The Adoption Of Predictive Analytics As Technology And Mythologies Evolve Over Time?
So it’s becoming harder and harder for businesses to stay abreast of all the changing dynamics within technology and the business community in general. As we become more global as a society and as individual businesses, we are forced to react at a pace that is hard for any one organization to maintain the required internal knowledge to be effective. This is why businesses should consider outsourcing this function, but the real question is why should businesses consider outsourcing in general? By investing in outsourcing providers that focus 100% of their time on that one subset of capabilities, they are more likely to stay ahead of the curve than you as an individual business.
At Lescault and Walderman our business model as an organization is doing what we do best, investing in what we do best, and hiring third-party providers that can deliver the knowledge base. This is why our clients come to us because we deal with accounting technology every day. We know what software is best and how to implement that accounting technology quickly and effectively. Over the years we have seen how different organizations operate in their industry and what works for them to be effective and agile. This experience gives us insights that any one individual couldn’t have. We are an organization of many brains coming to one solution as opposed to a few brains coming to many solutions.
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