In circa 2012 the Income Statement and Balance Sheet continue to be two central sources of information needed to assess a company’s financial health – and, in some cases used to judge how best to run it. Interestingly the present day balance sheet, a company’s primary statement of financial position, received its modern form in 1868. The income statement we use today, which is a company’s financial statement that indicates how revenue is transformed into net income, was defined in the 1930’s.
It is not my intention to dwell on the riveting topic of the history of modern accounting! Here is the point: The signals of health in a business we have been trained to look for haven’t changed for a century or more, yet the amount of information available today that could indicate the relative health of a business is radically different. It’s sad to say, but Ebenezer Scrooge would be as adept in a board meeting today as the day that Charles Dickens conjured him up in 1843!
The amount of information available today is indeed tremendous, and it continues to grow exponentially. We all know this expanding universe via the term “Big Data”, which represents the aggregate of global data from private companies, government entities, social networks and the like. It’s grown to the point where we use the term “zettabyte” to describe it! (That’s a 1 with 21 zeroes after it). The issue is not just that we are dealing with copious quantities of data; we are also, dealing with data that has incredible variety – text, multimedia, social media, etc.
Ironically, with all this information at our disposal, we continue to use the same old lagging signals, derived from concepts like a Balance Sheet and Income statement as the key indicators of a business’s health! This happens not only quarterly and yearly intervals, it also permeates in our operational KPIs such as “revenue by region”, “cost per unit” and provides a rear view analysis of the business to drive our business in the present and future. Does it not seem incongruous that while the “noise” surrounding a business has increased millions of times over during the past century, the signals of health we look for in the board room haven’t changed at all?
While I am not proposing that customer sentiment on Twitter be added to an organization’s SEC filings, is it that crazy to consider utilizing that information to actively run the business? With all this new “noise” (e.g., constant generation of Big Data) shouldn’t we be grooming our companies to constantly scan for “new signals” that could be powerful indicators of future performance? My previous point on Twitter sentiment is a great example: Would you say that every manager in your business is aware, every day, of whether your customers are feeling positive or negative about your company? It may not be as critical to your balance sheet as inventory on hand, but it certainly has an impact.
Understanding and identifying new signals in all this Big Data noise within the context of the global digital economy is critical to any organization’s success. Fretting over the size of data is irrelevant, but rather we should occupy our time focusing on understanding what all this data is actually telling us! Some of us fret because we are concerned about our abilities to deal with the volume, velocity and variety of the data that we are being hit with. Well, there is good news on that front as well – we do have ways now to address this quite elegantly. Before I get into that, let us take a look at an example of a new signal.
So what are the “new signals”?
These range from the hopefully obvious, such as social sentiment analysis (what your customers are saying about you or a newly launched product), to the not-so-obvious examples like using NOAA (National Oceanic and Atmospheric Administration) data to predict shipping delays. And it includes signals that companies have been aware of but have proven difficult to measure, such as proactively reducing fulfillment gaps with real-time supply chain visibility and by predicting customer demand or improving the ratio of successful insurance claims audits by automating fraud detection. These signals vary by industry and are often a leading indicator of business performance.
In keeping with my earlier line of thought, let us consider a financial example. The Income Statement and Balance Sheet are at best rear-view measures of the top line and bottom line. They provide a snapshot in time of all that has happened, but very little, if any, indication of what is happening in the enterprise. For example, an online retailer with a subscription model experiences a massive drop in stock price because of poor Income Statement results. Further analysis indicates that there was a dramatic drop in subscribers (Churn) in one of their most profitable segments. It would stand to reason that a pre-emptive pulse-check on the churn could have helped stem the bleeding and perhaps prevented the reaction on Wall Street. This churn is an example of a new signal that could have helped this one enterprise run its business more proactively rather than look for explanations with a rear-view perspective. So how does a company gain the ability to know midstream that it has a problem or there is an opportunity going unaddressed? How will a company gain the intelligent actionable insights to make this happen? What is needed is the ability to ask complex questions going across the volume and variety of data in an interactive manner, and most importantly in real-time. How best to accomplish this?
Every company needs a real time data platform
We are so conditioned to the heavy construction, slow paced mode of gathering information and waiting days, weeks or months for anything meaningful to come back that we fail to look for anything better out there. The truth is that something better already exists – a real-time data platform – that can ingest the ever growing data elements that influence your business and compare them with traditional measures from the balance sheet and income statement, giving insight now vs. months down the road. This real-time data platform is based on SAP HANA and has extreme capabilities to collect, move, store and process massive amounts of data. It’s the latest innovation in storing information from any source and discovering new trends, patterns and behaviors in real time…all critical to gaining competitive advantage.
It is a revolutionary platform that’s best suited for performing real-time analytics, and developing and deploying real-time applications. Leveraging its unique ability to handle both transactional and analytical workloads fully in-memory, it delivers blazing fast results in real-time to your queries performed on live raw data. In other words, you can be reporting on and pondering on business events as they occur. No matter what new signal you need to focus on, you gain the ability with SAP HANA to zoom in on it in real-time thus enabling you to take pre-emptive action to stem the flow of negative influences and step up the actions that will bring a positive impact to your bottom line!
Every company needs a data scientist
I point out the capabilities of SAP HANA to illustrate the point that we no longer need to feel inadequate in the arena of measuring new signals. To be successful in the long run, we also need to make the discovery, definition, and deployment of these measures part of a new data-driven culture within the organization. Every company needs a data scientist. Companies on Wall Street have had these for decades. They just call them “quants” (Quantitative Analysis Experts). These are people that comb endless streams of information and look for NEW information, looking for trends, or signals, that could have an impact on a stock, bond or other trading market that would create advantage for the firm. So my question for you is: Who is your “Quant”, or, if you prefer a grander title, who is your Chief Data Scientist? Without this critical thinker in an organization, I fear that firm will be relevant to Mr. Scrooge a hundred years from now!
In order to run a 21st century business, it is imperative to pay attention to the many non-traditional signals that reflect your organization’s health. Do not be inhibited by the ferocity or variety with which data is proliferating – instead, focus on how best to tune into those new signals. Appoint your “quant” or Chief Data Scientist and leverage a real-time data platform, and you’ll lead your company beyond the balance sheet!