Business Analytics: Just Another Passing Fad?
Suddenly, business analytics is the hot new thing. Does that mean it’s worth paying attention to?
In short order, business analytics has made a quick ascent to the top of many executives’ must-have lists. And as anyone who has been in business long enough knows, that’s ample reason to question whether this is just another passing fad – or a new capability that’s going to become essential for any company interested in making smarter decisions. So which is it?
Here’s the debate.
Move along, nothing to see here.
Same stuff, new wrapper.
|We’ve been doing what people are now calling “business analytics” for years. There’s nothing new here.||The difference here is a matter of depth and degree. Only a few years ago, even the best practitioners of analytics couldn’t have done a fraction of what they can do with the technologies that are available today.|
|New analytics tools are great, but they’re no match for the explosive growth in data over the past few years. Sounds nice, but there are just way too many signals to decode today.||Just like anything else, you have to attack this in chunks. Start with the business issues where you really need insight and collect data in a way that you can actually use it. This is no time to be defeatist.|
|Even if there is something new here, we don’t have the time or capacity to take on yet another thing – especially when the jury’s still out on its value. We’re going to sit this one out for a couple of rounds.||You’re overestimating what it takes to get a business analytics capability up and running. And once you have it in place, there’s a good chance that it will help you attack some of the other challenges holding you back.|
It’s the real deal.
Get used to it.
|While you’re debating it, others are already seeing real benefits from their investments in business analytics. There’s a first-mover advantage at work here. Time to get cracking.||Maybe, but it’s also really complicated. We have a lot of irons in the fire these days and to do analytics right we would have to shuffle existing priorities. That’s not happening right now.|
|The added computing power and ease of using new software, in addition to some new twists on the underlying math, really does open up new possibilities. That’s why adoption is accelerating in almost every industry and sector.||If software’s the big story here, I think we’ll wait it out – at least until there’s some interesting new math.|
|Today’s “fad” just might be tomorrow’s legacy approach. Because there’s a lot of brainpower being applied to business analytics these days. Scientists, mathematicians and developers are turning up new opportunities all the time.||So some up-and-comers are playing around with new tools. Where are the rocket scientists who are tinkering with the analytics model at the root level? I don’t see the talent to sustain this fad.|
Jane Griffin, Principal, Deloitte Consulting LLP
Business analytics has the potential to be a fad – but only if that’s how your organization approaches it. If you go just far enough to check the “business analytics” box on a strategic plan – buying some software, adding analytics staff here and there – you’ll get exactly what you put into it, or less. Window dressing that delivers shallow capabilities is on the fast track to irrelevance.
The executives I talk to every day are wrestling with business decisions where a better understanding of data at a very deep level can make all the difference. Take risk management and fraud detection, for example. It used to be that banks were the companies that had advanced analytics capabilities in place to keep fraud in check. But now other industries such as health care, life sciences and defense are using advanced analytics in similar ways – to detect patterns that show something is amiss. Corrupt practices, money laundering, embezzling, IP theft and more. Low-level analytics just won’t get you there.
Work your way through the list of ground-shaking developments in business today – none are areas where companies can continue to shoot from the hip. Pricing. Workforce trends. Health reform. Even security and terrorism threats. These are all complex challenges where advanced signal detection capabilities are critical. And the new generation of business analytics tools can bring those capabilities within easier reach than ever – as long as you don’t treat them like just the latest round of business hype. When business analytics technologies are hardwired into your business processes, the result can be a sharper view of the patterns and signals buried deep below the surface of your data. That’s no fad. That’s a serious competitive advantage.
A view from the Retail sector
Mary Delk, Director, Deloitte Consulting LLP
The retailers I talk with think business analytics is the real deal. Their problem is figuring out how to make it work in organizations that were built with a whole different approach in mind. Retail has always been about intuition – in a world of fickle customer desires, the person who can predict the next big thing is the one who wins. No algorithm could ever replace that. Right?
Instinct still has a part to play in retail, but the kind of predictive insight that can be obtained from business analytics is already proving to be a game-changer for some of the leading retail companies. Here are some of the things they’ve learned.
- Link analytics goals to business drivers. For instance, if your strategy is to be the low-cost provider, it may make sense to focus on supply chain analytics to reduce cycle times and cost. Wherever you decide to begin in applying deep analytics, keep it relevant – especially when you’re getting started.
- Make the case. A business case will help focus your efforts and help ensure you’re getting the returns you expect.
- Know your data. Good data is the fuel for insight. Make sure you know what you have – and what you don’t have – from the outset. It can save you a lot of grief down the road.
- Start simple. While it’s tempting to apply analytics in every corner of your business, start by picking your battles carefully. Put your energy into projects that can deliver measurable benefits quickly. A lot of retailers we work with start with pricing or customer analytics.
- Use what you have. You’ve been collecting a lot of data already, right? Feed it into your new business analytics tools.
- Run a pilot. Don’t feel you need to roll out an enterprise initiative when you’re just getting started. Create manageable pilots to tests hypotheses in the early stages and build out from there.
Analytics can help retailers make smarter choices that lead to real business value. Organic sales growth. Margin increases. Reductions in costs or spending. Talent retention. You name it and business analytics can probably help. But not if you sit on the sidelines and wait for others to show the way.
A view from the Insurance sector
Tami Frankenfield, Specialist Leader, Deloitte Consulting LLP
A passing fad or the real deal? To some extent, we have been doing one or more forms of business analytics in the insurance industry for some time. But have we really been leveraging our capabilities to gain both insight and foresight into our business? Business analytics is as much about looking into the future as it is about evaluating the past.
For the insurance industry, business analytics is about embedding insight into our operations to drive business strategy. So, what does that mean? It means that we can leverage the wealth of data we have to guide and evolve our decision making processes; processes such as underwriting a policy, establishing a reserve for a claim, or presenting the next leading product to up-sell or cross-sell to a customer.
Through business analytics, we can analyze segments of our business with a Business Intelligence tool, perhaps providing insight into pockets of our business that indicate adverse selection. We can then leverage this information to hone our underwriting guidelines. We can do this directly in the underwriting process through embedded analytics.
Through business analytics, we can leverage predictive models derived from claims analysis to refine the way we reserve claims at first notice of loss. Those same capabilities (and data) can be leveraged to detect claims fraud. Better yet, we can detect the indication of fraud directly in the loss report process.
Through business analytics, we can identify the buying patterns of our existing customers and derive propensity models. What better way to leverage that information than use it to predict the behaviors of our prospective customers? Take it one step further and we can combine the propensity scores with behavior analytics and embed these into our sales process, increasing the likelihood of presenting the right product to the right customer at the right time.
Business analytics allows us to leverage our information assets to gain insights, detect exceptions and identify patterns to drive integrated decision-making. Is the road ahead really that steep? The fact is that many insurance companies have the data foundation in place to enable business analytics. The next step is to capitalize on that foundation and take action through business analytics.
A view from the Life Sciences sector
W. Scott Evangelista, Principal and National Life Sciences Commercial Solutions Leader, Deloitte Consulting LLP
Without committed leadership from the top of an organization, the best answers will not find the light of day and the “my number is better than yours” issue will persist. The shackles of the past (standard reports with standard data) will inevitably bind companies to increasingly failing strategies. I believe it is time leadership embraces predictive modeling to enable more effective decision making.
So many companies when faced with gradual market shifts and increasing competition or strengthening barriers keep turning to old solutions and don’t recognize they are in the midst of new problems. Leadership with many companies react so slowly to change that the companies are often in dire straits before the mandate for change comes…usually from the newly appointed CEO.
The one advantage pharmaceutical companies have in leveraging predictive analytics is that most of them are so far behind the state of what is possible that they can learn quickly from other industries and adopt tested technologies to facilitate their rapid adoption.
If Pharmaceutical Leadership is not investing today in building broad capabilities in predictive analytics, they will soon be looking to leverage their vast experience on the lecture circuit. Leadership needs to embrace the notion that analytics can help them create and find insights that will yield competitive advantage and even if they don’t embrace it, they should at least be willing to do tests of the concept. In many ways, companies have been outsourcing these capabilities for years to vendors that do very robust statistical modeling and make recommendations on how resources should be allocated. This results in many companies getting the same advice (most use the same few vendors) and having no meaningful advantage.
It’s time for a change, the lecture circuit isn’t that interesting!
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