There is a classic recipe for surviving a crisis. You have to accumulate cash while you can – the cash that will nourish you through your financial hunger. You have to invest into R&D and routinely improve your processes – Japanese call this kaizen – to change for the better. You have to keep your savings, investments, and debts in healthy balance. You need to know your escape route in advance, the ‘rings of defense’ you will deploy when the crisis hits. You have to have a portfolio of businesses in independent industries, and you need to learn how to prioritize your projects and get rid of toxic assets. This is a huge burden to carry as an executive. You understand that you must rely on data while making decisions, because, as we all know ‘words are cheap’. These days, ignoring data is not an option, because your rivals are always exploring new ways to compete.

Business executives often suffer from poor forecasts, insufficient data, and misleading advice that directs them towards imprudent decisions. Eventually, they find their businesses unprepared for yet another crisis and they ultimately fail.

Before the Crisis: Monitor & Predict

In a crisis, stock markets fall, interest rates inflate, and the economy collapses. Worst of all, most of us don’t even see it coming. We know that crises happen from time to time, and we know that sooner or later another one will come. This is what our common sense tells us. But if we know that a crisis will come, why are most of us are in shock when it arrives? Because we never know exactly when the financial skies will fall.

Before a crisis, try to forecast as much as possible. Use predictive analytics wherever you have data. None of your data storage should operate without an algorithm that searches for correlations and predicts the next value. And none of your business units should operate without digital records and databases for data storage. Predictive analytics will reveal patterns in your business, detect deviations long before a human eye can do it, and spot stagnations that should send warning signals about upcoming disruptive change – i.e., a crisis.

Patterns are attributes of established economies before a crisis. Patterns tend to become stronger over time when an environment remains stable. In the established economy, businesses are mature, trade channels are developed, social networks are established, markets are occupied, and the rules of the game are written. These rules define patterns, which are sometimes too complex to recognize with the naked eye, but transparent to data mining algorithms and forecasting methods. Predictive analytics is a masterpiece of data science, and you have to know the art of data analysis to use it wisely.

However, if you can predict everything in your business, if you think you have found all the correlations, if your R-squared is almost 1, then be ready for the crash. Prepare for the crisis. Stagnation of smooth growth is against nature.

Business analytics is about using the right data, for the right people, at the right time. You are the right person, and today is the right time, which means you have to monitor your business. You have to have a reporting system, with a slick, cool look, one that’s mobile and at your fingertips, with up-to-date data presented in bubble charts, box and whisker plots, histograms and maps. Your business data must flow through algorithms that predict patterns and trends, find clusters and deviations, and bring brilliant visualizations to your reporting system. Remember: forewarned is forearmed. Robust business analytics is your digital shield from crisis.

During the Crisis: Optimize & Redesign

I spent a substantial part of my career with Corning Incorporated, an industrial company with a 160-year-old history. Can you imagine how many economic crises it weathered over those 160 years? Survival during crisis is all about managing resources. Analytics will not help you with your corporate strategy. Implementing business analytics is a strategy itself. Analytics will help you to organize and save your resources during a crisis, optimize spending, and improve business processes.

During the crisis, streamline your business processes, remove bottlenecks, minimize non-value-added steps, work hard to deliver quick turnaround and zero delays. Make the process robust and stable in order to maintain supply, with zero variability and optimal product quality. This is tough, but you have to do it. Business process modeling is the key to performance excellence. When you are short on budget, people, materials, machines – you should optimize, explore and exploit, and find the best combination of these elements with the help of algorithms.

Essentially, business is a process that converts inputs into outputs. Every business does that. In education, you convert newcomers into experts; in finance, you convert cash, assets and obligations into financial products; in any assembly industry, you convert parts into goods. The business process is a line of sequential steps that adds value to your product. What business owners usually want, especially during a crisis, is to make the production process cheaper and more efficient – in other words, to decrease the number of steps while retaining the product’s value. Analytics can help you with that. Actually, if you are serious about your business and plan to withstand the crisis, business process analytics is your lifejacket.

A common pitfall is to think that a value-added analysis and a value-stream map is the end point, when in fact it’s really just the beginning. During a crisis, you can’t run your business the same way you did before the crisis. This is obvious. You need to change – which, together with death and taxes, is one of three life’s three inevitabilities. You may like to summon a good, oldfashioned process engineer to learn best practices and unite your team, or call a consulting company to draw a new value stream map to eliminate non-value-added steps and redesign. You’ll likely end up with several options – several new designs for your improved process – but only one chance to try one of them because of time and budget pressures. But how will you know that you picked the best version of the new process? What if you could test your new process in a virtual world before investing in the full-scale deployment? And on that front, there is a technology called imitation modeling, or discrete event modeling. The latter is an industry in itself, and includes a number of software vendors and consulting companies.

During a crisis, your budget is a typical constraint. Not enough customers, not enough cash, not enough financial support from banks and investors. Actually, when your budget is tight, you have two options: to come up with a new creative solution through a business process redesign, or to carefully redistribute your resources, prioritize and optimize your budget allocation, and find an optimum balance. When your business is rich and fat, you can spend overspend. Life is good, so why bother to hold back? But during a crisis, every penny counts. And that’s when budget optimization happens. People only do it when something forces them to. In your case, this something is the economic crisis. If your advertising budget is low, then your sales are low. You want to see your sales grow, but you don’t want to spend a lot on promotion. Optimization seeks to balance the tradeoffs you need to make. Speaking scientifically, in the promotion budget allocation, you want to maximize the effectiveness of your promotional efforts for a given budget. These are your objectives and constraints. Direct-mail marketing; ads in magazines, newspapers, and web; public relations activities and social network pages; radio and TV advertising; search engine marketing – these are your promotion vehicles. But how do you allocate your promotion budget across these different vehicles to maximize the number of ad impressions? In the world of analytics, we refer to situations of this type as ‘optimization problems’.

Ironically, lack of revenue may force you to seek ways to increase your profit with the same goods in same market conditions only by optimizing the price. Why you have not done this before? How do you set the price for your products? There is a whole sophisticated methodology around pricing. In general, consumers tend to buy more when the price is low, and vice versa. We are not talking about luxury goods – we’re talking about frozen vegetables and pizza. They feel they can “stock up” at the lower prices in the short term. In the long term, they don’t continue to buy because there’s a limit to the amount of frozen vegetables they want to own, even when they’re offered at very low prices. The bottom line is that you can sell more at lower prices, and eventually gain more, through sales volume in certain market environments. The fine balance you have to find is called the ‘optimal price’.

When you optimize the parameters of your redesigned process, you may have to adjust dozens, even hundreds of factors to improve your key performance indicators (KPI). To do that, you need two things: a process model, or a function that links your factors with your KPIs and the optimization algorithm.

There are plenty of optimization algorithms. You’ll probably never encounter most of them but it’s good to understand what happens behind the scenes during an optimization. There are local optimums and global optimums like waves on an ocean surface. Some waves are high enough to suit your needs. If you’re an average surfer, these are the local optimums. But if you want the biggest wave – not because you’re desperate but because, like Mercedes, you prefer ‘the best or nothing’ – you want the global optimum. This represents the best possible combination of your process parameters, the best possible price for your product, and the best possible allocation scheme for your promotional budget. There’s always room for improvement (i.e., for optimization). So treat the crisis as an opportunity, be smart, and use analytics.

After The Crisis: Survey & Simulate

After a crisis, the world is never the same, and most experience is irrelevant. You learned your lesson. You knew you should have used predictive analytics before the crisis, and redesign and optimize your business as the crisis unfolded. God laughed at your plans and simply wiped out everything around you. The environment changed, you changed, they changed. Fortunately, life sometimes allow you a global reset. Now you need to start from scratch, and you need some inputs. You already tortured yourself with questions: ‘What if I’d held on to that contract?’, ‘What if I did that thing differently?’, ‘What if I’d known that in advance?”. Well, you didn’t, and here you are. Now it’s time to start using analytics from the beginning. To test ‘what-if’ scenarios, model outcomes, and simulate situations. It’s time to talk to people to collect the data and create your ‘Management Flight Simulator’. This is the term that experts at the MIT Sloan School of Management use to describe system dynamics modeling.

A cognitive map, or causal map, is a way to document your understanding of your situation on paper. These maps express your judgement that certain events or actions will lead to practical outcomes. If you do not have any understanding or judgment, then you head out, conduct interviews and draw the map. The map a set of nodes linked together by relationships. At first, you need to collect the information, or conduct ‘data elicitation’. A good example of data elicitation is a TV interview with a financial analyst in which he or she speaks about oil prices and speculates whether prices will go up or down. The TV host asks the analyst series of open-ended questions: ‘What can cause the oil prices to change?’, ‘What factors control oil prices?’ This unstructured data gathering – ‘elicitation’, or simply an interview – yields a richer understanding of a situation and important insights into existing knowledge. Linkage between the map nodes can be derived from listening for words in the analyst’s speech, such as ‘if-then’, ‘because’, ‘so’, etc. Another way to reveal relationships between the map nodes is to list all the variables and ask an expert to draw connecting links among them.

When programmed using specialized computer software, or even simply drawn on a whiteboard, the causal loop diagram, or the map, will help you understand dynamics of your system and your business. When all the parameters are in place, you can study the stability of your decisions for vulnerability to external changes. You can identify scenarios where your business will operate in a self-sustaining mode, and ones where it will be highly unstable, when even a small breakage can cause a disaster. I’m not talking about business process modeling here – although you can surely use system dynamics for that. I’m talking about interactions between different units and even organizations inside your business.

Okay. You’re recovering from the crisis. You talked to a number of people, thought long and hard, generated a new vision, considered what you’ve done wrong and what you can do better. Now it’s time to find your place in the sun and lodge your business in a market niche with a good climate where your business will start to grow. You’ve already conducted surveys and collected data about your customers’ preferences. At first sight, the data looked scattered, and each survey response varied in some way. You faced a new challenge: to find groups of customers with similar preferences for certain product attributes, and to define your market segments. Market segmentation is one of the tools to succeed in the market and match your competitors, who have also started to recover from the crisis. Luckily, using analytics, you can identify the groups of customers that desire your unique product or service. All markets have segments. Even commodity products, like laundry detergent, have segments: travelers prefer small packages for portability, while people with budget constraints prefer larger sizes to benefit from cheaper per-ounce prices. Identifying your market segment helps you focus your core competencies on the relevant markets and use your company resources more efficiently.

Always collect data as much as possible. Collect, record, store and analyze. Your efforts will pay off. Talk to people, conduct interviews and surveys, build cognitive maps and causal loops, use system dynamics and simulations, and run what-if scenarios. Collect every piece of information, don’t be afraid of vague data, cluster and structure your findings using analytics, find your market niche and your ideal set of product attributes – and start growing from there.

Final Remarks

Be serious about data collection and analytics software from the start. Educate your employees about the culture of data storage, and teach them how to use databases (or at least explain the basics). Avoid open-source code, free software, start-ups and fresh university spin-offs. Choose vendors you can rely on – i.e., those with at least a proven, 20-year record of market success. Use ‘all-in-one’ software suites that include data storage, data analysis, and reporting. Your business analytics system should be rock-solid, not something built from fragments and pieces.

Don’t mess with the terms. Don’t call everything ‘Big Data’. You have to clearly understand the new professions and job descriptions. Marketing analyst, sales analyst, financial analyst, system analyst, business process analyst – these are all different experts. Business analytics is a set of skills and technologies, not a profession by itself. You have to remember this fact when you will start implementing business analytics in your company.

Here is the list of methods recomended in a framework of SCANBA Anti-Crisis Analytics:

Monitor & Predict:

  • Searchable Data Warehouse: SQL & Hadoop
  • Transform & Load Historical Data (ETL)
  • KPI Dashboards with Predictive Analytics
  • Data Minings & Process Mining
  • Process Control & Analytics
  • Reporting Services & Alerting

Optimize & Redesign

  • Project Scorecards & Ranking
  • Portfolio Optimization
  • Values-Stream Mapping & Value-Added Analysis
  • Business Process Analytics
  • HR Analytics
  • Desicion Support Systems & Visual Analytics

Survey & Simulate

  • What-if Scenario Analysis: System Dynamics; Agent-Based Modeling; Monte Carlo Simulations
  • Bayesian Inference & Cognitive Map Analysis
  • Structured Surveys & Conjoint Analysis
  • Data Clustering & Market Segmentation

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