Spreadsheets

Spreadsheets are excellent tools for combining and analyzing data. Excel, probably the most popular spreadsheet program, has extensive capabilities for visualizing data (charts), analyzing data (statistical analysis), and summarizing data (pivot tables). Its powerful and relatively easy-to-use formulas make complex calculations and logic possible, allowing you to link data from many sources to find the answers you need.

However, spreadsheets are not such a good choice for collecting and storing data. Without robust access and editing control, it is easy for any person who is editing a spreadsheet to accidentally delete or overwrite existing data. Even more problematic, if there are formulas in a spreadsheet, changing its layout can break them and result in incorrect calculations that are difficult to detect and fix. Finally, the limitation of the flat sheet structure in spreadsheets makes it cumbersome to collect and store data that contains complex relationships.

Do: Use spreadsheets to combine data from multiple sources, analyze your data for a deeper understanding, and visualize and summarize your insights to communicate them to others.

Don't: Use spreadsheets as your data collection tool, your data storage solution, or when multiple people need access to the data.

Databases

Databases, in many ways, have the opposite strengths and weaknesses of spreadsheets. With a powerful relational model, they can store the many, complex relationships that exist in today's data (e.g. a customer that is also a supplier and/or an employee; products with multiple configurations and styles, etc.). Robust access controls and a server-based architecture provide simultaneous access to data by multiple people while ensuring that only people with permission can access and change the data.

Unlike spreadsheets, databases can be more difficult to use for analysis and reporting. Their relational model splits data among multiple tables, and knowledge of special querying languages (usually SQL) are necessary to pull data out. Most databases do not have built in reporting or analysis packages. Though there are often related offerings that can bring that functionality (e.g. SQL Server can be used with SQL Server Reporting Services and SQL Server Analysis Services), they take special knowledge and experience to program. Finally, databases do not connect easily with other data sources, which can make cross-source analysis difficult.

Do: Use databases to capture and store complex data, allow multiple people to access and edit data at the same time, and couple them with statistical and reporting packages to perform very complex analysis or reporting.

Don't: Use databases for ad hoc analysis and querying, charts and graphing, combining data from multiple sources.

Why Not Both?

Spreadsheets and databases both have their own strengths and weaknesses, but they are very complementary. For day to day data capture and storage, you should use a database. However, when it comes time to do analysis and dig into your data, making an extract of some of the data in your database and putting it in a spreadsheet is a good option. The combination of these two tools allows you to collect and store your data in a reliable location while allowing you to dig deeply into your data to find other insights.

When choosing between a spreadsheet and a database, keep in mind their individual strengths and weaknesses and make sure you are using the right tool for the job! Not sure how to choose for your specific situation? Drop us a line and we're happy to point you in the right direction!

The Strategy-Execution Gap is the disconnect between a company's expected performance based on its strategy and the actual performance when the strategy is implemented. In many cases, when implementing a new strategy, the results are neither what's expected or desired. The Harvard Business Review has written extensively about the phenomenon, here, here, here, and here). The gap can occur when leaders:

Implement a new business strategy without paying sufficient attention to the underlying organizational changes necessary for success
Ignore internal feedback during execution and miss the opportunity to adjust accordingly
Fail to recognize and/or respond to changing market conditions

Often, leaders, in the belief that they have an analytically sound strategy, attribute failure to under-performing employees. However, employee under-performance is rarely the root cause. If leaders are able to recognize unexpected and undesired results as an opportunity to revise strategy and/or execution, results may improve and the success they had initially predicted may ultimately be achieved.

The Wells Fargo fake accounts scandal is a great example of the Strategy-Execution gap. In this case, Wells Fargo leadership developed an aggressive sales strategy of cross-selling. However, in implementing the strategy, they ran into several problems. First, they had not correctly predicted or possibly considered the limits of their customers' wallets. Second, they had set unrealistic performance targets for branch employees and put intense pressure on employees to meet those unrealistic performance goals. Third, they failed to recognize what was happening and continued to implement a flawed strategy for a number of years. As a result, thousands of employees "met" performance targets by opening fake accounts because they were unable to meet them with real accounts and the consequence for missing targets was termination. Ultimately, Wells Fargo was fined millions of dollars, employees were fired, and the CEO resigned. It's hard to believe that this is what they had initially envisioned as the outcome. Perhaps, improved feedback between the executives who designed the strategy and the leaders and employees responsible for implementing it would have led to a more desirable outcome.

Strategy is a Hypothesis

Fortunately, the Strategy-Execution Gap can be overcome with flexibility in managing both strategy and execution. Particularly, you should think of your strategy as a hypothesis to be tested. By taking a strategy as learning approach, senior leadership can continuously compare results with their expectations; and investigate when they don't align. The reasons for a gap are many. Perhaps customers behave differently than expected. Maybe a competitor has made an expected move. Alternatively, the rest of the organization might not understand the strategy fully and may not be making the right choices to implement it. Still another possibility, the people in the company are actually under performing. Any or all of these factors could be at play. This is why companies must continually measure performance, learn, and adjust.

Strategy is the hypothesis and the scientific method can be used to evaluate its implementation. In the business world, we refer this method as the plan-do-check-adjust cycle. For strategy and execution, the cycle is as follows:

Use the Plan, Do, Check, Adjust Cycle to manage the execution of your business strategy.

The Right Data is Key!

The key currency in the Plan-Do-Check-Act cycle is data! As you execute a strategy, collecting data about what you did and what happened is critical to evaluating how the strategy worked and how you should adjust based on your new knowledge. The data you'll need to evaluate your strategy, learn from your experience, and adjust comes in three main flavors.

Data about what happened

Probably the data that people think the most about is data about what happened. What were the results? How many widgets were produced? What happened to sales, revenue, expenses and profit? Did market share change? Ultimately, these are the data points that you will use to determine whether your strategy is being successful. Thus, you must carefully define what success looks like for the strategy. Is the purpose of the strategy to increase market share? Reduce expenses? Improve production? Whatever the overall goal is, the data you collect must allow you to evaluate whether the desired results were achieved.

Data about what you did

As important as data about what happened but not nearly as obvious to people is the data about what you did. Understanding the actions that the organization took to implement the strategy is the other half of determining cause and effect for your strategy. Gather data about how the business processes changed in implementing the strategy. Did marketing change their social media strategy? Did sales offer more discounts? Did production run more shifts? This data can be connected with your data about the outcome of your strategy and help you understand how various changes to your business impacted its overall performance and the achievement of the goals of your strategy.

Data about the conditions around you

As important as understanding what is happening within your business, it is equally important to understand the conditions in which you are operating. Your business does not operate in a vacuum. Thus, accounting for changes in customer behavior, competitor actions, and larger economic forces are key components of successfully formulating and implementing your strategy. Data about competitors and the market as a whole is often the most difficult to come by. Sources include research firms, trade journals/associations, and your own company's research. Regardless of your source, it is important to carefully integrate your internal and external data to provide the full picture of your business environment. With this full picture, analysis of your strategy can offer much stronger conclusions about what worked, what didn't, and—most importantly—why.

Analytics Makes Sense of it All!

While it is clear that data is vital to evaluating your strategy, doing it consistently can take a lot of effort, especially if you are doing it manually! Larger companies, with a multitude of data sources and many people, have been using analytics to make sense of their data for years. Fortunately for smaller companies, newer analytics and reporting tools can quickly integrate data from multiple sources, making it easier than ever for small companies to take advantage of the power of their data!

For simple data analysis, I typically use Excel because it is quick and easy. However, as soon as there are multiple data sources involved I tend to use more powerful tools like Microsoft's Power BI. These tools allow me to pull data from multiple data sources, clean the data, and define how the various sources relate to each other. Then, digging into the data is as easy as drag and drop to create visuals and slice the data every which way!

You can do it too!

It's tempting to think everything I've talked about only applies to big companies, but it's simply not true. In the age of eCommerce, Amazon, and rapid changes in the marketplace, staying on top of your strategy and making sure it changes as you learn are vital for the growth and success of companies of all sizes. We can help you build the learning process into your regular routine and be your partner for working more efficiently, choosing and implementing the right technology for you, and unleashing the power of your data to make better decisions.

Contact us below to find out more about how we can prepare your company to compete and grow in today's fast paced business climate!

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Spreadsheets vs Databases, Which Should I Use?