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For most of us, it’s impossible to consider doing our work without the internal systems that communicate, organise and report on our efforts. Impossible to consider a world without emails, wikis and financial software that are invisible to the outside world, but fundamental pillars supporting the business. And, for the most part, these systems are just that — critical. But are they efficient?
Efficiency can only be determined by looking at the sum of its parts. To use a simple example, manually copying information from an email into a wiki can be made more efficient by integrating the two technologies or skipping one altogether. Typically, as a business evolves, its efficiency needs grow causing the complexity and customisation of the supporting IT systems to grow as well. The scale starts with a cobbled together system of emails and wikis and moves through to large ERP systems such as SAP. But what should you be looking for when designing and choosing these systems?
The first consideration is the outputs you require. Sometimes these will be simple and focussed, such as the centralised collection and organisation of company documents. An ecommerce system may need to track and report on sales, inventory and returns. Sometimes, however, the scale and complexity of the business makes the output more difficult to determine upfront, particularly where these outputs are human generated. In these cases, you may need to start with collecting data and interrogating it to determine the correct measurements.
In this case, what should you capture? This is a far trickier question than it appears, as you must take the cost of data collection into account. A typical question faced, for example, by most professional services companies is whether to ask their employees to log time. If you do log time, do you try to capture all possible time or just billable time? The risk is that by focussing on capturing the wrong data you increase inefficiency and it could also lead to poor decisions when analysing it later.
Another important point needs to be made around trusting your data. It sounds nonsensical to collect data and then not trust it enough to base decisions on, but this is exactly what many businesses do. There are few more powerful business tools than accurate, trustworthy data — and few more debilitating ones than a system that is “good enough” to remain in place, but not trusted by the executive to make critical decisions on. Trustworthy data is not a destination, but a journey — particularly where human inputs play a significant role.
But let’s assume the systems are in place to collect trustworthy data — often a mighty effort that involves changes to business process and needs buy-in at all levels of the organisation. You’re not done yet though — you must now analyse the data. Raw data amounts quickly, so good tools are necessary. What you need is a way to get an overview of information and then an ability to drill down in ever-increasing detail to answer specific questions. Practically, this translates to the combined functions of filtering and grouping data on arbitrary criteria — after all, who knows where your analysis might lead you?
But still you are not done. Most people in the organisation are not data analysts, and in any event the management of a business is an ongoing affair and needs consistent metrics to determine progress over time. The final hurdle is in determining the correct metrics to measure the business on. Choose the right ones and employees can be motivated correctly, choose the wrong ones and you waste time and energy focussing on marginal or detrimental activities.
Presentation of data is critical too — like it or not many people are visually orientated and simple charts can make plain what a table of numbers cannot. Information systems can only be as good as the people using them, and the sustainable way to use them efficiently is to engender a sense of ownership around the relevant metrics at all levels of the organisation.
Hopefully, by the time you’re done your efforts will have highlighted inefficiencies, and business processes can be changed to eliminate them. And then it’s time to iterate — considering your data collection, trustworthiness, analysis and metrics all over again. It’s not easy, but the reward is an efficient business that thrives when others are competing and survives when others do not.