All businesses generate data during operations but instead of leaving it to gather dust in a hard drive, why not make use of this resource? No matter what format it comes in, data is crucial to uncovering the beating heart of a company and transparently showcasing the performance of its day-to-day processes. It allows a company to investigate its strengths and weaknesses, and where further development will optimise their business strategy.
Seeking this informative data from as many different areas as possible ensures that decisionmakers can get a full picture of the company as a whole. However, this comes as a double-edged sword as it can also lead to integrity issues. The two fundamental challenges of data collection are the assortment of formats they come in and the range of locations they are stored in.
Businesses often find themselves at a crossroads, faced with complex choices that require analysing and seeking actionable insights from multiple, disparate data sets. Traditionally, a business will rely on the expertise of its leaders, anecdotal knowledge of business performance, or experience gained in the company’s past pursuits. A business intelligence analyst requires this and more, including an in-depth understanding of the organisation’s operations and the costs, level of risk, operational performance, system productivity and data safety that encompass it. This is because these factors are of paramount importance when planning and delivering any business strategy. Trying to balance these priorities is a complex task for any executive team; however, there is nothing more persuasive than having hard data to solidify your position.
Businesses can utilise data to make key decisions and observations on:
- Business performance tracking (revenue, growth, business sustainability and annuity).
- Client experience (performance and satisfaction analysis).
- Sales performance (compliance and best practice).
- Risk and response analysis (insurance and crisis management).
- Asset management (performance and lifecycle management).
- People and company culture (training requirements and sentiment analysis).
- Utilisation of available technologies and automation (data quality and timeliness).
- Brand awareness and marketing strategies (social media and digital marketing engagement).
Dealing with your data Mountain
Data can help pinpoint what exactly went wrong during a slow sales month, negate the risk of an unnecessary backlog of product or service delivery, highlight missed innovation opportunities or track an increase in negative customer experiences. By reviewing data from various sections of a company, one can generate an insightful overview of unique processes and focus on how these do or don’t work.
Capturing data from all over the business is central to ensuring there is an overall snapshot of the current business performance; however, this can be problematic. Much of this data will be independently curated and sit in a range of different formats and systems. When businesses start collecting data, it is often focusing on addressing one particular area and therefore it’s highly unlikely to be formally documented and stored to account for how future data collection will take place.
Is all that data making you dizzy?
Data is often not organised in a predefined way and can be peppered with anomalies or incorrect formatting. This data can be human-generated or machine-generated, in a textual or a non-textual format.
To further complicate matters, this data is typically stored in various formats and housed all over the place. These locations include:
- Enterprise Resource Planning (ERP) software for finance and procurement.
- Customer Relationship Management (CRM) tools for client management.
- Project trackers for costs, planning, time and risk.
- Asset management systems to keep on top of key resources.
- Standard business data such as documents, spreadsheets and PDFs.
- Team-based data platforms like SharePoint, Dynamics. Drive. Dropbox and employee communication products such as Microsoft Teams or Google Meet.
When data is spread across these various silos it can be almost impossible for a business leader to effectively read into this well of information and extrapolate meaningful results. Instead of seeing the whole picture, a company can only access and operate off what each data silo holds . With the huge range of available data, there is a significant risk that there will be incompatibility issues. Having all this potentially useful information in several different data silos makes for challenging analysis in the short term and leaves business leaders with two options:
- Manually collate and organise this disparate data into a single, compatible format.
- Use a business intelligence tool that can read different formats from different sources and bring them together.
Collating data manually
The company’s IT team will need to identify each data source, access each of these systems and collect all the usable data in turn. Any alterations to the data will need to be decided, governed and implemented before being placed into an appropriate centralised data storage system.
The data will, however, likely need to be cleaned and formatted to fit within a predetermined structure. Through data cleaning, this wealth of information will be appropriately formatted and ready for business intelligence tools to use.
Retaining all the available data and not simply extracting data ‘as needed’ is of paramount importance as key information could be easily lost throughout the manual process.
Depending on the scale of the company and quantity of recorded data, manual data collecting can be an extremely expensive and painstaking task. Instead of seeing relevant and real-time insights, as found using BI tools, this slow manual process will only show a static snapshot of the data which can quickly become outdated as even newer data is created minute-to-minute. With the overwhelming amount of data values and limitless formatting issues, manually combining these data sources is undoubtedly extremely difficult. Moreover, the regular manipulation of data by users in in Excel can lead to large scale invalidity: A single error or removal of a cell can result in the single source of truth not being true.
Using a Business Intelligence tool
Instead of wasting a considerable amount of costly manpower to reorganise this data manually into one central system, a company can instead use a platform that can read and relate these different formats automatically. By using specialist and affordable, enterprise-ready business intelligence software, such as Qlik Sense or PowerBI you can simultaneously clean and analyse the data provided from a range of different sources. This data can then also be utilised much more quickly and effectively.
Data analytics tools are an important layer in your operational processes, providing a method to convert your raw data into meaningful insights, especially when combining a diverse range of sources. It will also improve customer or stakeholder experience (CX) by ensuring that each individual viewing the data sees the view most customised to their role and relevant to them, whilst using the same data source as another user with a different view. This will get the most out of the existing data pipeline and greatly enhance the deep and transparent insights you receive from all your data. As an experienced business advisory and data analytics solutions provider, we at Cast Solutions can bring all these sources into a business intelligence tool to create a single, personalised view of the business.
By using an enterprise business intelligence tool to pull together your data into a dashboard, Cast Solutions can help to find a way to ensure all this disparate data from a variety of different systems and formats can be related in the most meaningful way. Enlisting specialists to create this allows you to focus on running your business, whilst the experts can handle the complex task of managing the end-to-end analytics system set-up.
