CampionPPS : Business Intelligence Blog

It has become increasingly important for supply chains of today to effectively report upon business performance, both as a means to assess where the organisation has been, but also to determine where it is heading and for shaping future direction. As part of this process, it is key that the organisation involved defines appropriate supply chain report metrics and KPIs for the purposes of monitoring and control. This aids understanding the business in a more meaningful way, provides a benchmark against which to assess ongoing performance, identifies the need to respond to any gaps against target, and offers direction as to those business critical areas requiring focus. Increasingly, more and more detailed supply chain reports has become the norm, as has the need for real time solutions facilitating rapid drill down of information in order to achieve a more visible, efficient, and responsive supply chain structure. Reporting can take place at an operational day-to-day level, at a tactical level, and at a more strategic longer-term level. Modern BI solutions, such as InetSoft Style Intelligence, can support these supply chain report needs for greater transparency across organisations and the desire for rapid, more detailed reporting requirements to aid decision making through all levels.

Supply Chain Report Metrics

Firstly, modern BI solutions are intuitive. Through a process of exploration, it is possible to create appropriate supply chain report metrics and KPIs in order to measure, control and report upon business performance. In setting and communicating required targets for customer service, inventory, waste, or supplier delivery performance both internally and with external partners, it is possible to monitor and control operations more effectively having established a benchmark by way of reference.  As an example, if you are unable to prove that a supplier is performing poorly versus expectations, how will you ever bring about any marked improvement in their service level? Alternatively, if maximum capacity levels aren’t referenced, how will the business know to respond to situations where there is insufficient machine time or labour for future demand and plan accordingly? Through the use of defined KPIs and the reporting of expected and actual delivery (or non delivery) against these established metrics, BI solutions improve visibility, provide information to aid decision making, and assist in more tightly controlling operations.

Data on the Fly

Secondly, modern BI solutions allows access to a diverse range of information platforms, and are able to extract detail directly from the source on the fly. The result is that the provision of data isn’t dependant upon complex predefined structures or lengthy ETL processes, potentially impacting time to response through a delay in the availability of report requests.  Instead, today’s BI solutions permit real time reporting using information from numerous sources that can be presented in a single, intelligible view and in a way which is meaningful to the end user. The result is therefore one less constrained by data availability and typified by a need to sift or sort irrelevant information, and more concerned with the actual needs of the recipient. People across the supply chain can benefit from such supply chain reports.  Be it a planner who must respond to low inventory levels due to heavy orders, or a supply chain manager who wishes to review waste levels over a particular timeframe for budgeting purposes. The BI solutions facilitate more detailed, adhoc, real time reporting including the potential to use push alerts or notifications for variances versus expectations, and in doing so improve time to response and visibility.

Self-Service BI

Thirdly, modern BI solutions are extremely user friendly and are not heavily reliant upon IT involvement. The supply chain team can create their own supply chain reports and analysis to suit themselves – taking advantage of self-service BI.  It’s about placing the right information in the hands of those in a position to actually respond to it, at the right time.

Finally, many BI solutions encompass the facility to trend data. This aids reporting in determining a predicted landing or future position across the supply chain, and reparatory action can be taken as necessary.

InetSoft BI

The InetSoft Style Intelligence solution is an ideal fit for supply chain report delivery – take a look for yourself http://www.campionpps.co.uk/business-intelligence.html

There is good news for businesses and BI users as more affordable, easy to use and easy to implement BI solutions appear on the market.  Easy BI models are all the rage.  No longer do companies have to dig deep down into their coffers to invest in overtly expensive and complex BI solutions.

BI tools are critical for effective management and decision-making, yet many businesses have in the past refused to invest in costly BI solutions that prove far too complex to implement, manage or use.  The complexity of BI technology has meant that, historically, they tended to be intensively IT dependent.  One effect of this was that simple procedures that ought to be carried out at the user level ended up in a queue for action by IT experts.  The IT team was therefore responsible first for implementing the BI solution, integrating new data sources, running reports, updating the solution as well as responding to random or ad hoc queries by users.  It was therefore no surprise that many BI implementations failed as IT struggled to keep up with the demands and struggled to deliver a BI solution that was fit for purpose. And users also required extensive training to grasp even the basics of the BI tools.  Decision makers found themselves no better placed as the information was locked away in the BI solution; accessible only by an IT expert.

Fortunately, the market has responded to these ills by providing a newer breed of easy BI applications that prove not only more affordable but much easier to use.  It is forecasted that there will be a higher rate of adoption of BI solutions as businesses strive to become more efficient and to get ahead of the competition.  And they now have more confidence to invest the time and money since the new ‘Easy BI’ models pose much less risk and offer much quicker ROI.

Inetsoft boasts a zero-client easy BI solution – not only is it easy to implement but it is also easy for users to understand and use themselves.  The Style Intelligence BI platform requires minimum IT expertise to deploy the software  and can be up and running in no time.  It also has a shallow learning curve requiring only excel level skills making it much more attractive to users.  Inetsoft promises greater overall BI self-service for users with data sources being easily integrated through a point and click visual interface and intuitive data visualisation tools.

Business Intelligence has just gotten easier and one thing remains certain, users will continue to see even more new and interesting developments aimed at making every end user a BI expert.  And that’s why Campion PPS are big fans of Easy BI.

The public sector hasn’t really been our target market over the years – although many of the team have public sector experience, we’ve tended to focus more on the manufacturing and supply chain sector.  However, as lean becomes more and more relevant for public sector bodies, we’re finding that our lean manufacturing background and our BI toolset present a compelling combination that can help with the ‘lean government’ transition.

So we’ve pulled together a highly effective lean performance management platform – using the InetSoft business intelligence solution together with our lean transformation know-how.

CampionPPS are specialists in ERP, performance management, process improvements and getting more value from business systems.  We are all about bringing people, processes and systems together for optimum results.  So overlaying all that with the InetSoft BI to create a lean government toolset made perfect sense.

It enables government departments to track, understand, and manage their business in order to maximise business performance.

Business Intelligence Benefits

Business Intelligence can be a driver for continuous improvement of costs, quality and customer service:

• Improve operational effectiveness
• Make faster, better decisions
• Increase business insight
• Tighten governance and control
• Ensure transparency
• Reduce costs
• Improve quality

A lean government can be achieved with business intelligence – focusing on efficiency, value and savings.

InetSoft BI Features

InetSoft is really quick and easy to get up and running – rapid implementation, shallow learning curve:

• Easy: Unite every major system – easily
• Agile: Link systems with adhoc spreadsheets – quickly
• Robust: Track, manage, improve performance – robustly

Imagine one fast, effective dashboard delivering complete visibility across all departments.

Lean Government

CampionPPS combine lean transformation know-how with easy, agile and robust business intelligence – the ideal combination for lean government.

Join us at our Masterclass at the Lean Government event in London on 22^nd September – http://tinyurl.com/3w7g4ky

In our recent blog article, ‘BI Supports a Lean Supply Chain’ we identified how newer generation BI technology can be seen to support lean methodology within the supply chain function. In this second article, we will discuss how these BI systems not only assist with the identification, monitoring, control and reduction of waste via supply chain metrics, complementing other lean techniques, but how the technology in itself is ‘lean’.  Lean BI, Lean IT …

As outlined previously, lean methodology consists of a series of tools and techniques used for the systematic identification, reduction, and removal of waste within an organisation. The concept is customer focused, and having defined the appropriate ‘customer value’ level, any activities failing to contribute to this overall value are seen as waste or non-value adding. A key focus of the strategy is the reduction of unnecessary cost using existing resource, freeing up additional time or capacity to spend on those activities contributing to improved performance, efficiency, or profitability.

Newer BI systems can be characterised by the need for a less complex IT infrastructure. Their ability to tap into a diverse range of information real or right time on the fly, overcomes, in many cases, the requirement for large data warehouses and significant ETL processes to present data in a format which is meaningful to the end user. This approach of using as few components as possible, and linking directly with the relevant source data, removes any unnecessary IT involvement in writing rigid structures and implementing a costly data warehouse solution. There is no middleware involved. Lean BI, Lean IT…

There is also minimal IT team input throughout, be this in setup or maintenance. The fact that structures aren’t hard-wired before any user requirements are discussed prevents the need for costly rewrites at a later stage. Instead, new generation BI solutions give the power back to the end user, allowing them to create queries and present findings using only information in which they are interested. These solutions reduce implementation and maintenance costs, increase available capacity within the IT function, free up processing power no longer spent on resource hungry ETL activities, and save time for the end user. Be this due to their not having to wait upon requests for report modifications as a result of predefined structures only a techie can navigate, or sift through a mass of data rather than only that of interest. Lean BI, Lean IT…

With an improved time to value and reduced cycle of implementation over more traditional BI systems, newer solutions are lean in reducing unnecessary processes. Large costs aren’t spent on development and lengthy installation, and resource isn’t required over an extended period and on a heavy ongoing basis. In providing a flexible approach tailored to the organisation at inception rather than a rigid system, numerous iterations aren’t required and so costly redevelopment costs minimised. The idea is that the first version fits the organisation from day one. The potential to run systems via a web based portal whereby servers are hosted by the software provider, flexible purchasing approaches, and the lower cost associated with introduction, be it through reduced development and maintenance charges or server requirements, all contribute to a ‘lean’ approach. Many packages integrate with a range of other products using standard technologies already on the market, leading to a reduced need to develop appropriate interfaces. The result is fewer end user packages to work with, as data is consolidated into one all encompassing tool, providing a streamlined, leaner, system.  Lean BI, Lean IT…

In summary, modern BI solutions can help to develop lean business functions by helping to identify, monitor, control and reduce waste, but they can also help to develop a lean IT function.   Lean BI, Lean IT…

In previous blogs we have looked at data mashup and compared it with data warehousing techniques.   Because data mashup is such a relevant discussion for the future of BI systems, we have decided to give it a further look.  This time focusing on the relationship between data mashup and self-service BI.

What is Data Mashup?

Data mashup is the term used by BI experts to describe applications used to combine disparate data sources on the fly without the need for a data warehouse or an ETL process.  Data mashup not only allows users to combine data from disparate data sources but also enables users to combine data from different tables within a single data source.

Data mashup is key to self-service BI as it gives users the capacity, not previously had, to experiment and combine their own data sources.  Users can either combine data sources from different fields that have been intentionally exposed to a BI system but not yet mapped in a data schema or they can integrate their own external data and combine it with data sources already available within the BI system.

Data Mashup meets Self-Service BI

In many companies where BI applications have been implemented there have been significant challenges to the implementation process.  Some of the principal challenges that have been faced by businesses are the high demand on IT personnel to drive many of the BI functions, lack of technological skills by end-users and decision makers, and the general complexity of most BI solutions making it hard for users to manipulate without long periods of training and introduction.

Data mashup is an enabler for businesses to benefit from the many virtues of self-service BI.  The relationship between self-service BI and data mashup changes the orientation of the BI solution from IT expertise based to being business-user centric.  By putting power in the hands of end-users they can define data relationships and explore with different data sources.  The fact that users best understand the results they need to achieve allows them to manipulate the data to establish the best data relationships to produce the best results.

With self-service BI, end-users drive the BI process thereby creating a more adaptable, flexible BI solution.  Instead of the scenario where IT sets up the data relationships ahead of time, by giving end users the capacity to mashup data they can, gradually, identify their data requirement needs and respond by creating data mashups to match those needs.  Flexibility is further added as users will be able to create data mashups as their needs and those of the business change over time.  Rather than trying to second-guess them upfront and then being stuck with what you’ve got and unable to change it as the business requirements evolve.

There are plenty benefits when data mashup meets self-service BI.  By empowering users the success of the BI solution is increased significantly as users no longer view it as complex and outside their grasp.  They become better able to find more effective solutions themselves and with the wide scope for experimentation, they will become the key drivers of the BI solution.

The Verdict

The data mashup / self-service BI approach offers up various improvements to business performance, but end-user satisfaction is a key outcome that in itself will deliver benefits such as a higher success rate of deployment, usage and adoption.  Cost reductions can be achieved too since there is much less need for IT experts and highly skilled data analysts, and the training investments required for the business-users is also much less.  (And we’ve already highlighted in previous blogs the savings that can be made due to the fact that the high costs associated with data warehouses and ETL can be avoided).

There are obviously business benefits to be had from the successful implementation of any BI solution approach.  However, these business benefits can be multiplied with a data mashup approach, not least because it truly opens up the enablement of self-service BI.  Note: BI vendors have been claiming their BI systems delivered self-service since the day dot, however, in most cases this was a rather disingenuous claim…

In our recent blog article, “Using BI to Manage your Supply Chain Metrics”, we outlined the benefits of newer generation BI tools in helping to assess, monitor, and control business performance through the use of appropriate supply chain metrics. In helping to define relevant metrics to measure operational performance real time or near real time, and in aiding decision making by providing access to previously untapped information on the fly, we discussed how such tools assist individuals at all levels in shaping business direction. These packages facilitate greater visibility across the organisation, and in turn help to control costs and highlight key problem areas where efforts to improve efficiency should be focused.  So how can BI support a lean supply chain?

Lean Methodology

The main thrust of lean methodology revolves around putting the customer first, and in doing so, is concerned with the identification of those processes which do, and more importantly do not, contribute to overall customer value. Many argue that the concept itself is made up of a number of interrelated tools (Kanban, JIT etc), which when combined, help to achieve the systematic identification and timely removal of waste within the business. That is, processes which don’t have any real purpose or are non-value adding. A key aim of lean is to reduce cost using existing resource, and free up additional time or capacity which can then be directed to those areas offering real business benefit and an improvement to bottom line performance.  The premise is very much one of more for less; better quality, improved effectiveness, and increased profitability, at reduced cost and using existing operations.

Lean Supply Chain

Given significant economic pressures, there is a clear need to improve efficiency and reduce costs across the supply chain, whilst maintaining exacting quality standards in the face of heavy competition. An example of this need to reduce spending whilst delivering exemplary levels of service would be the situation currently faced within public sector healthcare. Whilst lean methodology is concerned with the identification and elimination of waste, it does not necessarily determine where best to utilise any additional slack created. A BI tool can help on a number of fronts to support a lean supply chain.

Firstly, through the definition and use of supply chain metrics, newer BI solutions provide a means to monitor and shape business performance, measure improvements made, and identify key areas of focus. These tools can be used to track such things as supplier performance, customer service or satisfaction, inventory value, returns, sales or lost sales, machine efficiencies, cost of specials, and shortcode or discounted product levels. Through the use of metrics, it is possible to benchmark performance, and identify variances outside of tolerance for address. For example, a particular packaging supplier may consistently fall short of requirements, with numerous failed deliveries. The impact of their poor performance is increased specials and a premium charge, or delivery failures of finished goods impacting customer service and resulting in a bill for loss of profits. Without a means to identify these non value adding activities and additional costs, how would the business know where to focus its energies? A good BI solution can complement other lean techniques in ensuring resources are directed to the right areas.

Secondly, the provision of information real time, or right time, improves responsiveness and enables reparatory action to be taken perhaps sooner than it otherwise would. Therefore, rather than becoming aware of a variance too late to positively impact any outcome, those at an operational level can make informed decisions and adapt to the risk as it occurs. In the case of the failed supplier delivery mentioned earlier, action may be taken to source finished goods from an alternative warehouse, agree a short upfront with a friendly customer, or pro rata available supply. The facility to trend performance can also assist in spotting and eradicating potential problems ahead of time. So when reviewing historic machine efficiencies vs expected demand for example, it may be possible to identify likely pinch points and flag them for address. The result could be a smoothing of demand by moving promotional proposals around, or an early stock build to ensure sufficient inventory is in place at a time when capacity is tight. In addition, capturing a history of poor performance would perhaps assist the company engineers in determining equipment requiring closest scrutiny. In improving responsiveness, a BI system supports a lean supply chain methodology in helping to identify and remove potential non-value adding activities or costs before they occur, and in reducing their impact if they occur.

Finally, BI solutions also provide direction as to where additional slack created can best be utilised. For example, in trending internal sales data in conjunction with external market data or information from social media platforms, it is possible to determine best sellers, SKUs to be removed from the range, place in the market, and growing or shrinking sectors for entry or exit. As such, it facilitates more informed decision making in determining where to focus efforts for maximum reward, and assists in avoiding potentially costly mistakes.

Supply Chain Performance

In summary, BI tools support a lean supply chain in providing the means to extract, analyse and monitor detailed supply chain performance information and providing direction as to where efforts to reduce waste are best spent. The availability of data real time and the facility for trending performance allows pre-emptive action to be taken to reduce risk and any associated waste, and improves time to response in the event of unforeseen occurrences. At both an operational and strategic level, BI can aid the business in determining where additional capacity created through any lean approach should be utilised.

Much of the debate within the Business Intelligence (BI) community continues to be centered on the role of the data warehouse in a BI solution.  The consensus seems to be that data warehouse continues to be relevant to BI solutions especially for enterprise where there is a vast amount of data.  In fact, many of the modern BI solutions, though not requiring the existence of a data warehouse, are often designed to integrate horizontally and interact with a data warehouse where one exists.

Data warehouses are often criticised for being costly and complex to manage generally making them less suited to SMEs and less oriented towards a self-service user approach.  The problem is that instead of revisiting the role of the data warehouse in BI solutions, many BI vendors have been taking a dogged approach that is reliant on businesses investing heavily in a data warehouse as a part of their BI solution.  There has also been a tendency to expand data warehouse into other applications.  A common perspective is that the data warehouse approach to BI is relevant, even necessary for large enterprises, while the new BI solutions are best suited for SMEs.

However, for any BI implementation to be successful, first consideration must be the needs of business including an overview of business dynamics.  Consideration must be given as to how best these needs can be satisfied, whether by using a traditional BI solution or a modern BI application.   Traditional BI using a data warehouse tends to be associated with historical data while modern, web-based BI solutions are largely associated with operational / transactional / or current data.  Some businesses are more reliant on current or operational data to produce on the fly reports and intra-day analytics.  On the other hand, there are businesses that have a greater need for historical data, for example in the health industry information derived from analysing historical data is often used to inform policy and resource management and allocation.  So the key consideration as to whether data warehousing is an appropriate BI approach is really around what type of data is at the core of your business and what you want to do with that data.

It is relevant that data warehouse architecture was introduced to correct for a number of problems associated with the early Decision Support Systems (DSS).  Often the data required existed in disparate sources, also in its existing form the data was unsuitable for reporting. There were also data quality issues and a lack of historical data.  Data warehouses were the unique solutions to these problems allowing for the easy integration of data sources and the creation of an historical data archive.  Combined with an ETL process data quality and reporting issues could then be resolved.  However, BI technology has improved and progressed remarkably, developing new ways of addressing these challenges.  For example, data mash-up techniques improve the interaction with operational data enabling data mash-up across multiple data source.  Refined ETL processes within web-based solutions have led to BI solutions that are not only more cost effective, and less complex but also more agile.

The key point really is that there is just much more choice these days in what sort of BI solution you implement and it can be tailored more closely to fit your business – in terms of scale, technology, cost and business model.  Data warehouses come into their own when there are huge amounts of data or where there is an emphasis on historical data analysis and for many enterprise it is the right approach.  However, as the BI technology progresses alternative approaches such as data mashups without the need for data warehouses become a valid option even for large enterprises with large data volumes.

It’s not just one-size fits all any more…

With the need for companies to remain competitive under difficult economic circumstances, tighter margins, and complex global networks, cost cutting and the streamlining of operations are important factors impacting overall supply chain performance. The identification, reduction, and timely elimination of cost drivers within the supply chain, provides a means by which significant improvements to bottom line and profitability can be achieved.

In the face of heightened competition and greater uncertainty regarding consumer spending patterns, there is recognition of the need for faster, real time decision making power, a shorter time to response, and the monitoring of performance via relevant metrics. These supply chain metrics, or key performance indicators (KPIs), aid individuals at all levels to understand the business in a more meaningful way. By comparing predefined and acceptable targets for sales, waste, inventory, returns, customer or supplier performance etc, against those levels realised, supply chain metrics can be used to aid the decision making process. They provide a way in which to assess, monitor, and control supply chain performance ongoing, and in doing so offer a history of where the business has been, but also a view of where it is going.

In itself, the need for greater visibility throughout the organisation, and specifically responsiveness within its supply chain, creates a number of challenges. Whilst understanding the requirement for more timely information, many businesses are simply unable to extract relevant data from the breadth of sources available for interpretation, or are reliant upon the provision of detail post the event.

The potential outcome? A lack of accessible information that prevents managers identifying and addressing the root cause of many issues, or from taking time sensitive decisions due to the delay in its availability. This may be the cutting of production in the event of poor promotional performance, the moving of inventory between warehouses to avoid stock outs, or an important call to a supplier regarding a failed delivery of product required for that day. This could impact supply chain performance in a variety of ways, such as: increased costs of holding inventory no longer required, potential waste, delivery failures, additional specials, and a dip in customer service or bill for loss of profits may ensue.

This is where newer BI solutions offer benefit:

Firstly, they provide accessibility to a diverse range of information, from Excel spreadsheets to social media platforms, with minimal user training. They are easy to deploy and even easier to use, and with limited IT involvement, data can be presented and structured in a visually impactful manner, and in a way that is straightforward to understand and manipulate ongoing. Performance in terms of expectations vs actuals can be monitored via appropriate supply chain metrics, and reparatory action taken as required. This may involve for example, trending and benchmarking supplier delivery performance, and holding subsequent discussions regarding quality, cost, or lead-times based upon findings. Through clearly defined supply chain KPIs, suppliers will more closely understand what is expected of them, as well as any standards they must achieve. Without a base standard or means to monitor performance, improvements are difficult to quantify, and costs harder to control. A BI system provides this means.

Secondly, they permit access and retrieval of information for analysis real time (or more importantly at the right time), without significant delays to query performance. Data previously difficult to extract is made available on the fly, permitting a swifter response from those individuals at an operational level with day-to-day decision making power. By defining supply chain metrics upfront, and in returning data real time via the BI system, it is possible to have an almost live view across the organisation and to identify variances against expectations as they occur. Any deviation from tolerance is quickly highlighted driving an appropriate response, as individuals see only relevant data via their supply chain dashboard rather than all data.

Thirdly, they aid, through exploration, the creation of appropriate measures and metrics upfront. By unlocking useful information, it is possible to determine supply chain metrics in a level of detail that more closely fit the needs of the organisation. An ideal world, rather than a solution based upon best endeavours with the data that is available.

In summary, the newer generation of BI solutions provide a means to define relevant metrics for the monitoring and control of supply chain performance, but also the tools to access, retrieve, interpret, and respond to information in a timely fashion via a format that is meaningful to the end user.  This in turn aids greater transparency throughout the organisation, cuts down time spent developing reports which aren’t fit for purpose, and assists overall decision making.  Using a good BI tool to manage your supply chain metrics can greatly enhance your supply chain performance.

Music to our ears – users driving BI demands for ease of use and context functions.  This is at the very heart of the InetSoft BI solution approach – easy, agile and robust self-service BI.

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UK based plastic moulding company chooses Style Intelligence to create data mashups from Baan ERP system data

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